Students will select, read, critically review and present a summary of one of the listed papers for that topic area. The papers were chosen to introduce and highlight the diversity of IST faculty’s recent research interests and methods. Feel free to choose the latest papers from IST faculty that are not listed below.
Overview Paper: Badillo, S., Banfai, B., Birzele, F., Davydov, I. I., Hutchinson, L., Kam‐Thong, T., ... & Zhang, J. D. (2020). An introduction to machine learning. Clinical pharmacology & therapeutics, 107(4), 871-885.
Anderson, A., Dodge, J., Sadarangani, A., Juozapaitis, Z., Newman, E., Irvine, J., ... & Burnett, M. (2020). Mental models of mere mortals with explanations of reinforcement learning. ACM Transactions on Interactive Intelligent Systems (TiiS), 10(2), 1-37.
Bannihatti Kumar, V., Iyengar, R., Nisal, N., Feng, Y., Habib, H., Story, P., ... & Sadeh, N. (2020, April). Finding a choice in a haystack: Automatic extraction of opt-out statements from privacy policy text. In Proceedings of The Web Conference 2020 (pp. 1943-1954).
Bui, N., Yen, J., & Honavar, V. (2016). Temporal causality analysis of sentiment change in a cancer survivor network. IEEE transactions on computational social systems, 3(2), 75-87.
Chen, Y., Zhang, Z., Wu, C., Davaasuren, D., Goldstein, J. A., Gernand, A. D., & Wang, J. Z. (2020). AI-PLAX: AI-based placental assessment and examination using photos. Computerized Medical Imaging and Graphics, 84, 101744.
Dodge, J., Anderson, A. A., Olson, M., Dikkala, R., & Burnett, M. (2022, March). How Do People Rank Multiple Mutant Agents? In 27th International Conference on Intelligent User Interfaces (pp. 191-211).
Dou, Z. Y., Barman-Adhikari, A., Fang, F., & Yadav, A. (2021, May). Harnessing Social Media to Identify Homeless Youth At-Risk of Substance Use. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 17, pp. 14748-14756).
Gopinath, A. A. M., Wilson, S., & Sadeh, N. (2018). Supervised and unsupervised methods for robust separation of section titles and prose text in web documents. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (pp. 850-855).
Hartt, M., Hosseini, H., & Mostafapour, M. (2020). Game on: Exploring the effectiveness of game-based learning. Planning Practice & Research, 35(5), 589-604.
Hsieh, T. Y., Wang, S., Sun, Y., & Honavar, V. (2021, March). Explainable multivariate time series classification: a deep neural network which learns to attend to important variables as well as time intervals. In Proceedings of the 14th ACM international conference on web search and data mining (pp. 607-615).
Hu, Y., Cheng, X., Wang, S., Chen, J., Zhao, T., & Dai, E. (2022). Times series forecasting for urban building energy consumption based on graph convolutional network. Applied Energy, 307, 118231.
Kandimalla, B., Rohatgi, S., Wu, J., & Giles, C. L. (2021). Large scale subject category classification of scholarly papers with deep attentive neural networks. Frontiers in research metrics and analytics, 5, 600382.
Liu, H., Mu, T. J., & Huang, X. (2021). Detecting human—object interaction with multi-level pairwise feature network. Computational Visual Media, 7(2), 229-239.
Silverman, J. D., Bloom, R. J., Jiang, S., Durand, H. K., Dallow, E., Mukherjee, S., & David, L. A. (2021). Measuring and mitigating PCR bias in microbiota datasets. PLoS computational biology, 17(7), e1009113.
Tang, X., Liu, Y., Shah, N., Shi, X., Mitra, P., & Wang, S. (2020, August). Knowing your fate: Friendship, action and temporal explanations for user engagement prediction on social apps. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 2269-2279).
Wilbur, M., Mukhopadhyay, A., Vazirizade, S., Pugliese, P., Laszka, A., & Dubey, A. (2021, September). Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-Task and Inductive Transfer Learning. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 502-517). Springer, Cham.
Wu, Q., Li, Z., Wang, H., Chen, W., & Wang, H. (2019, July). Factorization bandits for online influence maximization. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 636-646).
Xu, D., Cheng, W., Luo, D., Liu, X., & Zhang, X. (2019, August). Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs. In IJCAI (pp. 3947-3953).
Ye, M., Cui, S., Wang, Y., Luo, J., Xiao, C., & Ma, F. (2021, April). Medpath: Augmenting health risk prediction via medical knowledge paths. In Proceedings of the Web Conference 2021 (pp. 1397-1409).
Lee, J., Le, T., Chen, J., & Lee, D. (2023). Do Language Models Plagiarize? The ACM Web Conference (WWW), Austin, TX, April 2023
Fukami, K., Maulik, R., Ramachandra, N., Fukagata, K., & Taira, K. (2021). Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning, Nature Machine Intelligence, 3 (11), 945-951
Gui, H., Jia, F., Chen, J., Squicciarini, A., Yadav, A. (2023). RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model, ACM CIKM
Xing, E., Venkatraman, S., Le, T., & Lee, D. (2024). ALISON: Fast and effective stylometric authorship obfuscation. In Proceedings of the AAAI Conference on Artificial Intelligence, 38(17), 19315–19322. https://doi.org/10.1609/aaai.v38i17.29901
Zhang, X., Lee, D., Wang, S. (2025). Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector. In: Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T., Varol, G. (eds) Computer Vision – ECCV 2024. ECCV 2024. Lecture Notes in Computer Science, vol 15139. Springer, Cham. https://doi.org/10.1007/978-3-031-73004-7_12
Rauer, E., Basu, S., & Honavar, V. (2025). Checking consistency of CP-theory preferences in polynomial time. In Proceedings of the AAAI Conference on Artificial Intelligence, 39(14), 15126–15133. https://doi.org/10.1609/aaai.v39i14.33659
Ashtekar, N., Zhu, J., & Honavar, V. G. (2025). Class Incremental Learning from First Principles: A Review. Transactions on Machine Learning Research, 2025.
Liu, H., Li, C., Zhang, X., Zhang, F., Ma, F., Wang, W., & Yu, H. (2025). AdaDHP: Fine-grained fine-tuning via dual Hadamard product and adaptive parameter selection. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Vol. 1: Long Papers) (pp. 9492–9504). https://doi.org/10.18653/v1/2025.acl-long.467
Chang, Y., Cao, B., Wang, Y., Chen, J., & Lin, L. (2025). JoPA: Explaining large language model's generation via joint prompt attribution. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Vol. 1: Long Papers) (pp. 22106–22122). https://doi.org/10.18653/v1/2025.acl-long.1074
Zeng, Y., Cao, Y., Cao, B., Chang, Y., Chen, J., & Lin, L. (2025). AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion Models. Proceedings of Machine Learning Research, 267, 74037-74050.
Wang, F., Zhang, Z., Zhang, X., Wu, Z., Mo, T. H., Lu, Q., Wang, W., Li, R., Xu, J., Tang, X., He, Q., Ma, Y., Huang, M., & Wang, S. (2025). A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness. ACM Transactions on Intelligent Systems and Technology, 16(6), Article 145. https://doi.org/10.1145/3768165
Hosseini, H., Narang, S., & Wąs, T. (2025). Fair distribution of delivery orders. Artificial Intelligence, 347, 104389. https://doi.org/10.1016/j.artint.2025.104389
Chang, A., Wang, T., & Ma, F. (2026). Enhancing medical large vision-language models via alignment distillation. In Proceedings of the AAAI Conference on Artificial Intelligence, 40(24), 19952–19960. https://doi.org/10.1609/aaai.v40i24.39079
Overview Paper: Olson, G. M., & Olson, J. S. (2003). Psychological aspects of the human use of computing. Annual. Review of Psychology, 54, 491-516.
Abdullah, S., Murnane, E. L., Matthews, M., & Choudhury, T. (2017). Circadian computing: sensing, modeling, and maintaining biological rhythms. In Mobile health (pp. 35-58). Springer, Cham.
Bardzell, J., Bardzell, S., & Light, A. (2021, May). Wanting To Live Here: Design After Anthropocentric Functionalism. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1- 24).
Belavkin, R. V., Ritter, F. E., & Elliman, D. G. (2020, December). Towards including simple emotions in a cognitive architecture in order to better fit children’s behavior. In Proceedings of the Twenty First Annual Conference of the Cognitive Science Society (pp. 784-784). Psychology Press.
Billah, S. M., Ashok, V., Porter, D. E., & Ramakrishnan, I. V. (2018, April). SteeringWheel: a locality-preserving magnification interface for low vision web browsing. In Proceedings of the 2018 CHI conference on human factors in computing systems (pp. 1-13).
Gross, S., Bardzell, J., Bardzell, S., & Stallings, M. (2017). Persuasive anxiety: designing and deploying material and formal explorations of personal tracking devices. Human–Computer Interaction, 32(5-6), 297-334.
Gui, X., & Chen, Y. (2019, May). Making healthcare infrastructure work: Unpacking the infrastructuring work of individuals. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-14).
Gupta, S., Jablonski, J., Tsai, C. H., & Carroll, J. M. (2022). Instagram of Rivers: Facilitating Distributed Collaboration in Hyperlocal Citizen Science. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1), 1-22.
Huang, C. Y., Huang, S. H., & Huang, T. H. K. (2020, April). Heteroglossia: In-situ story ideation with the crowd. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-12).
Huang, T. H., Chang, J. C., & Bigham, J. P. (2018, April). Evorus: A crowd-powered conversational assistant built to automate itself over time. In Proceedings of the 2018 CHI conference on human factors in computing systems (pp. 1-13).
Kou, Y., & Gui, X. (2020). Emotion regulation in eSports gaming: a qualitative study of league of legends. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW2), 1-25.
Lee, S., Reddie, M., Tsai, C. H., Beck, J., Rosson, M. B., & Carroll, J. M. (2020, April). The emerging professional practice of remote sighted assistance for people with visual impairments. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-12).
Sun, F., & Cai, G. (2017, June). Community issue review: crystallizing knowledge for encouraging civic engagement. In Proceedings of the 18th Annual International Conference on Digital Government Research (pp. 260-269).
Wu, H., Wang, Y., Liu, J., Qiu, J., & Zhang, X. L. (2020). User-defined gesture interaction for in-vehicle information systems. Multimedia Tools and Applications, 79(1), 263-288.
Uchendu, A., Lee, J., Shen, H., Le, T., Huang, T.-H., & Lee, D. (2023). Does Human Collaboration Enhance the Accuracy of Identifying Deepfake Texts? 11th AAAI Conf. on Human Computation and Crowdsourcing (HCOMP), Delft, Netherlands, November 2023
Lin, C. & Silvia L. (2021). Techniques of Use: Confronting value systems of productivity, progress, and usefulness in computing and design. In Proceedings of the ACM Human Factors in Computing Systems Conference (CHI '21).
Yeh, M.-H., Wan, R., & Huang, T.-H. K. (2024). CoCoLoFa: A dataset of news comments with common logical fallacies written by LLM-assisted crowds. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (pp. 660–677). https://doi.org/10.18653/v1/2024.emnlp-main.39
Kou, Y., Zhou, Y., Zhang, Z., & Gui, X. (2024). The ecology of harmful design: Risk and safety of game making on a metaverse platform. In Designing Interactive Systems Conference (DIS '24). https://doi.org/10.1145/3643834.3660678
Hernandez, R. H., Song, Q., Kou, Y., & Gui, X. (2024). "At the end of the day, I am accountable": Gig workers' self-tracking for multi-dimensional accountability management. In Proceedings of the CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3613904.3642151
Xie, J., Yu, R., Zhang, H., Billah, S. M., Lee, S., & Carroll, J. M. (2025). Beyond visual perception: Insights from smartphone interaction of visually impaired users with large multimodal models. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3706598.3714210
Kou, Y., Hernandez, R. H., & Gui, X. (2025). "The system is made to inherently push child gambling in my opinion": Child safety, monetization, and moderation on Roblox. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3706598.3713170
Tang, Z., Huang, C.-Y., Li, T.-C., Ng, H. Y. S., Huang, H.-H., & Huang, T.-H. K. (2025). Using contextually aligned online reviews to measure LLMs' performance disparities across language varieties. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the ACL: Human Language Technologies (Vol. 2: Short Papers) (pp. 342–355). https://doi.org/10.18653/v1/2025.naacl-short.29
Luo, Y., Gui, X., Ding, X., Zheng, X., Hernandez, R. H., Li, Z., & Song, Q. (2025). Reflecting upon the unintended consequences of personal informatics systems: A systematic review of empirical studies. In Proceedings of the 2025 ACM Designing Interactive Systems Conference. https://doi.org/10.1145/3715336.3735746
Ng, H. Y., Hsu, T. Y., Ramakrishnan, A. A., Kveton, B., Lipka, N., Dernoncourt, F., Lee, D., Yu, T., Kim, S., Rossi, R. A., & Huang, T. H. (2025). LAMP-CAP: Personalized Figure Caption Generation With Multimodal Figure Profiles. In C. Christodoulopoulos, T. Chakraborty, C. Rose, & V. Peng (Eds.), EMNLP 2025 - 2025 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2025 (pp. 9818-9832). (EMNLP 2025 - 2025 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2025). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2025.findings-emnlp.521
Kabir, I., Redmon, S. A., Elko, L. R., Williams, K., Case, M. A., Sowers, D. J., Wilkinson, K., & Billah, S. M. (2026). Giving meaning to movements: Challenges and opportunities in expanding communication by pairing unaided AAC with speech generated messages. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3772318.3791273
Ehtesham-Ul-Haque, M., & Billah, S. M. (2026). VoiceAlign: A shimming layer for enhancing the usability of legacy voice user interface systems. In Proceedings of the 31st International Conference on Intelligent User Interfaces (pp. 1704–1721). https://doi.org/10.1145/3742413.3789167
Li, Y., Saragih, I. D., Fick, D. M., Sundar, S. S., & Abdullah, S. (2026). A real-time voice agent for delivering individual cognitive stimulation therapy to persons living with dementia. In Proceedings of the 8th ACM Conference on Conversational User Interfaces. https://doi.org/10.1145/3816046.3816286
Overview Paper: Chanal, P. M., & Kakkasageri, M. S. (2020). Security and privacy in IOT: a survey. Wireless Personal Communications, 115(2), 1667-1693.
Chen, J., & Gu, Q. (2020, August). Rays: A ray searching method for hard-label adversarial attack. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 1739-1747).
Kim, T., Ding, A., Etigowni, S., Sun, P., Chen, J., Garcia, L., Zonouz, S., Xu, D., & Tian, D. (2022). Reverse Engineering and Retrofitting Robotic Aerial Vehicle Control Firmware using DisPatch, In Proceedings of the 20th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys), Portland, OR
Kim, T., Kumar, V., Rhee, J., Chen, J., Kim, K., Hwan, Kim, C., Xu, D.,& Tian, D. (2021). PASAN: Detecting Peripheral Access Concurrency Bugs within Bare-metal Embedded Applications, In Proceedings of the 30th USENIX Security Symposium (USENIX Security), Vancouver, BC, August 2021
Ye, H., Liu, S., Zhang, Z., & Hu, H. (2023). VIPER: Spotting Syscall-Guard Variables for Data-Only Attacks, In Proceedings of the 32nd USENIX Security Symposium (USENIX 2023).
Liang, Y., Liu, S., & Hu, H. (2022). Detecting Logical Bugs of DBMS with Coverage-based Guidance, In Proceedings of the 31st USENIX Security Symposium (USENIX 2022).
He, X., Yang, Y., Zhou, W., Wang, W., Liu, P., & Zhang, Y. (2021). Fingerprinting Mainstream IoT Platforms Using Traffic Analysis. IEEE Internet of Things Journal, 9(3), 2083-2093.
Zhang, L., Lian, K., Xiao, H., Zhang, Z., Liu, P., Zhang, Y., ... & Duan, H. (2022, May). Exploit the Last Straw That Breaks Android Systems. In 2022 IEEE Symposium on Security and Privacy (SP) (pp. 2230-2247). IEEE.
Le, T., Wang, S., & Lee, D. (2020, November). MALCOM: Generating malicious comments to attack neural fake news detection models. In 2020 IEEE International Conference on Data Mining (ICDM) (pp. 282-291).
Le, T., Tran-Thanh, L., & Lee, D. (2022). Socialbots on Fire: Modeling Adversarial Behaviors of Socialbots via Multi-Agent Hierarchical Reinforcement Learning. In Proceedings of the ACM Web Conference (WWW) (pp. 545-554).
Zhang, Z., Zhu, S., Mink, J., Xiong, A., Song, L., & Wang, G. (2022). Beyond Bot Detection: Combating Fradulent Online Survey Takers. In Proceedings of the ACM Web Conference (WWW).
Liu, Z., Zhu, S., Qin, B., Chen, H., & Song, L. (2021, April). Automatically detecting and fixing concurrency bugs in go software systems. In Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (pp. 616-629).
Zhu, S., Zhang, Z., Qin, B., Xiong, A., Song, L. (2022). Learning and Programming Challenges of Rust: A Mixed-Methods Study, In Proceedings of IEEE/ACM 44th International Conference on Software Engineering (ICSE).
Serra, E., Shrestha, A., Spezzano, F., & Squicciarini, A. (2020, March). DeepTrust: An automatic framework to detect trustworthy users in opinion-based systems. In Proceedings of the Tenth ACM Conference on Data and Application Security and Privacy (pp. 29-38).
Karimi, Y., Squicciarini, A., & Wilson, S. (2022). Automated detection of doxing on twitter, In Proceedings of the ACM on Human-Computer Interaction 6 (CSCW), 1-24
Wang, X., Wu, M., & Rajtmajer, S. (2023). From Yellow Peril to Model Minority: Asian stereotypes in social media during the COVID-19 pandemic. In Proceedings of ACM Conference on Web Science (WebSci), April 2023
Umar, P., Squicciarini, A., & Rajtmajer. S. (2019). Detection and Analysis of Self-Disclosure in Online News Commentaries. In Proceedings of The Web Conference (WWW), May 2019.
Merhi, M., Rajtmajer, S., & Lee, D. (2023). Information Operations in Turkey: Manufacturing Resilience with Free Twitter Accounts,17th Int'l AAAI Conf. on Web and Social Media (ICWSM), Limassol, Cyprus, June 2023
Cai, Z. & Xiong, A. (2023). Understanding users' privacy perception and decision of V2X communication in Connected Autonomous Vehicles, In Proceedings of the 32nd USENIX Security Symposium (USENIX Security).
Seo, H., Xiong, A., Lee, S., & Lee, D. (2022). If you have a reliable source, say something: Effect of correction comments on COVID-19 misinformation. In Proceedings of the AAAI Conference on Web and Social Media (ICWSM).
Zhang, H., Chen, J., Lin, L., Jia, J., & Wu, D. (2023). Graph Contrastive Backdoor Attacks, In Proceedings of the 40 th International Conference on Machine Learning (ICML), Honolulu, Hawaii, USA.
Li, X., Chen, L., & Wu, D. (2021). Turning Attacks into Protection: Social Media Privacy Protection Using Adversarial Attacks, In Proceedings of the SIAM International Conference on Data Mining (SDM)
Kumar, P., Subramaniam, M., Vitak, J., Clegg, T., & Chetty, M. (2020). Strengthening children’s privacy literacy through contextual integrity, Media and Communication 8 (4), 175-184
Seo, H., Lee, S., Lee, D., & Xiong, A. (2024). Reliability Matters: Exploring the Effect of AI Explanations on Misinformation Detection with a Warning. Proceedings of the International AAAI Conference on Web and Social Media, 18(1), 1395–1407. https://doi.org/10.1609/icwsm.v18i1.31397
Du, T., Kim, J., Squicciarini, A., & Rajtmajer, S. (2024). Toward Context-Aware Privacy Enhancing Technologies for Online Self-Disclosure. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 12(1), 44–54. https://doi.org/10.1609/hcomp.v12i1.31599
Ye, H., & Hu, H. (2025). Too Subtle to Notice: Investigating Executable Stack Issues in Linux Systems. https://doi.org/10.14722/ndss.2025.230924
Jia, F., Wu, T., Qin, X., & Squicciarini, A. (2025). The task shield: Enforcing task alignment to defend against indirect prompt injection in LLM agents. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Vol. 1: Long Papers) (pp. 29680–29697). https://doi.org/10.18653/v1/2025.acl-long.1435
Song, Q., Zhang, Z., Hernandez, R. H. L., Gui, X., & Kou, Y. (2025). How predatory monetization designs manifest in {Child-Friendly} video games. In Twenty-First Symposium on Usable Privacy and Security (SOUPS 2025) (pp. 515-534).
Wang, Z., Cao, C., Yu, L., Wang, S., Sun, X., & Liu, P. (2026). DeepSanitizer: Combining heuristic rules and deep learning models to spot silent buffer overflows in binary. IEEE Transactions on Dependable and Secure Computing, 23(2), 2320–2335. https://doi.org/10.1109/TDSC.2025.3626483
Song, Q., Wu, Y., Hernandez, R. H., Li, Y., Kou, Y., & Gui, X. (2026, May). Usable Anonymity in Reproductive Health Privacy. In 2026 IEEE Symposium on Security and Privacy (SP) (pp. 3627-3646). IEEE.
Yang, Y., Liu, Q., Brix, C., Zhang, H., & Cao, Y. (2025). {CertPHash}: Towards Certified Perceptual Hashing via Robust Training. In 34th USENIX Security Symposium (USENIX Security 25) (pp. 7839-7856).
Li, X., Yang, Y., Deng, J., Yan, C., Chen, Y., Ji, X., & Xu, W. (2024, December). Safegen: Mitigating sexually explicit content generation in text-to-image models. In Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security (pp. 4807-4821).
Min, R., Pang, T., Du, C., Liu, Q., Cheng, M. & Lin, M.. (2025). Improving Your Model Ranking on Chatbot Arena by Vote Rigging. Proceedings of the 42nd International Conference on Machine Learning, in Proceedings of Machine Learning Research 267:44252-44271 Available from https://proceedings.mlr.press/v267/min25a.html.
Qi, Q., Chen, H., Cheng, M., & Liu, H. (2025). Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks. In KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 1138-1149). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. 1). Association for Computing Machinery. https://doi.org/10.1145/3690624.3709316
Yu, Y., Sharma, T., Hu, M., Wang, J., & Wang, Y. (2025). Exploring Parent-Child Perceptions on Safety in Generative AI: Concerns, Mitigation Strategies, and Design Implications. In M. Blanton, W. Enck, & C. Nita-Rotaru (Eds.), Proceedings - 46th IEEE Symposium on Security and Privacy, SP 2025 (pp. 2735-2752). (Proceedings - IEEE Symposium on Security and Privacy). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SP61157.2025.00090
Sharma, T., Tseng, Y.-Y., Zhang, L., Ide, A., Mack, K. A., Findlater, L., Gurari, D., & Wang, Y. (2025). “Before, I asked my mom, now I ask ChatGPT”: Visual privacy management with generative AI for blind and low-vision people. In Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’25) (Article 17, pp. 1–14). Association for Computing Machinery. https://doi.org/10.1145/3663547.3746335
Overview Paper: Smutny, Z., & Vehovar, V. (2020). Social informatics research: Schools of thought, methodological basis, and thematic conceptualization. Journal of the Association for Information Science and Technology, 71(5), 529-539
Coche, J., Kropczynski, J., Montarnal, A., Tapia, A., & Benaben, F. (2021, May). Actionability in a Situation Awareness world: Implications for social media processing system design. In ISCRAM 2021-18th International conference on Information Systems for Crisis Response and Management (No. 2391, pp. p-994).
Cotter, K. (2022). Practical knowledge of algorithms: The case of BreadTube. New Media & Society, 14614448221081802.
Cotter, K., Medeiros, M., Pak, C., & Thorson, K. (2021). “Reach the right people”: The politics of “interests” in Facebook’s classification system for ad targeting. Big Data & Society, 8(1), 2053951721996046.
Fonseca, F. (2007). The double role of ontologies in information science research. Journal of the American Society for Information Science and Technology, 58(6), 786-793.
Grace, R., Halse, S., Aurite, W., Montarnal, A., & Tapia, A. (2019, January). Expanding awareness: Comparing location, keyword, and network filtering methods to collect hyperlocal social media data. In Proceedings of the 52nd Hawaii International Conference on System Sciences.
Hanrahan, B. V., Maitland, C., Brown, T., Chen, A., Kagame, F., & Birir, B. (2021). Agency and Extraction in Emerging Industrial Drone Applications: Imaginaries of Rwandan Farm Workers and Community Members. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), 1-21.
Maitland, C. (2019). Collective behaviors in mobile internet access: an exchange-based approach. Information Technologies & International Development, 15, 18.
Payton, F. C., Yarger, L. K., & Pinter, A. T. (2018). Text mining mental health reports for issues impacting today’s college students: qualitative study. JMIR mental health, 5(4), e10032.
Susser, D., & Grimaldi, V. (2021, July). Measuring Automated Influence: Between Empirical Evidence and Ethical Values. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (pp. 242-253).
Yarger, L., Payton, F. C., & Neupane, B. (2019). Algorithmic equity in the hiring of underrepresented IT job candidates. Online information review.
Zimmer, M., Kumar, P., Vitak, J., Liao, Y., & Chamberlain Kritikos, K. (2020). ‘There’s nothing really they can do with this information’: unpacking how users manage privacy boundaries for personal fitness information. Information, Communication & Society, 23(7), 1020-1037.
Lin, C., Lindtner, S., & Wuschitz, S. (2019) Hacking Difference in Indonesia: The Ambivalences of Designing for Alternative Futures. In Proceedings of the 2019 on Designing Interactive Systems Conference (DIS '19). ACM, 1571-1582.
Cotter, K., Ritchart, A., De, A., Foyle, K., Kanthawala, S., McAtee, H., & Watson, T. (2024). If you’re reading this, it’s meant for you: The reflexive ambivalence of algorithmic conspirituality. Convergence: The International Journal of Research into New Media Technologies, 30(6), 1893-1918.
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