School of Engineering
Department of Computer Science

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 2025-2026

Tony Astolfi, PhD student, presented “TurtleKV: A Dynamically Tunable Key/Value Store,” co-authored by Vidya Silai, Darby Huye, Lan Liu, Professor Raja R. Sambasivan, and Professor Johes Bater at the Northeast Database Day (January 2026, Boston).

Rukhshan Haroon, PhD candidate, presented “NeuroBridge: Using Generative AI to Bridge Cross-neurotype Communication Differences through Neurotypical Perspective-taking,” co-authored by Kyle Wigdor, Katie Yang, Nicole Toumanios, Eileen T. Crehan, and Professor Fahad Dogar at the the 27th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’25); published in Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '25). Association for Computing Machinery, New York, NY, USA, Article 46, 1–19.  https://doi.org/10.1145/3663547.3746337.  *This paper received the SIGACCESS Best Student Paper Award, presented to the individual(s) judged by an awards committee to have written the best student paper appearing in the ASSETS conference proceedings; the student must be the first author.

Alberto Naveira Montalvo, PhD candidate, presented “Variational Latent Space Co-Optimization for Protein–Small Molecule Co-Design,” co-authored by Professor Soha Hassoun at the AIChE PD2M AI for Pharma Conference (May 2026).

Other Publications

Sarah Abowitz, PhD candidate, published “Student Use of Commentaries with Inline Reference Resolution,” co-authored by Professor Gregory Crane in Hypertext 2025: Proceedings of the 36th ACM Conference on Hypertext and Social Media, September 2025, New York. https://doi.org/10.1145/3720553.3746681.

Budvin Edippuliarachchi, PhD candidate, published “AMRaCut: Scalable Partitioning for Adaptive Mesh Refinement,” co-authored by David Van Komen, and Professor Hari Sundar in SC '25: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November 2025, New York. https://doi.org/10.1145/3712285.3759863

Timothy Duggan, PhD candudate, published “The Price Is Not Right: Neuro-Symbolic Methods Outperform VLAs on Structured Long-Horizon Manipulation Tasks with Significantly Lower Energy Consumption,” co-authored by Pierrick Lorang, Hong Lu, and Professor Matthias Scheutz in Proceedings of the IEEE International Conference on Robotics & Automation (ICRA), June 2026, Vienna.

Alberto Naveira Montalvo, PhD candidate, published “Towards mechanistic understanding of mediated extracellular electron transfer,” co-authored by Apurva Kalia, Caroline M. Ajo-Franklin, Anne Brown, Prashant Deshlahra, and Professor Soha Hassoun in Biochemical Engineering Journal, vol. 232, April 2026, p. 110191.

Julia Santaniello, PhD student, published “Towards Reinforcement Learning from Neural Feedback: Mapping fNIRS Signals to Agent Performance,” co-authored by Matthew Russell, Benson Jiang, Donatello Sassaroli, Professor Robert Jacob, and Professor Jivko Sinapov in Proceedings of the 40th AAAI Conference on Artificial Intelligence, 40(21), 17670-17678. January 2026. https://doi.org/10.1609/aaai.v40i21.38823

 

AY 2024-2025

Carson Powers, PhD candidate, presented “'Threat modeling is very formal, it's very technical, and also very hard to do correctly': Investigating Threat Modeling Practices in Open-Source Software Projects,” co-authored by Harjot Kaur, Ronald Thompson, Sascha Fahl, and Professor Daniel Votipka at the 34th USENIX Security Symposium (August 2025).  

Rukhshan Haroon, PhD student, presented “TwIPS: A Large Language Model Powered Texting Application to Simplify Conversational Nuances for Autistic Users,” co-authored by Professor Fahad Dogar at the 26th International ACM SIGACCESS Conference on Computers and Accessibility (October 2024); published in Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '24). Association for Computing Machinery, New York, NY, USA, Article 24, 1–18. https://doi.org/10.1145/3663548.3675633

Ethan Harvey, PhD candidate, presented “Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective,” co-authored by Mikhail Petrov and Professor Michael C. Hughes at the NeurIPS 20224 Workshop on Fine-Tuning in Machine Learning: Principles and Scalability, December 2024, Vancouver.

Shivam Goel, PhD candidate, presented “FLEX: A Framework for Learning Robot-Agnostic Force-based Skills Involving Sustained Contact Object Manipulation,” co-authored by Shijie Fang, Wenchang Gao, Professor Matthias Scheutz, and Professor Jivko Sinapov at the International Conference on Robotics and Automation (ICRA), May 2025. https://tufts-ai-robotics-group.github.io/FLEX/

Liang (Leon) Wang, PhD candidate, presented “Empower Real-World BCIs with NIRS-X: An Adaptive Learning Framework that Harnesses Unlabeled Brain Signals,” co-authored by Jiayan Zhang, Jinyang Liu, Devon McKeon, David Guy Brizan, Giles Blaney, and Professor Rob Jacob at the ACM UIST 2024 Symposium on User Interface Software and Technology, October 2024, Pittsburgh.

Other Publications

Sarah Abowitz, PhD candidate, published “Bridging the Understanding Gap: Helping Readers Engage Directly with Foreign-Language Sources More Easily,” co-authored by Alison Babeu, and Professor Gregory Crane in JCDL 2024: Proceedings of the 24th ACM/IEEE Joint Conference on Digital Libraries, March 2025.  Article 38, 1-5.

Tanushree Burman, PhD candidate, published “Smart Motor: A Low-Cost Hardware and Software Toolkit for Introducing Supervised Machine Learning to Elementary School Students,” co-authored by Milan Dahal, Geling Xu, Chris Rogers, Jennifer Cross, and Professor Jivko Sinapov in AAAI Conference on Artificial Intelligence, March 2025. Proceedings of the AAAI Conference on Artificial Intelligence, 39(28), 29128-29136.

Tanushree Burman, PhD candidate, published “Balancing Act: Mastering Beam-and-Ball Control with Reinforcement Learning,” co-authored by Jevon Coney, Chris Rogers, Jennifer Cross, and Professor Jivko Sinapov in Robotics in Education, April 2025. Lecture Notes in Networks and Systems, vol 1544. Springer, Cham. https://doi.org/10.1007/978-3-031-98762-5_21