Graduate Research
The Department of Computer Science is passionate about involving students at every level in its research. We are proud to say that we have many graduate students who do research with our faculty members. The department would be pleased to add additional papers and presentations to this list, regardless of the year. Please send us the citation for your paper/presentation using this link. It will then be added to this website.
Below are papers and presentations made by graduate students this past academic year.
AY 2023-2024
Kapil Devkota, PhD (E23), presented "Fast approximate isorank for scalable global alignment of biological networks," co-authored by Professor Anselm Blumer, Professor Xiaozhe Hu, and Professor Lenore Cowen at International Conference on Research in Computational Molecular Biology (RECOMB), May 2024; published in International Conference on Research in Computational Molecular Biology (pp. 1-16). Cham: Springer Nature Switzerland.
Shivam Goel, PhD candidate, presented “NovelGym: A Flexible Ecosystem for Hybrid Planning and Learning Agents Designed for Open Worlds,” co-authored by Yichen Wei, Panagiotis Lymperopoulos, Klara Chura, Professor Matthias Scheutz, and Professor Jivko Sinapov at the 23rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-2024). https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p688.pdf
Ethan Harvey, PhD candidate, presented “A Probabilistic Method to Predict Classifier Accuracy on Larger Datasets given Small Pilot Data,” co-authored by Wansu Chen, David M. Kent, and Professor Michael C. Hughes in Machine Learning for Health (ML4H), December 2023. https://proceedings.mlr.press/v225/harvey23a/harvey23a.pdf
Jindan Huang, PhD candidate, presented “Modeling Variation in Human Feedback with User Inputs: An Exploratory Methodology,” co-authored by Reuben M. Aronson, and Professor Elaine Schaertl Short at the 2024 ACM/IEEE International Conference on Human-Robot Interaction, March 2024. https://dl.acm.org/doi/10.1145/3610977.3634925
Zhe Huang, PhD candidate, presented “Systematic Comparison of Semi-Supervised and Self-Supervised Learning for Medical Image Classification,” co-authored by Ruijie Jiang, Professor Shuchin Aeron, and Professor Michael Hughes at the IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), June 2024.
Darby Huye, PhD candidate, presented “Systemizing and mitigating topological inconsistencies in Alibaba’s microservice call-graph datasets,” co-authored by Lan Liu, and Professor Raja R. Sambasivan at the ACM/SPEC International Conference on Performance Engineering, May 2024; published in Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering (ICPE '24). Association for Computing Machinery, New York, NY, USA, 276–285. https://doi.org/10.1145/3629526.3645043
Samantha Katcher, PhD candidate, presented “Should I Even Be Here?" Perceptions and Experiences of Safety and Belonging in the Cybersecurity Community” at Annual Boston Security Usability Research Day (ABSURD) April 2024.
Nicholas Rabb, PhD candidate, presented “A Tale of Two Cities: Information Diffusion During Environmental Crises in Flint, Michigan and East Palestine, Ohio”, co-authored by Catherine Knox at 12th International Conference on Complex Networks and Their Applications, November 2023.
Polina Shpilker, PhD candidate, co-authored “Context-Sensitive Editing for the MEDFORD Metadata Language” with Liam Strand (primary), Andrew Powers, Professor Lenore Cowen, Professor Alva Couch, and Professor Noah Daniels at the 17th International Conference on Metadata and Semantics Research (MTSR) October 2023.
Christopher Thierauf, PhD candidate candidate presented “Automating Dataset Production Using Generative Text and Image Models,” co-authored by Mitchell Abrams and Professor Matthias Scheutz at the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), May 2024; published in Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 1988-1995)
Hang Yu, PhD candidate, presented “From "Thumbs Up" to "10 out of 10": Reconsidering Scalar Feedback in Interactive Reinforcement Learning,” co-authored by Reuben M. Aronson, Katherine H. Allen, and Professor Elaine Schaertl Short at the International Conference on Intelligent Robots and Systems (IROS), October 2023. https://ieeexplore.ieee.org/document/10342458.
Other publications
Ayca Aygun, PhD candidate published “Assessment of Multiple Systemic Human Cognitive States using Pupillometry,” co-authored by Thuan Nguyen and Professor Matthias Scheutz in Proceedings of the Annual Meeting of the Cognitive Science Society, 46, 2024. https://escholarship.org/uc/item/0954476j
Kapil Devkota, PhD (E23) was the co-first author for the journal publication "TT3D: Leveraging precomputed protein 3D sequence models to predict protein–protein interactions," co-authored by Samuel Sledzieski (co-first author), Rohit Singh, Professor Lenore Cowen, and Professor Bonnie Berger in Bioinformatics 39, no. 11 (2023): btad663.
Shivam Goel, PhD candidate, Panagiotis Lymperopoulos, PhD candidate, co-first authors for “A neurosymbolic cognitive architecture framework for handling novelties in open worlds,” co-authored by Ravenna Thielstrom, Evan Krause, Patrick Feeney, Pierrick Lorang, Sarah Schneider, Yichen Wei, Eric Kildebeck, Stephen Goss, Professor Michael C Hughes, Professor Liping Liu, Professor Jivko Sinapov, and Professor Matthias Scheutz in Journal Artificial Intelligence, June 2024. https://hrilab.tufts.edu/publications/goeletal24aij.pdf
Ethan Harvey, PhD candidate, published “Transfer Learning with Informative Priors: Simple Baselines Better than Previously Reported,” co-authored by Mikhail Petrov, and Professor Michael C. Hughes in Transactions on Machine Learning Research (TMLR), May 2024. ISSN 2835-8856. https://openreview.net/pdf?id=BbvSU02jLg
Pierrick Lorang, PhD student, published “Adapting to the "open world'': the utility of hybrid hierarchical reinforcement learning and symbolic planning,” co-authored by Horvath Helmut, Tobias Kietreiber, Patrik Zips, Clemens Heitzinger, and Professor Matthias Scheutz in Proceedings of the 2024 IEEE International Conference on Robotics and Automation (ICRA), May 2024.
Nicholas Rabb, PhD candidate, published “Investigating the effect of selective exposure, audience fragmentation, and echo-chambers on polarization in dynamic media ecosystems,” co-authored by Professor Lenore Cowen, and Professor JP de Ruiter in Applied Network Science 8, no. 1 (December 2023): 78.