Publications

Conference papers

AAAI Conference on Artificial Intelligence (AAAI)

• Sam Goree, Weslie Khoo, and David Crandall. Correct for Whom? Subjectivity and the Evaluation of Personalized Image Aesthetics Assessment Models. In AAAI Conference on Artificial Intelligence (AAAI). 2023.
• Jinqi Xiao, Chengming Zhang, Yu Gong, Miao Yin, Yang Sui, Lizhi Xiang, Dingwen Tao, and Bo Yuan. HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks. In AAAI Conference on Artificial Intelligence (AAAI). 2023.

• Mohsen Heidari, Ananth Grama, and Wojciech Szpankowski. Toward physically realizable quantum neural networks. In AAAI Conference on Artificial Intelligence (AAAI), volume 36, 6902–6909. 2022.
• Nikolai Karpov and Qin Zhang. Instance-sensitive algorithms for pure exploration in multinomial logit bandit. In AAAI Conference on Artificial Intelligence (AAAI). 2022.

• Seung Lee, Bradford Mott, Anne Ottenbreit-Leftwich, Adam Scribner, Sandra Taylor, Kyungjin Park, Jonathan Rowe, Krista Glazewski, Cindy E Hmelo-Silver, and James Lester. AI-infused collaborative inquiry in upper elementary school: A game-based learning approach. In AAAI Conference on Artificial Intelligence (AAAI), volume 35, 15591–15599. 2021.

• Caleb Kisby, Saul Blanco, Alex Kruckman, and Lawrence Moss. Logics for sizes with union or intersection. In AAAI Conference on Artificial Intelligence (AAAI). 2020.
• Kyle Richardson, Hai Hu, Lawrence S. Moss, and Ashish Sabharwal. Probing Natural Language Inference Models through Semantic Fragments. In AAAI Conference on Artificial Intelligence (AAAI). 2020.
• Kai-Cheng Yang, Onur Varol, Pik-Mai Hui, and Filippo Menczer. Scalable and generalizable social bot detection through data selection. In AAAI Conference on Artificial Intelligence (AAAI), volume 34, 1096–1103. 2020.

AAAI International Conference on Weblogs and Social Media (ICWSM)

• Diogo Pacheco, Pik-Mai Hui, Christopher Torres-Lugo, Bao Tran Truong, Alessandro Flammini, and Filippo Menczer. Uncovering coordinated networks on social media. In AAAI International Conference on Weblogs and Social Media (ICWSM). 2021.

• Pik-Mai Hui, Kai-Cheng Yang, Christopher Torres-Lugo, and Filippo Menczer. BotSlayer: DIY real-time influence campaign detection. In AAAI International Conference on Weblogs and Social Media (ICWSM), volume 14, 980–982. 2020.

ACM CHI Conference on Human Factors in Computing Systems (CHI)

• Varoon Mathur, Caitlin Lustig, and Elizabeth Kaziunas. Disordering Datasets: Sociotechnical Misalignments in AI-Mediated Behavioral Health. In ACM CHI Conference on Human Factors in Computing Systems (CHI). 2022.

• Sam Goree, Bardia Doosti, David J. Crandall, and Norman Su. Investigating the Homogenization of Web Design: A Mixed-Methods Approach. In ACM CHI Conference on Human Factors in Computing Systems (CHI). 2021.
• Youngseung Jeon, Seungwan Jin, Patrick C Shih, and Kyungsik Han. FashionQ: an AI-driven creativity support tool for facilitating ideation in fashion design. In ACM CHI Conference on Human Factors in Computing Systems (CHI). 2021.

ACM Conference on Recommender Systems

• Antonela Tommasel and Filippo Menczer. Do Recommender Systems Make Social Media More Susceptible to Misinformation Spreaders? In ACM Conference on Recommender Systems, 550–555. 2022.

ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics

• Tingyi Wanyan, Mingquan Lin, Eyal Klang, Kartikeya M Menon, Faris F Gulamali, Ariful Azad, Yiye Zhang, Ying Ding, Zhangyang Wang, Fei Wang, and others. Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction. In ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 1–9. 2022.

• Anuj Godase, Md Khaledur Rahman, and Ariful Azad. GNNfam: utilizing sparsity in protein family predictions using graph neural networks. In ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 1–10. 2021.

ACM International Conference on Supercomputing (SC)

• Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, and others. Clicktrain: Efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning. In ACM International Conference on Supercomputing (SC). 2021.

ACM International Web Science Conference (WebSci)

• Haewoon Kwak, Jisun An, and Yong-Yeol Ahn. A systematic media frame analysis of 1.5 million new york times articles from 2000 to 2017. In ACM International Web Science Conference (WebSci), 305–314. 2020.

ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

• Lizhi Xiang, Miao Yin, Chengming Zhang, Aravind Sukumaran-Rajam, P Sadayappan, Bo Yuan, and Dingwen Tao. TDC: Towards Extremely Efficient CNNs on GPUs via Hardware-Aware Tucker Decomposition. In ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. 2022.

ACM SIGSAC Conference on Computer and Communications Security (CCS)

• Yizheng Chen, Shiqi Wang, Yue Qin, Xiaojing Liao, Suman Jana, and David Wagner. Learning security classifiers with verified global robustness properties. In ACM SIGSAC Conference on Computer and Communications Security (CCS), 477–494. 2021.

• Tao Lv, Ruishi Li, Yi Yang, Kai Chen, Xiaojing Liao, XiaoFeng Wang, Peiwei Hu, and Luyi Xing. Rtfm! automatic assumption discovery and verification derivation from library document for api misuse detection. In ACM SIGSAC Conference on Computer and Communications Security (CCS), 1837–1852. 2020.

ACM Symposium on Eye Tracking Research and Applications (ETRA)

• Zehua Zhang, David Crandall, Michael Proulx, Sachin Talathi, and Abhishek Sharma. Can Gaze Inform Egocentric Action Recognition? In ACM Symposium on Eye Tracking Research and Applications (ETRA). 2022.

ACM Technical Symposium on Computer Science Education (SIGCSE)

• Abe Leite and Saúl A Blanco. Effects of human vs. automatic feedback on students' understanding of AI concepts and programming style. In ACM Technical Symposium on Computer Science Education (SIGCSE). 2020.

ACM/IEEE Design Automation Conference (DAC)

• Peiyan Dong, Siyue Wang, Wei Niu, Chengming Zhang, Sheng Lin, Zhengang Li, Yifan Gong, Bin Ren, Xue Lin, and Dingwen Tao. Rtmobile: Beyond real-time mobile acceleration of rnns for speech recognition. In ACM/IEEE Design Automation Conference (DAC), 1–6. 2020.

ACM/IEEE International Conference on Human Robot Interaction (HRI)

• Vicky Charisi, Selma Sabanović, Angelo Cangelosi, and Randy Gomez. Designing and Developing Better Robots for Children: A Fundamental Human Rights Perspective. In ACM/IEEE International Conference on Human Robot Interaction (HRI), 712–714. 2021.

• Chaolan Lin, Karl F MacDorman, Selma Šabanović, Andrew D Miller, and Erin Brady. Parental expectations, concerns, and acceptance of storytelling robots for children. In ACM/IEEE International Conference on Human Robot Interaction (HRI), 346–348. 2020.
• Megan Strait, Florian Lier, Jasmin Bernotat, Sven Wachsmuth, Friederike Eyssel, Robert Goldstone, and Selma Šabanović. A three-site reproduction of the joint simon effect with the nao robot. In ACM/IEEE International Conference on Human Robot Interaction (HRI), 103–111. 2020.
• Selma Šabanović. We're in This Together: Social Robots in Group, Organizational, and Community Interactions. In ACM/IEEE International Conference on Human Robot Interaction (HRI), 3–4. 2020.

ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED)

• Cheng Chu, Nai-Hui Chia, Lei Jiang, and Fan Chen. Canopy: A CNFET-based Process Variation Aware Systolic DNN Accelerator. In ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED). 2022.
• Cheng Chu, Nai-Hui Chia, Lei Jiang, and Fan Chen. QMLP: An Error-Tolerant Nonlinear Quantum MLP Architecture using Parameterized Two-Qubit Gates. In ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED). 2022.

• Fan Chen. Puffin: an efficient DNN training accelerator for direct feedback alignment in FeFET. In ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED). 2021.

ACM/IEEE Joint Conference on Digital Libraries

• Allen Riddell. Reliable editions from unreliable components: estimating ebooks from print editions using profile hidden markov models. In ACM/IEEE Joint Conference on Digital Libraries, 1–5. 2022.

Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization

• Antonela Tommasel, Juan Manuel Rodriguez, and Filippo Menczer. Following the Trail of Fake News Spreaders in Social Media: A Deep Learning Model. In Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, 29–34. 2022.

Advances in Neural Information Processing Systems (NeurIPS)

• Changlong Wu, Mohsen Heidari, Ananth Grama, and Wojciech Szpankowski. Expected Worst Case Regret via Stochastic Sequential Covering. In Advances in Neural Information Processing Systems (NeurIPS). 2022.

• Man Shun Ang, Jianzhu Ma, Nianjun Liu, Kun Huang, and Yijie Wang. Fast projection onto the capped simplex with applications to sparse regression in bioinformatics. In Advances in Neural Information Processing Systems (NeurIPS). 2021.
• Brandon G. Jacques, Zoran Tiganj, Marc W. Howard, and Per B. Sederberg. DeepSITH: Efficient Learning via Decomposition of What and When Across Time Scales. In Advances in Neural Information Processing Systems (NeurIPS), 27530–27541. 2021.
• Sadamori Kojaku, Jisung Yoon, Isabel Constantino, and Yong-Yeol Ahn. Residual2Vec: Debiasing graph embedding with random graphs. In Advances in Neural Information Processing Systems (NeurIPS), volume 34, 24150–24163. 2021.

• Nikolai Karpov and Qin Zhang. Batched coarse ranking in multi-armed bandits. In Advances in Neural Information Processing Systems (NeurIPS). 2020.

Algebraic Structures and Natural Language

• Lawrence S. Moss. Algebra and Language: Reasons for (Dis)content. In Algebraic Structures and Natural Language, 227–250. 2022.

Annual Conference of the Cognitive Science Society (CogSci)

• Eeshan Hasan and Jennifer Trueblood. Representational Smoothing to Improve Medical Image Decision Making. In Annual Conference of the Cognitive Science Society (CogSci), volume 44. 2022.
• Sahaj Singh Maini, Louis Francis Labuzienski, Saurabh Gulati, and Zoran Tiganj. Comparing Impact of Time Lag and Item Lag in Relative Judgment of Recency. In Annual Conference of the Cognitive Science Society (CogSci), volume 44. 2022.

• Andrei Amatuni, Sara Schroer, Ryan Peters, Md Alimoor Reza, Yayun Zhang, David Crandall, and Chen Yu. In-the-Moment Visual Information Determines Learning. In Annual Conference of the Cognitive Science Society (CogSci). 2021.
• Ryan Peters, Andrei Amatuni, Sara Schroer, Shujon Naha, David Crandall, and Chen Yu. Are you with me? Modeling joint attention from egocentric vision. In Annual Conference of the Cognitive Science Society (CogSci). 2021.
• Zoran Tiganj, Wei Tang, and Marc Howard. A computational model for simulating the future using a memory timeline. In Annual Conference of the Cognitive Science Society (CogSci), volume 43. 2021.
• Samantha MW Wood and Justin N Wood. Distorting Face Representations in Newborn Brains. In Annual Conference of the Cognitive Science Society (CogSci). 2021.
• Yayun Zhang, Andrei Amatuni, Ellis Cain, Xizi Wang, David Crandall, and Chen Yu. Statistical learning of verb meaning. In Annual Conference of the Cognitive Science Society (CogSci). 2021.

• Satoshi Tsutsui, Arjun Chandrasekaran, Md Alimoor Reza, David Crandall, and Chen Yu. A Computational Model of Early Word Learning from the Infant's Point of View. In Annual Conference of the Cognitive Science Society (CogSci). 2020.
• Justin N Wood, Donsuk Lee, Brian Wood, and Samantha MW Wood. Reverse engineering the origins of visual intelligence. In Annual Conference of the Cognitive Science Society (CogSci). 2020.

• Elizabeth M Clerkin and Linda B Smith. The everyday statistics of objects and their names: How word learning gets its start. In Annual Conference of the Cognitive Science Society (CogSci), volume 2019, 240. 2019.

Arabic Natural Language Processing Workshop (WANLP)

• Noor Abo Mokh, Daniel Dakota, and Sandra Kübler. Improving POS Tagging for Arabic Dialects on Out-of-Domain Texts. In Arabic Natural Language Processing Workshop (WANLP). 2022.

British Machine Vision Conference (BMVC)

• Shujon Naha, Md Alimoor Reza, Chen Yu, and David J. Crandall. Localizing novel attended objects in egocentric views. In British Machine Vision Conference (BMVC). 2020.

Computational Theory of Mind for Human-Machine Teams

• Taher Rahgooy, K Brent Venable, and Jennifer S Trueblood. Integrating Machine Learning and Cognitive Modeling of Decision Making. In Computational Theory of Mind for Human-Machine Teams, 173–193. 2023.

Conference on Artificial Life (ALIFE)

• Eduardo J Izquierdo and Madhavun Candadai. What does functional connectivity tell us about the behaviorally-functional connectivity of a multifunctional neural circuit? In Conference on Artificial Life (ALIFE). 2022.
• Eduardo J Izquierdo, Gabriel J Severino, and Haily Merritt. Perpetual Crossers without Sensory Delay: Revisiting the Perceptual Crossing Simulation Studies. In Conference on Artificial Life (ALIFE). 2022.

• Abe Leite and Eduardo J Izquierdo. Generating reward structures on a parameterized distribution of dynamics tasks. In Conference on Artificial Life (ALIFE), number 2021. 2021.

• Randall D Beer. An integrated perspective on the constitutive and interactive dimensions of autonomy. In Conference on Artificial Life (ALIFE), 202–209. 2020.
• Randall D Beer. An investigation into the origin of autopoiesis. In Conference on Artificial Life (ALIFE), volume 26, 5–22. 2020.
• Lauren V Benson, Madhavun Candadai, and Eduardo J Izquierdo. Neural reuse in multifunctional neural networks for control tasks. In Conference on Artificial Life (ALIFE), number 32. 2020.
• Brian A Dahlberg and Eduardo J Izquierdo. Contributions from parallel strategies for spatial orientation in C. elegans. In Conference on Artificial Life (ALIFE), 16–24. 2020.
• Abe Leite, Madhavun Candadai, and Eduardo J Izquierdo. Reinforcement learning beyond the Bellman equation: Exploring critic objectives using evolution. In Conference on Artificial Life (ALIFE), 441–449. 2020.
• Mahi Luthra, Eduardo J Izquierdo, and Peter M Todd. Cognition evolves with the emergence of environmental patchiness. In Conference on Artificial Life (ALIFE). 2020.
• Graham Todd, Madhavun Candadai, and Eduardo J Izquierdo. Interaction between evolution and learning in nk fitness landscapes. In Conference on Artificial Life (ALIFE), 761–767. 2020.

Conference on Empirical Methods in Natural Language Processing (EMNLP)

• Bo Feng, Qian Lou, Lei Jiang, and Geoffrey Fox. CRYPTOGRU: Low Latency Privacy-Preserving Text Model Inference. In Conference on Empirical Methods in Natural Language Processing (EMNLP). 2021.

Conference on Information and Knowledge Management (CIKM)

• Yi Li, Yan Song, and Qin Zhang. Learning to cluster via same-cluster queries. In Conference on Information and Knowledge Management (CIKM), 978–987. 2021.

• Mohsen Sayyadiharikandeh, Onur Varol, Kai-Cheng Yang, Alessandro Flammini, and Filippo Menczer. Detection of novel social bots by ensembles of specialized classifiers. In Conference on Information and Knowledge Management (CIKM), 2725–2732. 2020.

Conference on Recent Advances in NLP (RANLP)

• Almas Abdibayev, Allen Riddell, and Daniel Rockmore. BPoMP: The Benchmark of Poetic Minimal Pairs–Limericks, Rhyme, and Narrative Coherence. In Conference on Recent Advances in NLP (RANLP), 1–9. 2021.
• Keith Carlson, Allen Riddell, and Daniel Rockmore. Unsupervised text style transfer with content embeddings. In Conference on Recent Advances in NLP (RANLP), 226–233. 2021.
• Holly Lopez Long, Alexandra O'Neill, and Sandra Kübler. On the Interaction between Annotation Quality and Classifier Performance in Abusive Language Detection. In Conference on Recent Advances in NLP (RANLP). 2021.
• Allen Riddell and Yohei Igarashi. Varieties of Plain Language. In Conference on Recent Advances in NLP (RANLP), 1180–1187. 2021.
• Allen Riddell, Haining Wang, and Patrick Juola. A call for clarity in contemporary authorship attribution evaluation. In Conference on Recent Advances in NLP (RANLP). 2021.
• He Zhou and Sandra Kübler. Delexicalized Cross-lingual Dependency Parsing for Xibe. In Conference on Recent Advances in NLP (RANLP). 2021.

Design, Automation \& Test in Europe Conference \& Exhibition (DATE)

• Fan Chen, Linghao Song, Hai Li, and Yiran Chen. MARVEL: A Vertical Resistive Accelerator for Low-Power Deep Learning Inference in Monolithic 3D. In Design, Automation & Test in Europe Conference & Exhibition (DATE). 2021.
• Fan Chen, Linghao Song, Hai Li, and Yiran Chen. RAISE: A Resistive Accelerator for Subject-Independent EEG Signal Classification. In Design, Automation & Test in Europe Conference & Exhibition (DATE). 2021.

• Yitu Wang, Fan Chen, Linghao Song, C-J Richard Shi, Hai Helen Li, and Yiran Chen. Reboc: Accelerating block-circulant neural networks in reram. In Design, Automation & Test in Europe Conference & Exhibition (DATE). 2020.

European Chapter of the Association for Computational Linguistics

• Haining Wang, Allen Riddell, and Patrick Juola. Mode effects' challenge to authorship attribution. In European Chapter of the Association for Computational Linguistics, 1146–1155. 2021.

European Conference on Computer Vision (ECCV)

• Mang Ye, Jianbing Shen, David J. Crandall, Ling Shao, and Jiebo Luo. Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification. In European Conference on Computer Vision (ECCV). 2020.

European Conference on IR Research (ECIR)

• Dominic Seyler, Wei Liu, XiaoFeng Wang, and ChengXiang Zhai. Towards dark jargon interpretation in underground forums. In European Conference on IR Research (ECIR), 393–400. 2021.

European Signal Processing Conference (EUSIPCO)

• R David Badger, Kristopher H Jung, and Minje Kim. An Open-Sourced Time-Frequency Domain RF Classification Framework. In European Signal Processing Conference (EUSIPCO), 1701–1705. 2021.
• R David Badger and Minje Kim. Singular Value Decomposition for Compression of Large-Scale Radio Frequency Signals. In European Signal Processing Conference (EUSIPCO), 1591–1595. 2021.

Findings of the Association for Computational Linguistics: ACL-IJCNLP

• Hai Hu, He Zhou, Zuoyu Tian, Yiwen Zhang, Yina Patterson, Yanting Li, Yixin Nie, and Kyle Richardson. Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference. In Findings of the Association for Computational Linguistics: ACL-IJCNLP, 3770–3785. August 2021.

Findings of the Association for Computational Linguistics: EMNLP

• Jisun An, Haewoon Kwak, Claire Seungeun Lee, Bogang Jun, and Yong-Yeol Ahn. Predicting anti-Asian hateful users on Twitter during COVID-19. In Findings of the Association for Computational Linguistics: EMNLP. 2021.

• Hai Hu, Kyle Richardson, Liang Xu, Lu Li, Sandra Kübler, and Lawrence Moss. OCNLI: Original Chinese Natural Language Inference. In Findings of the Association for Computational Linguistics: EMNLP. 2020.

IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

• Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Christian Fuegen, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei Huang, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, and Jitendra Malik. Ego4D: Around the World in 3,000 Hours of Egocentric Video. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2022.

• Norman Su and David J. Crandall. The Affective Growth of Computer Vision. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2021.

• Bardia Doosti, Shujon Naha, Majid Mirbagheri, and David Crandall. HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.
• Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David Crandall, and Steven Hoi. Learning Video Object Segmentation from Unlabeled Videos. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.

IEEE Conference on Robotics and Automation (ICRA)

• Weizhe Chen and Lantao Liu. Informative Planning in the Presence of Outliers. In IEEE Conference on Robotics and Automation (ICRA). 2022.

• Zehua Zhang, Ashish Tawari, Sujitha Martin, and David Crandall. Interaction Graph for Object Importance Estimation in On-road Driving Videos. In IEEE Conference on Robotics and Automation (ICRA). 2020.

IEEE European Symposium on Security and Privacy (EuroS\&P)

• Yunhui Long, Lei Wang, Diyue Bu, Vincent Bindschaedler, Xiaofeng Wang, Haixu Tang, Carl A Gunter, and Kai Chen. A pragmatic approach to membership inferences on machine learning models. In IEEE European Symposium on Security and Privacy (EuroS&P), 521–534. 2020.

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

• Sunwoo Kim and Minje Kim. Bloom-Net: Blockwise Optimization for Masking Networks Toward Scalable and Efficient Speech Enhancement. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 366–370. 2022.
• Darius Petermann and Minje Kim. Spain-Net: Spatially-Informed Stereophonic Music Source Separation. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 106–110. 2022.
• Haici Yang, Sanna Wager, Spencer Russell, Mike Luo, Minje Kim, and Wontak Kim. Upmixing via style transfer: a variational autoencoder for disentangling spatial images and musical content. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 426–430. 2022.
• Hao Zhang, Srivatsan Kandadai, Harsha Rao, Minje Kim, Tarun Pruthi, and Trausti Kristjansson. Deep Adaptive Aec: Hybrid of Deep Learning and Adaptive Acoustic Echo Cancellation. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 756–760. 2022.

• Haici Yang, Kai Zhen, Seungkwon Beack, and Minje Kim. Source-aware neural speech coding for noisy speech compression. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 706–710. 2021.

• Sunwoo Kim, Haici Yang, and Minje Kim. Boosted locality sensitive hashing: Discriminative binary codes for source separation. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 106–110. 2020.
• Sanna Wager, George Tzanetakis, Cheng-i Wang, and Minje Kim. Deep autotuner: A pitch correcting network for singing performances. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 246–250. 2020.
• Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, and Minje Kim. Efficient and scalable neural residual waveform coding with collaborative quantization. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 361–365. 2020.

IEEE International Conference on Cluster Computing (CLUSTER)

• Jinyang Liu, Sheng Di, Kai Zhao, Sian Jin, Dingwen Tao, Xin Liang, Zizhong Chen, and Franck Cappello. Exploring autoencoder-based error-bounded compression for scientific data. In IEEE International Conference on Cluster Computing (CLUSTER). 2021.

IEEE International Conference on Data Mining (ICDM)

• Md Khaledur Rahman, Majedul Haque Sujon, and Ariful Azad. Force2Vec: Parallel force-directed graph embedding. In IEEE International Conference on Data Mining (ICDM), 442–451. 2020.

IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL)

• Satoshi Tsutsui, Xizi Wang, Guangyuan Weng, Yayun Zhang, David Crandall, and Chen Yu. Action Recognition based on Cross-Situational Action-object Statistics. In IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL). 2022.

IEEE International Conference on Intelligent Robots and Systems (IROS)

• Eric Nichols, Sarah Rose Siskind, Levko Ivanchuk, Guillermo Pérez, Waki Kamino, Selma Šabanović, and Randy Gomez. Hey Haru, Let's Be Friends! Using the Tiers of Friendship to Build Rapport through Small Talk with the Tabletop Robot Haru. In IEEE International Conference on Intelligent Robots and Systems (IROS), volume, 6101–6108. 2022.
• Durgakant Pushp, Swapnil Kalhapure, Kaushik Das, and Lantao Liu. UAV-miniUGV Hybrid System for Hidden Area Exploration and Manipulation. In IEEE International Conference on Intelligent Robots and Systems (IROS), 1297–1304. 2022.

• Jagpreet Chawla, Nikhil Shripad Thakurdesai, Anuj Balasaheb Godase, Md Alimoor Reza, David J. Crandall, and Soon-Heung Jung. Error Diagnosis of Deep Monocular Depth Estimation Models. In IEEE International Conference on Intelligent Robots and Systems (IROS). 2021.

IEEE International Conference on Multimedia and Expo (ICME)

• Yuchen Wang, Mingze Xu, John Paden, Lara Koenig, Geoffrey C. Fox, and David J. Crandall. Deep Tiered Image Segmentation for Detecting Internal Ice Layers in Radar Imagery. In IEEE International Conference on Multimedia and Expo (ICME). 2021.

IEEE International Conference on Robot \& Human Interactive Communication (RO-MAN)

• Sawyer Collins and Selma Šabanović. “What Does Your Robot Do?” A Tabletop Role-Playing Game to Support Robot Design. In IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 1097–1102. 2021.

• Heike Brock, Selma Sabanovic, Keisuke Nakamura, and Randy Gomez. Robust real-time hand gestural recognition for non-verbal communication with tabletop robot haru. In IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), 891–898. 2020.

IEEE International Conference on Systems, Man, and Cybernetics (SMC)

• Veda Narayana Koraganji, Aidan J Whelan, Akhil Mokkapati, Juliette N Zerick, R Michael Winters, and Gregory F Lewis. Performance of 1D-CNNs for EEG-Based Mental State Classification: Effects of Domain, Window Size and Electrode Montage. In IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2664–2671. 2021.

IEEE International Parallel and Distributed Processing Symposium (IPDPS)

• Md Khaledur Rahman, Majedul Haque Sujon, and Ariful Azad. Fusedmm: A unified sddmm-spmm kernel for graph embedding and graph neural networks. In IEEE International Parallel and Distributed Processing Symposium (IPDPS), 256–266. 2021.

IEEE International Symposium on High Performance Computer Architecture

• Linghao Song, Fan Chen, Youwei Zhuo, Xuehai Qian, Hai Li, and Yiran Chen. Accpar: Tensor partitioning for heterogeneous deep learning accelerators. In IEEE International Symposium on High Performance Computer Architecture. 2020.

IEEE International Symposium on Information Theory (ISIT)

• Mohsen Heidari, Achilleas Anastasopoulos, and S Sandeep Pradhan. Upper Bounds on the Feedback Error Exponent of Channels With States and With Memory. In IEEE International Symposium on Information Theory (ISIT), 1330–1335. 2022.
• Changlong Wu, Mohsen Heidari, Ananth Grama, and Wojciech Szpankowski. Sequential vs. fixed design regrets in online learning. In IEEE International Symposium on Information Theory (ISIT), 438–443. 2022.

• Mohsen Heidari, Arun Padakandla, and Wojciech Szpankowski. A theoretical framework for learning from quantum data. In IEEE International Symposium on Information Theory (ISIT), 1469–1474. 2021.

IEEE Security and Privacy (Oakland)

• Yi Chen, Yepeng Yao, XiaoFeng Wang, Dandan Xu, Chang Yue, Xiaozhong Liu, Kai Chen, Haixu Tang, and Baoxu Liu. Bookworm game: Automatic discovery of LTE vulnerabilities through documentation analysis. In IEEE Security and Privacy (Oakland), 1197–1214. 2021.

• Rakibul Hasan, David Crandall, Mario Fritz, and Apu Kapadia. Automatically Detecting Bystanders in Photos to Reduce Privacy Risks. In IEEE Security and Privacy (Oakland). 2020.

IEEE Virtual Reality and 3D User Interfaces (VR)

• Seungwon Paik, Youngseung Jeon, Patrick C Shih, and Kyungsik Han. I Feel More Engaged When I Move!: Deep Learning-based Backward Movement Detection and its Application. In IEEE Virtual Reality and 3D User Interfaces (VR). 2021.

IEEE Winter Conference on Applications of Computer Vision (WACV)

• Zhenhua Chen, Chuhua Wang, and David Crandall. Semantically Stealthy Adversarial Attacks against Segmentation Models. In IEEE Winter Conference on Applications of Computer Vision (WACV). 2022.
• Zehua Zhang and David Crandall. Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning. In IEEE Winter Conference on Applications of Computer Vision (WACV). 2022.

• Shujon Naha, Qingyang Xiao, Prianka Banik, Md Alimoor Reza, and David J. Crandall. Part Segmentation of Unseen Objects Using Keypoint Guidance. In IEEE Winter Conference on Applications of Computer Vision (WACV). 2021.
• Satoshi Tsutsui, Yanwei Fu, and David J. Crandall. Whose hand is this? Person Identification from Egocentric Hand Gestures. In IEEE Winter Conference on Applications of Computer Vision (WACV). 2021.
• Tongxin Wang, Zhengming Ding, Wei Shao, Haixu Tang, and Kun Huang. Towards fair cross-domain adaptation via generative learning. In IEEE Winter Conference on Applications of Computer Vision (WACV), 454–463. 2021.

IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

• Sunwoo Kim and Minje Kim. Test-time adaptation toward personalized speech enhancement: Zero-shot learning with knowledge distillation. In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 176–180. 2021.
• Darius Petermann, Seungkwon Beack, and Minje Kim. Harp-net: Hyper-autoencoded reconstruction propagation for scalable neural audio coding. In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 316–320. 2021.
• Aswin Sivaraman and Minje Kim. Zero-Shot Personalized Speech Enhancement Through Speaker-Informed Model Selection. In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 171–175. 2021.

IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH)

• Farzaneh Zokaee, Bing Li, and Fan Chen. FeFET-based Process-in-Memory Architecture for Low-Power DNN Training. In IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH). 2021.

International Conference on Animal-Computer Interaction

• Cassie Kresnye, Sam Rasmussen, Mia Gallardo, and Patrick Shih. Payload Drones and ACI: Drone Navigation System Prototype. In International Conference on Animal-Computer Interaction. 2021.

• K Cassie Kresnye, Christopher Flynn Martin, and Patrick C Shih. Drone Delivery Service: An Orangutan Enrichment Pilot Study. In International Conference on Animal-Computer Interaction. 2020.
• K Cassie Kresnye and Patrick C Shih. Movement Patterns as Enrichment: Exploratory Canine-Drone Interaction Pilot Study. In International Conference on Animal-Computer Interaction. 2020.

International Conference on Artificial Intelligence in Medicine (AIME)

• Tingyi Wanyan, Martin Kang, Marcus A Badgeley, Kipp W Johnson, Jessica K De Freitas, Fayzan F Chaudhry, Akhil Vaid, Shan Zhao, Riccardo Miotto, Girish N Nadkarni, and others. Heterogeneous graph embeddings of electronic health records improve critical care disease predictions. In International Conference on Artificial Intelligence in Medicine (AIME), 14–25. 2020.

International Conference on Case-based Reasoning (ICCBR)

• David Leake, Zachary Wilkerson, and David Crandall. Extracting Case Indices from Convolutional Neural Networks: A Comparative Study. In International Conference on Case-based Reasoning (ICCBR). 2022.

• David Leake and Xiaomeng Ye. Harmonizing Case Retrieval and Adaptation with Alternating Optimization. In International Conference on Case-based Reasoning (ICCBR), 125–139. 2021.
• Zachary Wilkerson, David Leake, and David Crandall. On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval. In International Conference on Case-based Reasoning (ICCBR). 2021.
• Xiaomeng Ye, David Leake, Vahid Jalali, and David Crandall. Learning Adaptations for Case-Based Classification: A Neural Network Approach. In International Conference on Case-based Reasoning (ICCBR). 2021.

• Xiaomeng Ye, David Leake, William Huibregtse, and Mehmet Dalkilic. Applying Class-to-Class Siamese Networks to Explain Classifications with Supportive and Contrastive Cases. In International Conference on Case-based Reasoning (ICCBR). 2020.

International Conference on Computational Creativity (ICCC)

• Xiaomeng Ye, Ziwei Zhao, David Leake, and David Crandall. Generation and Evaluation of Creative Images from Limited Data: A Class-to-Class VAE Approach. In International Conference on Computational Creativity (ICCC). 2022.

International Conference on Computational Linguistics

• Ludovic Mompelat, Daniel Dakota, and Sandra Kübler. How to Parse a Creole: When Martinican Creole meets French. In International Conference on Computational Linguistics, 4397–4406. 2022.

International Conference on Computational Science

• Bruno Magalhães, Michael Hines, Thomas Sterling, and Felix Schürmann. Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks. In International Conference on Computational Science, 94–108. 2020.

International Conference on Field-Programmable Logic and Applications (FPL)

• Chengming Zhang, Tong Geng, Anqi Guo, Jiannan Tian, Martin Herbordt, Ang Li, and Dingwen Tao. H-GCN: A graph convolutional network accelerator on versal acap architecture. In International Conference on Field-Programmable Logic and Applications (FPL). 2022.

International Conference on Information

• Kahyun Choi. Bimodal Music Subject Classification via Context-Dependent Language Models. In International Conference on Information, 68–77. 2021.

International Conference on Language Resources and Evaluation (LREC)

• Zuoyu Tian and Sandra Kübler. Offensive Language Detection Using Brown Clustering. In International Conference on Language Resources and Evaluation (LREC). 2020.

International Conference on Learning Representations (ICLR)

• Yijie Wang, Y. Zhou, and Jianzhu Ma. Learning Sparse Group Models Through Boolean Relaxation. In International Conference on Learning Representations (ICLR). 2023.

• Qian Lou, Yilin Shen, Hongxia Jin, and Lei Jiang. SAFENet: A secure, accurate and fast neural network inference. In International Conference on Learning Representations (ICLR). 2020.

International Conference on Machine Learning (ICML)

• Brandon G. Jacques, Zoran Tiganj, Aakash Sarkar, Marc W. Howard, and Per B. Sederberg. A deep convolutional neural network that is invariant to time rescaling. In International Conference on Machine Learning (ICML), volume 162, 9729–9738. 2022.

• Mohsen Heidari, Jithin Sreedharan, Gil I Shamir, and Wojciech Szpankowski. Finding relevant information via a discrete fourier expansion. In International Conference on Machine Learning (ICML), 4181–4191. 2021.
• Qian Lou and Lei Jiang. Hemet: A homomorphic-encryption-friendly privacy-preserving mobile neural network architecture. In International Conference on Machine Learning (ICML). 2021.

• Kefan Dong, Yingkai Li, Qin Zhang, and Yuan Zhou. Multinomial logit bandit with low switching cost. In International Conference on Machine Learning (ICML), 2607–2615. 2020.

• Chao Tao, Saúl Blanco, and Yuan Zhou. Best arm identification in linear bandits with linear dimension dependency. In International Conference on Machine Learning (ICML). 2018.

International Conference on Parsing Technologies

• Daniel Dakota, Zeeshan Ali Sayyed, and Sandra Kübler. Bidirectional Domain Adaptation Using Weighted Multi-Task Learning. In International Conference on Parsing Technologies. 2021.

International Conference on Social Robotics

• Eric Nichols, Sarah Rose Siskind, Waki Kamino, Selma Šabanović, and Randy Gomez. Iterative Design of an Emotive Voice for the Tabletop Robot Haru. In International Conference on Social Robotics, 362–374. 2021.

• Randy Gomez, Deborah Szapiro, Luis Merino, Heike Brock, Keisuke Nakamura, and Selma Sabanovic. Emoji to robomoji: exploring affective telepresence through haru. In International Conference on Social Robotics, 652–663. 2020.
• Swapna Joshi, Sawyer Collins, Waki Kamino, Randy Gomez, and Selma Šabanović. Social robots for socio-physical distancing. In International Conference on Social Robotics, 440–452. 2020.

International FLAIRS Conference

• Caleb Kisby, Saúl Blanco, and Lawrence Moss. The Logic of Hebbian Learning. In International FLAIRS Conference. 2022.

International Joint Conference on Neural Networks (IJCNN)

• Boli Fang, Zhenghao Peng, Hao Sun, and Q. Zhang. Meta Proximal Policy Optimization for Cooperative Multi-Agent Continuous Control. In International Joint Conference on Neural Networks (IJCNN). 2022.

International Symposium on Artificial Intelligence and Mathematics (ISAIM)

• Matthias Scheutz, Kamal Premaratne, Lawrence S. Moss, and Avery Caulfield. Probabilistic `If-Then' Rules: On Bayesian Conditionals and Probabilistic Implications. In International Symposium on Artificial Intelligence and Mathematics (ISAIM). 2022.

International Symposium on Bioinformatics Research and Applications

• Yuan Xie, Yulong Pei, Yun Lu, Haixu Tang, and Yuan Zhou. Learning Structural Genetic Information via Graph Neural Embedding. In International Symposium on Bioinformatics Research and Applications, 250–261. 2020.

International Workshop on Treebanks and Linguistic Theories (TLT)

• Kenneth Steimel, Akbar Amat, Arienne Dwyer, and Sandra Kübler. Fine-Grained Morpho-Syntactic Analysis for the Under-Resourced Language Chaghatay. In International Workshop on Treebanks and Linguistic Theories (TLT). 2020.

Interspeech

• Aswin Sivaraman, Sunwoo Kim, and Minje Kim. Personalized Speech Enhancement Through Self-Supervised Data Augmentation and Purification. In Interspeech. 2021.

• Aswin Sivaraman and Minje Kim. Sparse Mixture of Local Experts for Efficient Speech Enhancement. In Interspeech. 2020.

Joint Conference on Lexical and Computational Semantics (SEM)

• Zeming Chen, Qiyue Gao, and Lawrence S. Moss. NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning. In Joint Conference on Lexical and Computational Semantics (SEM), 78–88. 2021.

Language Resources and Evaluation Conference

• Haining Wang and Allen Riddell. CCTAA: A Reproducible Corpus for Chinese Authorship Attribution Research. In Language Resources and Evaluation Conference, 5889–5893. 2022.

Meeting of the Society for Computation in Linguistics (SCIL)

• Daniel Dakota and Sandra Kübler. What's in a Span? Evaluating the Creativity of a Span-Based Neural Constituency Parser. In Meeting of the Society for Computation in Linguistics (SCIL). 2021.

• Hai Hu, Qi Chen, Kyle Richardson, Atreyee Mukherjee, Lawrence Moss, and Sandra Kübler. MonaLog: A Lightweight System for Natural Language Inference Based on Monotonicity. In Meeting of the Society for Computation in Linguistics (SCIL). 2020.

Robotics: Science and Systems (RSS)

• Weizhe Chen, Roni Khardon, and Lantao Liu. AK: Attentive Kernel for Information Gathering. In Robotics: Science and Systems (RSS). 2022.
• Zheng Chen, Durgakant Pushp, and Lantao Liu. CALI: Coarse-to-Fine ALIgnments Based Unsupervised Domain Adaptation of Traversability Prediction for Deployable Autonomous Navigation. In Robotics: Science and Systems (RSS). 2022.

SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

• Zuoyu Tian and Sandra Kübler. Period Classification in Chinese Historical Texts. In SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature. 2021.

USENIX Conference on Security Symposium

• Yuxuan Chen, Xuejing Yuan, Jiangshan Zhang, Yue Zhao, Shengzhi Zhang, Kai Chen, and XiaoFeng Wang. Devil's Whisper: A General Approach for Physical Adversarial Attacks against Commercial Black-Box Speech Recognition Devices. In USENIX Conference on Security Symposium, SEC'20. 2020.

Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems (XCBR)

• David Leake. Case-Based Explanation: Making the Implicit Explicit. In Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems (XCBR). 2022.

• Lawrence Gates and David Leake. Evaluating CBR Explanation Capabilities: Survey and Next Steps. In Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems (XCBR), 40–51. 2021.

Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis

• Yue Chen, Yingnan Ju, and Sandra Kübler. IUCL at WASSA 2022 Shared Task: A Text-Only Approach to Empathy and Emotion Detection. In Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 228–232. 2022.

Workshop on Online Abuse and Harms (WOAH)

• Dante Razo and Sandra Kübler. Investigating Sampling Bias in Abusive Language Detection. In Workshop on Online Abuse and Harms (WOAH), 70–78. 2020.

Books

• Christoph Bartneck, Tony Belpaeme, Friederike Eyssel, Takayuki Kanda, Merel Keijsers, and Selma Šabanović. Human-robot interaction: An introduction. Cambridge University Press, 2020.

Journal articles

ACM Transactions on Privacy and Security

• Yuxuan Chen, Jiangshan Zhang, Xuejing Yuan, Shengzhi Zhang, Kai Chen, Xiaofeng Wang, and Shanqing Guo. Sok: A modularized approach to study the security of automatic speech recognition systems. ACM Transactions on Privacy and Security, 25(3):1–31, 2022.

ACS Nano

• Joshua Smith, Md Alimoor Reza, Nathanael Smith, Jianxin Gu, Maha Ibrar, David Crandall, and Sara Skrabalak. Plasmonic Anti-counterfeit Tags with High Encoding Capacity Rapidly Authenticated with Deep Machine Learning. ACS Nano, 2021.

AIDS and Behavior

• Andy Edinger, Danny Valdez, Eric Walsh-Buhi, and Johan Bollen. Deep learning for topical trend discovery in online discourse about Pre-Exposure Prophylaxis (PrEP). AIDS and Behavior, pages 1–11, 2022.

American Journal of Recreation Therapy

• Lori Eldridge, Shinichi Nagata, Jennifer Piatt, Cedomir Stanojevic, Selma Šabanović, Casey Bennett, Natasha Randall, and others. Utilization of socially assistive robots in recreational therapy. American Journal of Recreation Therapy, 19(2):35–45, 2020.

Analytical chemistry

• Kaiyuan Liu, Sujun Li, Lei Wang, Yuzhen Ye, and Haixu Tang. Full-spectrum prediction of peptides tandem mass spectra using deep neural network. Analytical chemistry, 92(6):4275–4283, 2020.

Annual review of biomedical data science

• Rion Brattig Correia, Ian B Wood, Johan Bollen, and Luis M Rocha. Mining social media data for biomedical signals and health-related behavior. Annual review of biomedical data science, 3:433–458, 2020.

Applied Network Science

• John Bollenbacher, Diogo Pacheco, Pik-Mai Hui, Yong-Yeol Ahn, Alessandro Flammini, and Filippo Menczer. On the challenges of predicting microscopic dynamics of online conversations. Applied Network Science, 6:1–21, 2021.

BMC bioinformatics

• Marcin Malec, Hasan Kurban, and Mehmet Dalkilic. CcImpute: An accurate and scalable consensus clustering based algorithm to impute dropout events in the single-cell RNA-seq data. BMC bioinformatics, 23(1):291, 2022.
• Jeremy J Yang, Christopher R Gessner, Joel L Duerksen, Daniel Biber, Jessica L Binder, Murat Ozturk, Brian Foote, Robin McEntire, Kyle Stirling, Ying Ding, and others. Knowledge graph analytics platform with LINCS and IDG for Parkinson's disease target illumination. BMC bioinformatics, 23(1):37, 2022.

Behavior Research Methods

• Calvin Isch, Marijn Ten Thij, Peter M Todd, and Johan Bollen. Quantifying changes in societal optimism from online sentiment. Behavior Research Methods, pages 1–9, 2022.

Behavior research methods

• Charles Maitha, Jesse C Goode, Danielle P Maulucci, Suha MS Lasassmeh, Chen Yu, Linda B Smith, and Jeremy I Borjon. An open-source, wireless vest for measuring autonomic function in infants. Behavior research methods, 52:2324–2337, 2020.

Biological Cybernetics

• Randall D Beer. Codimension-2 parameter space structure of continuous-time recurrent neural networks. Biological Cybernetics, 116(4):501–515, 2022.

Cell Reports

• Youngheun Jo, Farnaz Zamani Esfahlani, Joshua Faskowitz, Evgeny J Chumin, Olaf Sporns, and Richard F Betzel. The diversity and multiplexity of edge communities within and between brain systems. Cell Reports, 37(7):110032, 2021.

Cognition

• Erin M Anderson, Eric S Seemiller, and Linda B Smith. Scene saliencies in egocentric vision and their creation by parents and infants. Cognition, 229:105256, 2022.

• Jennifer S Trueblood, Quentin Eichbaum, Adam C Seegmiller, Charles Stratton, Payton O'Daniels, and William R Holmes. Disentangling prevalence induced biases in medical image decision-making. Cognition, 212:104713, 2021.

• Justin N Wood and Samantha MW Wood. One-shot learning of view-invariant object representations in newborn chicks. Cognition, 2020.

Computational Brain \& Behavior

• William R Holmes, Payton O’Daniels, and Jennifer S Trueblood. A joint deep neural network and evidence accumulation modeling approach to human decision-making with naturalistic images. Computational Brain & Behavior, 3:1–12, 2020.

Computational Linguistics

• Katerina Kalouli, Hai Hu, Alexander Frank Webb, Lawrence S Moss, and Valeria de Paiva. Curing the SICK and Other NLI Maladies. Computational Linguistics, 2023.

Computers in Human Behavior

• Marlena R Fraune, Benjamin C Oisted, Catherine E Sembrowski, Kathryn A Gates, Margaret M Krupp, and Selma Šabanović. Effects of robot-human versus robot-robot behavior and entitativity on anthropomorphism and willingness to interact. Computers in Human Behavior, 105:106220, 2020.

Concurrency and Computation: Practice and Experience

• Vibhatha Abeykoon, Geoffrey Fox, Minje Kim, Saliya Ekanayake, Supun Kamburugamuve, Kannan Govindarajan, Pulasthi Wickramasinghe, Niranda Perera, Chathura Widanage, Ahmet Uyar, and others. Stochastic gradient descent-based support vector machines training optimization on Big Data and HPC frameworks. Concurrency and Computation: Practice and Experience, 34(8):e6292, 2022.

Culturally Sustainable Social Robotics: Proceedings of Robophilosophy

• Selma Šabanović. Designing Companion Artifacts: The Relational Construction of Culture and Technology in Social Robotics. Culturally Sustainable Social Robotics: Proceedings of Robophilosophy, 2021.

Current Biology

• Kathryn Bonnen. Motion vision: Fish swimming to see. Current Biology, 33(1):R30–R32, 2023.

Data Intelligence

• Tingyi Wanyan, Hossein Honarvar, Ariful Azad, Ying Ding, and Benjamin S Glicksberg. Deep learning with heterogeneous graph embeddings for mortality prediction from electronic health records. Data Intelligence, 3(3):329–339, 2021.

Diachronica

• Patrícia Amaral, Hai Hu, and Sandra Kübler. Tracing semantic change with distributional methods: The contexts of textit algo. Diachronica, 2022.

Digital Scholarship in the Humanities

• Hai Hu, Patrícia Amaral, and Sandra Kübler. Word Embeddings and Semantic Shifts in Historical Spanish: Methodological Considerations. Digital Scholarship in the Humanities, 2021.

EPJ data science

• Elise Jing and Yong-Yeol Ahn. Characterizing partisan political narrative frameworks about COVID-19 on Twitter. EPJ data science, 10(1):53, 2021.

Engineering

• Yiran Chen, Yuan Xie, Linghao Song, Fan Chen, and Tianqi Tang. A survey of accelerator architectures for deep neural networks. Engineering, 6(3):264–274, 2020.

Experimental and Applied Acarology

• Oghenekaro Omodior, Mohammad R Saeedpour-Parizi, Md Khaledur Rahman, Ariful Azad, and Keith Clay. Using convolutional neural networks for tick image recognition–a preliminary exploration. Experimental and Applied Acarology, 84:607–622, 2021.

Frontiers in Computational Neuroscience

• Jason A Yoder, Cooper B Anderson, Cehong Wang, and Eduardo J Izquierdo. Reinforcement Learning for Central Pattern Generation in Dynamical Recurrent Neural Networks. Frontiers in Computational Neuroscience, 2022.

• Erick Olivares, Eduardo J Izquierdo, and Randall D Beer. A neuromechanical model of multiple network rhythmic pattern generators for forward locomotion in C. elegans. Frontiers in Computational Neuroscience, 15:572339, 2021.

Frontiers in Robotics and AI

• Natasha Randall, Swapna Joshi, Waki Kamino, Long-Jing Hsu, Abhijeet Agnihotri, Grace Li, Donald Williamson, Kate Tsui, and Selma Šabanović. Finding ikigai: How robots can support meaning in later life. Frontiers in Robotics and AI, 2022.

• Chaolan Lin, Selma Šabanović, Lynn Dombrowski, Andrew D Miller, Erin Brady, and Karl F MacDorman. Parental acceptance of children’s storytelling robots: A projection of the uncanny valley of AI. Frontiers in Robotics and AI, 8:579993, 2021.

Frontiers in Virtual Reality

• Andreas Bueckle, Kilian Buehling, Patrick C Shih, and Katy Börner. Optimizing Performance and Satisfaction in Matching and Movement Tasks in Virtual Reality with Interventions Using the Data Visualization Literacy Framework. Frontiers in Virtual Reality, 2022.

HKS Misinformation Review

• Dimitar Nikolov, Alessandro Flammini, and Filippo Menczer. Right and left, partisanship predicts (asymmetric) vulnerability to misinformation. HKS Misinformation Review, 2020.

IEEE Access

• Md Alimoor Reza, Kai Chen, Akshay Naik, David J. Crandall, and Soon-Heung Jung. Automatic dense annotation for monocular 3d scene understanding. IEEE Access, 8:68852 – 68865, 2020.

IEEE Journal of Selected Topics in Signal Processing

• Aswin Sivaraman and Minje Kim. Efficient personalized speech enhancement through self-supervised learning. IEEE Journal of Selected Topics in Signal Processing, 16(6):1342–1356, 2022.

IEEE Robotics and Automation Letters (RA-L)

• Ihab S Mohamed, Kai Yin, and Lantao Liu. Autonomous Navigation of AGVs in Unknown Cluttered Environments: log-MPPI Control Strategy. IEEE Robotics and Automation Letters (RA-L), 2022.
• Chuhua Wang, Yuchen Wang, Mingze Xu, and David Crandall. Stepwise Goal-Driven Networks for Trajectory Prediction. IEEE Robotics and Automation Letters (RA-L), 2022.

IEEE Signal Processing Letters

• Kai Zhen, Mi Suk Lee, Jongmo Sung, Seungkwon Beack, and Minje Kim. Psychoacoustic calibration of loss functions for efficient end-to-end neural audio coding. IEEE Signal Processing Letters, 27:2159–2163, 2020.

IEEE Systems Journal

• Ying Mao, Yuqi Fu, Wenjia Zheng, Long Cheng, Qingzhi Liu, and Dingwen Tao. Speculative container scheduling for deep learning applications in a kubernetes cluster. IEEE Systems Journal, 2021.

IEEE Transactions on Aerospace and Electronic Systems

• Tingjun Lei, Chaomin Luo, Timothy Sellers, Ying Wang, and Lantao Liu. Multi-task Allocation Framework with Spatial Dislocation Collision Avoidance for Multiple Aerial Robots. IEEE Transactions on Aerospace and Electronic Systems, 2022.

IEEE Transactions on Big Data

• Tingyi Wanyan, Akhil Vaid, Jessica K De Freitas, Sulaiman Somani, Riccardo Miotto, Girish N Nadkarni, Ariful Azad, Ying Ding, and Benjamin S Glicksberg. Relational learning improves prediction of mortality in COVID-19 in the intensive care unit. IEEE Transactions on Big Data, 7(1):38–44, 2020.

IEEE Transactions on Information Theory

• Mohsen Heidari, Jithin K Sreedharan, Gil Shamir, and Wojciech Szpankowski. Sufficiently Informative and Relevant Features: An Information-Theoretic and Fourier-Based Characterization. IEEE Transactions on Information Theory, 68(9):6063–6077, 2022.

IEEE Transactions on Parallel and Distributed Systems (TPDS)

• Haoyu Jin, Donglei Wu, Shuyu Zhang, Xiangyu Zou, Sian Jin, Dingwen Tao, Qing Liao, and Wen Xia. Design of a Quantization-based DNN Delta Compression Framework for Model Snapshots and Federated Learning. IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023.

• Kai Zhao, Sheng Di, Sihuan Li, Xin Liang, Yujia Zhai, Jieyang Chen, Kaiming Ouyang, Franck Cappello, and Zizhong Chen. FT-CNN: Algorithm-based fault tolerance for convolutional neural networks. IEEE Transactions on Parallel and Distributed Systems (TPDS), 32(7):1677–1689, 2020.

IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)

• Tianfei Zhou, Fatih Porikli, David J. Crandall, Luc Van Gool, and Wenguan Wang. A Survey on Deep Learning Techniques for Video Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2023.

• Xiankai Lu, Wenguan Wang, Jianbing Shen, David Crandall, and Jiebo Luo. Zero-Shot Video Object Segmentation with Co-Attention Siamese Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 4(4):2228–2242, April 2022.
• Satoshi Tsutsui, Yanwei Fu, and David J. Crandall. Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022.
• Yu Yao, Xizi Wang, Mingze Xu, Zelin Pu, Yuchen Wang, Ella Atkins, and David J. Crandall. DoTA: Unsupervised Detection of Traffic Anomaly in Driving Videos. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022.
• Junbo Yin, Jianbing Shen, Xin Gao, David Crandall, and Ruigang Yang. Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022.

• Xiankai Lu, Wenguan Wang, Jianbing Shen, David J. Crandall, and Luc Van Gool. Segmenting Objects from Relational Visual Data. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2021.

IEEE/ACM Transactions on Audio, Speech, and Language Processing

• Sunwoo Kim and Minje Kim. Boosted Locality Sensitive Hashing: Discriminative, Efficient, and Scalable Binary Codes for Source Separation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 30:2659–2672, 2022.

• Kai Zhen, Jongmo Sung, Mi Suk Lee, Seungkwon Beack, and Minje Kim. Scalable and efficient neural speech coding: A hybrid design. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 30:12–25, 2021.

Industrial \& Engineering Chemistry Research

• Pranesh Navarathna, Faye Cameron, Mrunal Sontakke, Shu Yang, Travis Diamond, and B Wayne Bequette. Machine-Learning-Based Detection of Pressure-Induced Faults in Continuous Glucose Monitors. Industrial & Engineering Chemistry Research, 2023.

Interaction Studies

• Marlena R Fraune, Selma Šabanović, and Eliot R Smith. Some are more equal than others: Ingroup robots gain some but not all benefits of team membership. Interaction Studies, 21(3):303–328, 2020.

International Journal of Artificial Intelligence in Education

• Anne Ottenbreit-Leftwich, Krista Glazewski, Minji Jeon, Katie Jantaraweragul, Cindy E Hmelo-Silver, Adam Scribner, Seung Lee, Bradford Mott, and James Lester. Lessons Learned for AI Education with Elementary Students and Teachers. International Journal of Artificial Intelligence in Education, pages 1–23, 2022.

International Journal of Research in Marketing

• Keith Carlson, Praveen K Kopalle, Allen Riddell, Daniel Rockmore, and Prasad Vana. Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis. International Journal of Research in Marketing, 2022.

International Journal of Social Robotics

• Natasha Randall, Selma Šabanović, Staša Milojević, and Apurva Gupta. Top of the class: mining product characteristics associated with crowdfunding success and failure of home robots. International Journal of Social Robotics, 14(1):149–163, 2022.

Journal of Computational Biology

• Wontack Han, Haixu Tang, and Yuzhen Ye. Locality-Sensitive Hashing-Based k-Mer Clustering for Identification of Differential Microbial Markers Related to Host Phenotype. Journal of Computational Biology, 2022.

Journal of Computational Literary Studies

• Almas Abdibayev, Yohei Igarashi, Allen Riddell, and Daniel Rockmore. Limericks and Computational Poetics: The Minimal Pairs Framework. Computational Challenges for Poetic Analysis and Synthesis. Journal of Computational Literary Studies, 2022.

Journal of Computational Social Science

• Kai-Cheng Yang, Emilio Ferrara, and Filippo Menczer. Botometer 101: Social bot practicum for computational social scientists. Journal of Computational Social Science, pages 1–18, 2022.

Journal of Energy Storage

• Selcuk Temiz, Hasan Kurban, Salim Erol, and Mehmet M Dalkilic. Regeneration of Lithium-ion battery impedance using a novel machine learning framework and minimal empirical data. Journal of Energy Storage, 2022.

Journal of Experimental Psychology

• Samantha MW Wood and Justin N Wood. One-shot object parsing in newborn chicks.Journal of Experimental Psychology, 2021.

Journal of Hardware and Systems Security

• Md Alimoor Reza, Zhenhua Chen, and David J. Crandall. Deep Neural Network-based Detection and Verification of Microelectronic Images. Journal of Hardware and Systems Security, 4:44–54, 2020.

Journal of Open Source Education

• Bernard t Hart, Titipat Achakulvisut, Ayoade Adeyemi, Athena Akrami, Bradly Alicea, Alicia Alonso-Andres, Diego Alzate-Correa, Arash Ash, Jesus Ballesteros, Aishwarya Balwani, and others. Neuromatch Academy: a 3-week, online summer school in computational neuroscience. Journal of Open Source Education, 5(49):118, 2022.

Journal of Vision

• Can Oluk, Kathryn Bonnen, Johannes Burge, Lawrence K Cormack, and Wilson S Geisler. Stereo slant discrimination of planar 3D surfaces: Frontoparallel versus planar matching. Journal of Vision, 22(5):6–6, 2022.

Knowledge and Information Systems

• Md Khaledur Rahman, Majedul Haque Sujon, and Ariful Azad. Scalable force-directed graph representation learning and visualization. Knowledge and Information Systems, 64(1):207–233, 2022.

Language Acquisition

• Hadar Karmazyn-Raz and Linda B Smith. Discourse with few words: coherence statistics, parent-infant actions on objects, and object names. Language Acquisition, pages 1–19, 2022.

Natural Language Engineering

• Hai Hu and Sandra Kübler. Investigating Translated Chinese and Its Variants Using Machine Learning. Natural Language Engineering, 27(3):271–292, 2020.

Nature Communications

• Farnaz Zamani Esfahlani, Joshua Faskowitz, Jonah Slack, Bratislav Mišić, and Richard F Betzel. Local structure-function relationships in human brain networks across the lifespan. Nature Communications, 13(1):2053, 2022.

• Pisanu Buphamalai, Tomislav Kokotovic, Vanja Nagy, and Jörg Menche. Network analysis reveals rare disease signatures across multiple levels of biological organization. Nature Communications, 12(1):6306, 2021.
• Tongxin Wang, Wei Shao, Zhi Huang, Haixu Tang, Jie Zhang, Zhengming Ding, and Kun Huang. MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification. Nature Communications, 12(1):1–13, 2021.

Nature Human Behaviour

• Saumya Bhadani, Shun Yamaya, Alessandro Flammini, Filippo Menczer, Giovanni Luca Ciampaglia, and Brendan Nyhan. Political audience diversity and news reliability in algorithmic ranking. Nature Human Behaviour, 6(4):495–505, 2022.

Nature Neuroscience

• Kathryn Bonnen, Thaddeus B Czuba, Jake A Whritner, Adam Kohn, Alexander C Huk, and Lawrence K Cormack. Binocular viewing geometry shapes the neural representation of the dynamic three-dimensional environment. Nature Neuroscience, 23(1):113–121, 2020.

NeuroImage

• Maria Grazia Puxeddu, Joshua Faskowitz, Olaf Sporns, Laura Astolfi, and Richard F Betzel. Multi-modal and multi-subject modular organization of human brain networks. NeuroImage, 264:119673, 2022.

Nucleic acids research

• Fatemeh Sharifi and Yuzhen Ye. Identification and classification of reverse transcriptases in bacterial genomes and metagenomes. Nucleic acids research, 50(5):e29–e29, 2022.

PLOS Computational Biology

• Jonathan Samir Matthis, Karl S Muller, Kathryn L Bonnen, and Mary M Hayhoe. Retinal optic flow during natural locomotion. PLOS Computational Biology, 18(2):e1009575, 2022.

PLOS One

• Krishna Bathina, Marijn Ten Thij, and Johan Bollen. Quantifying societal emotional resilience to natural disasters from geo-located social media content. PLOS One, 17(6):e0269315, 2022.

• Krishna C Bathina, Marijn Ten Thij, Danny Valdez, Lauren A Rutter, and Johan Bollen. Declining well-being during the COVID-19 pandemic reveals US social inequities. PLOS One, 16(7):e0254114, 2021.
• Andreas Bueckle, Kilian Buehling, Patrick C Shih, and Katy Börner. 3D virtual reality vs. 2D desktop registration user interface comparison. PLOS One, 2021.

Patterns

• Tingyi Wanyan, Hossein Honarvar, Suraj K Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K De Freitas, Ishan Paranjpe, Akhil Vaid, Jing Zhang, and others. Contrastive learning improves critical event prediction in COVID-19 patients. Patterns, 2(12):100389, 2021.

PeerJ Computer Science

• Haewoon Kwak, Jisun An, Elise Jing, and Yong-Yeol Ahn. FrameAxis: characterizing microframe bias and intensity with word embedding. PeerJ Computer Science, 7:e644, 2021.
• Jisung Yoon, Kai-Cheng Yang, Woo-Sung Jung, and Yong-Yeol Ahn. Persona2vec: a flexible multi-role representations learning framework for graphs. PeerJ Computer Science, 7:e439, 2021.

Personality and Social Psychology Bulletin

• Eliot R Smith, Steven Sherrin, Marlena R Fraune, and Selma Šabanović. Positive emotions, more than anxiety or other negative emotions, predict willingness to interact with robots. Personality and Social Psychology Bulletin, 46(8):1270–1283, 2020.

Philosophical Transactions of the Royal Society B

• Hadar Karmazyn-Raz and Linda B Smith. Sampling statistics are like story creation: a network analysis of parent–toddler exploratory play. Philosophical Transactions of the Royal Society B, 378(1870):20210358, 2023.

Pilot and Feasibility Studies

• Danny Valdez, Kristen N Jozkowski, Katherine Haus, Marijn Ten Thij, Brandon L Crawford, María S Montenegro, Wen-Juo Lo, Ronna C Turner, and Johan Bollen. Assessing rigid modes of thinking in self-declared abortion ideology: natural language processing insights from an online pilot qualitative study on abortion attitudes. Pilot and Feasibility Studies, 8(1):1–14, 2022.

Proceedings of the National Academy of Sciences (PNAS)

• Elizabeth M Clerkin and Linda B Smith. Real-world statistics at two timescales and a mechanism for infant learning of object names. Proceedings of the National Academy of Sciences (PNAS), 119(18):e2123239119, 2022.

• Johan Bollen, Marijn Ten Thij, Fritz Breithaupt, Alexander TJ Barron, Lauren A Rutter, Lorenzo Lorenzo-Luaces, and Marten Scheffer. Historical language records reveal a surge of cognitive distortions in recent decades. Proceedings of the National Academy of Sciences (PNAS), 118(30):e2102061118, 2021.
• Marten Scheffer, Ingrid van de Leemput, Els Weinans, and Johan Bollen. The rise and fall of rationality in language. Proceedings of the National Academy of Sciences (PNAS), 118(51):e2107848118, 2021.
• Chen Yu, Yayun Zhang, Lauren K Slone, and Linda B Smith. The infant’s view redefines the problem of referential uncertainty in early word learning. Proceedings of the National Academy of Sciences (PNAS), 118(52):e2107019118, 2021.

• Ian M Bright, Miriam LR Meister, Nathanael A Cruzado, Zoran Tiganj, Elizabeth A Buffalo, and Marc W Howard. A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex. Proceedings of the National Academy of Sciences (PNAS), 117(33):20274–20283, 2020.

Proceedings of the VLDB Endowment

• Sian Jin, Chengming Zhang, Xintong Jiang, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, and Dingwen Tao. COMET: a novel memory-efficient deep learning training framework by using error-bounded lossy compression. Proceedings of the VLDB Endowment, 2021.

Science Advances

• Hao Peng, Qing Ke, Ceren Budak, Daniel M Romero, and Yong-Yeol Ahn. Neural embeddings of scholarly periodicals reveal complex disciplinary organizations. Science Advances, 7(17):eabb9004, 2021.

Scientific Reports

• Mohammad R Saeedpour-Parizi, Shirin E Hassan, Ariful Azad, Kelly J Baute, Tayebeh Baniasadi, and John B Shea. Target position and avoidance margin effects on path planning in obstacle avoidance. Scientific Reports, 11(1):1–18, 2021.

• Madhavun Candadai and Eduardo J Izquierdo. Sources of predictive information in dynamical neural networks. Scientific Reports, 10(1):1–12, 2020.

Scientific reports

• Kathryn Bonnen, Jonathan S Matthis, Agostino Gibaldi, Martin S Banks, Dennis M Levi, and Mary Hayhoe. Binocular vision and the control of foot placement during walking in natural terrain. Scientific reports, 11(1):20881, 2021.

The Annals of Applied Statistics

• Daniel J McDonald, Michael McBride, Yupeng Gu, and Christopher Raphael. Markov-switching state space models for uncovering musical interpretation. The Annals of Applied Statistics, 15(3):1147–1170, 2021.

Topics in Cognitive Science

• Eeshan Hasan, Quentin Eichbaum, Adam C Seegmiller, Charles Stratton, and Jennifer S Trueblood. Improving Medical Image Decision-Making by Leveraging Metacognitive Processes and Representational Similarity. Topics in Cognitive Science, 14(2):400–413, 2022.

Trends in Cognitive Sciences

• Linda B Smith and Hadar Karmazyn-Raz. Episodes of experience and generative intelligence. Trends in Cognitive Sciences, 2022.

• Tara van Viegen, Athena Akrami, Kathryn Bonnen, Eric DeWitt, Alexandre Hyafil, Helena Ledmyr, Grace W Lindsay, Patrick Mineault, John D Murray, Xaq Pitkow, and others. Neuromatch Academy: Teaching computational neuroscience with global accessibility. Trends in Cognitive Sciences, 25(7):535–538, 2021.