SIGBITS | Worcester Polytechnic Institute

Fall 2024 SIGBITS

Edited by Tian Guo
Reviewed by Craig Shue

New Faculty Joining the Department: The Computer Science department at Worcester Polytechnic Institute (WPI) welcomes two new tenure-track and teaching faculty in 2024. Prof. Prof. Raha Moraffah is a faculty member joining Computer Science to support both the teaching and research missions. Prof. Ramoza Ahsan will also be joining the department to support the teaching mission later this Fall.

Raha

Raha Moraffah, Assistant Professor

Raha earned her Ph.D. in computer science from Arizona State University. Her research spans machine learning, data mining, artificial intelligence, and causal inference, with a specific focus on developing trustworthy and responsible machine learning and generative AI algorithms. 

Ramoza

Ramoza Ahsan, Assistant Teaching Professor

These incoming faculty members will bring the total number of faculty to 40. Eight of our faculty have received NSF CAREER awards. The CS department is also home to two teaching professors who are on the tenure track, a path created by WPI in 2021 for otherwise contingent faculty. WPI is the first research university in the U.S. to create such a path to tenure specifically for teaching faculty.

Promotions:

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Wilson Wong, Associate Professor of Teaching

Wilson has been appointed as an associate professor of teaching. He joins 48 other teaching faculty members on this pioneering tenure track, which recognizes and rewards excellence in teaching.

The CS department currently serves over 1,250 undergraduate students, representing over 20% of WPI’s total undergraduate student body. The department has over 65 Ph.D. students and over 190 students seeking master’s-level degrees.

In 2024, the CS faculty research is supported by the NSF, NIH, DoE, and other federal and private funding sources with recent annual research expenditures averaging over $8.5 million. The CS department also has two new awardees of the National Science Foundation’s Computer and Information Science and Engineering Research Initiation Initiative (CRII), Prof. Roee Shraga and Prof. Hanmeng Zhan.

In 2024, the CS faculty has co-authored over 100 book chapters, journal papers, and conference papers. The publishing venues include top-tier journals and conferences such as JMLR, Nature Neuroscience, NeurIPS, SIGIR, S&P, KDD, ICDM, AAAI, VLDB, and SIGMOD.

Grants: 

Prof. Rose Bohrer is the PI on a National Science Foundation Grant: "Game Logic Programming." Award amount: $595,998.00. Project dates: May 1, 2024, to April 30, 2027.
Prof. Jun Dai is the PI and Prof. Xiaoyan Sun is the co-PI at WPI on the NSA NCAEC grant: “Strengthening Workforce Education: Excellence in Programming Securely (SWEEPS).” This is a coalition grant together with UC Davis, UMBC, Cal Poly, CRC, Dark Enterprises, and StrongKey. Total award amount: $2,500,000 + $750,000 (option year), WPI award amount: $690,000 + $206,999 (option year). Project dates: July 19, 2023, to July 19, 2025.
Prof. Jun Dai is the PI and Prof. Xiaoyan Sun is the co-PI on the NSA NCAEC grant “Expanding the National Cybersecurity Teaching Academy (NCTA).” Award amount transferred to WPI: $210,490.02 + $119,896 (option year). Project dates: August 14, 2023, to September 16, 2025.
Prof. Jun Dai is the PI at WPI on the NSF grant: “SaTc: EDU: Collaborative: An Assessment Driven Approach to Self-Directed Learning in Secure Programming (SecTutor).” Award amount transferred to WPI: $10,689.00. Project dates: June 1, 2024, to September 30, 2025.
Prof. Jun Dai is the PI and Prof. Xiaoyan Sun is the co-PI at WPI on the NSA NCAEC grant: “The National Cyber Teaching Academy (NCTA).” Award amount transferred to WPI: $34,760.25. Project dates: September 1, 2023, to December 31, 2024.
Prof. Tian Guo is the PI for a National Science Foundation Grant titled “Collaborative Research: CIRC: Planning-C: ExpAR: Scalable and Controllable AR Experimentation". This is a collaboration with the co-PI Feng Qian from the University of Southern California. Total award amount: $100,000, WPI award amount: $50,000. Project dates: August 1, 2024, to July 31, 2025.
Prof. Tian Guo is the PI for a National Science Foundation Grant titled “ExpandQISE: Track 1: Education and Research of System and Network Supports for Quantum Cloud". This grant includes a subaward to the Co-PI Chen Qian from the University of Santa Cruz. Total award amount: $799,995, WPI award amount: $563,996. Project dates: October 1, 2024, to September 30, 2027.
Prof. Tian Guo is the PI at WPI for a National Science Foundation Grant titled “Collaborative Research: CSR: Medium: Offloading Heterogeneous Distributed Workloads with Diverse Computation Models.” This is a collaborative award with the PI Sandip Kundu and Co-PI Russell Tessier from the University of Massachusetts Amherst. Total award amount: $1,199,998, WPI award amount: $399,999. Project dates: October 1, 2024, to September 30, 2028.
Prof. Tian Guo is the PI at WPI for a National Science Foundation Grant titled “Collaborative Research: SaTC: CORE: Small: Towards the Security of Immersive Multimedia Systems.” This is a collaborative award with the PI Sheng Wei and Co-PI Bo Yuan from Rutgers University. Total award amount: $599,995, WPI award amount: $200,000. Project dates: October 1, 2024, to September 30, 2027.
Prof. Neil Heffernan is the PI on the IES grant “Talking Math: Improving Math Performance and Engagement Through AI-Enabled Conversational Tutoring (CAIT).” WPI Award Amount: $3,749,600. Project dates: March 1, 2024, to February 28, 2027.
Prof. Neil Heffernan is the PI at WPI on the NSF grant “Using Artificial Intelligence to Personalize Mathematics Instruction to Students’ Interests.” WPI Award Amount: $299,199. Project dates: August 1, 2024, to July 31, 2028.
Prof. Neil Heffernan is the PI at WPI on the NSF grant: “Mid-scale R1-2: SafeInsights: A National Research Infrastructure for Large-Scale Learning Science and Engineering.” WPI Award Amount: $4,499,992. Project dates: May 1, 2024, to April 30, 2029.
Prof. Kyumin Lee serves as a PI, and Prof. Konrad Renata, Prof. Meredith Gore, and Dr. Diego Cardenosa serve as co-PIs on the “PACSP TOOLS: Strengthening conservation partnerships by advancing molecular and analytic tools for disrupting illegal wildlife trade” award from the National Science Foundation. Award amount: $1,983,255. Project dates: January 2025 to December 2028.
Prof. Roee Shraga is the PI on NSF Grant: “CRII: III: Improving the Utilization of Humans in Data Integration and Discovery.” Award amount: $174,995 .Project dates: September 2024 to August 2026.
Prof. Craig Shue serves as a PI and Profs. Jun Dai, Sherry Sun, and Robert Walls serve as co-PIs on the “2024 DoD Cyber Scholarship Program: Worcester Polytechnic Institute” award from the Department of Defense. Award amount: $116,398. Project dates: August 2024 to December 2025.
Prof. Erin Solovey is the PI, and Katherine Chen is the co-PI for a National Science Foundation grant: “RET Site: Engineering for People and the Planet: Research Experiences for Teaching Integrated STEM.” This grant renews NSF support for the RET Site program that has been running for the past three years and enables an additional three years. Award amount: $599,919. Project dates: June 1, 2024, to May 31, 2027.
Prof. Xiaoyan Sun is the PI and Prof. Jun Dai is the co-PI on the NSF grant: “SaTC: EDU: Developing Ready-to-Use Hands-on Labs with Portable Operating Environments for Digital Forensics Education.” Award amount transferred to WPI: $214,907.00. Project dates: October 15, 2023, to June 30, 2025.
Prof. Xiaoyan Sun is the PI and Prof. Jun Dai is the co-PI at WPI on the project “National Cyber Teaching Academy at WPI” supported by NSA NCAEC. Award amount: $194,339. Project dates: September 1, 2024, to August 31, 2025.
Prof. Hanmeng Zhan is the PI on NSF Grant: "CRII: Quantum Advantages through Discrete Quantum Walks.” Award amount: $174,420. Project dates: April 1, 2024 to March 31, 2026.

External Awards:

Prof. Tian Guo and her student Yiqin Zhao’s patent, “Visually coherent lighting for mobile augmented reality,” was awarded. US Patent App. 18/237,095, 2024.
The paper “ConDA: Contrastive Domain Adaptation for AI-generated Text Detection” co-authored by Prof. Raha Moraffah received the outstanding paper award from the Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics.
The paper “Devil in the Noise: Detecting Advanced Persistent Threats with Backbone Extraction,” coauthored by Prof. Fabricio Murai, received the best paper award from the IEEE Symposium on Computers and Communications (ISCC 2024).
Prof. Elke Rundensteiner’s paper with Prof. Matthew Ward, “Hierarchical parallel coordinates for exploration of large datasets,” from 1999 received the VIS Test-of-Time Award from the IEEE Visualization Conference.
Prof. Elke Rundensteiner’s paper, "MetaStore: Analyzing Deep Learning Meta-Data at Scale," has been nominated for the best paper award for PVLDB Vol. 17 (VLDB 2024), August 2024.
Prof. Elke Rundensteiner’s patent, “Machine learning systems and methods for attributed sequences,” was awarded. Zhuang; Zhongfang et al. US Patent App. 16/057,025.
Prof. Erin Solovey was named a 2024-25 Harvard-Radcliffe Institute Fellow at the Radcliffe Institute for Advanced Study at Harvard.
Prof. Jake Whitehill’s paper, titled "Speaker Diarization in the Classroom: How Much Does Each Student Speak in Group Discussions?" is the Winner of the Best Student Short Paper Award at Educational Data Mining.

Publications: 

Prof. Rose Bohrer’s Publications:

Rose Bohrer. “Programming Language Case Studies Can Be Deep.” Trends in Functional Programming in Education Workshop 2024.
Lena Dias, Benjamin Schneider, Rose Bohrer. “Neurotype Cafe: A Case Study in Neurodiverse Self-Representation.”
Foundations of Digital Games (FDG) 2024.
Rose Bohrer and Hannah Gommerstadt. “Linear Temporal Monitors for Session Types.” EXPRESS/SOS Workshop 2024.
Yichi Xu, Daniel Dougherty and Rose Bohrer. “A Coq Formalization of Unification Modulo Exclusive-Or (short paper).” International Conference on Logic Programming (ICLP) 2024 (to appear).
Rose Bohrer and Ashe Neth. “Pronoun Logic.” Queer in AI @ NAACL 2024.

JunDai

Prof. Jun Dai’s Publications:

O. Tawose, J. Dai, L. Yang, D. Zhao, "Toward Efficient Homomorphic Encryption for Outsourced Databases through Parallel Caching.” ACM SIGMOD 2023 International Conference on Management of Data.
I. Ngambeki, M. Bishop, J. Dai, P. Nico, "Validation of a Secure Programming Concept Inventory.” ACM Special Interest Group on Computer Science Education (SIGCSE) Technical Symposium (TS) 2023.

tian

Prof. Tian Guo’s Publications:

Yiqin Zhao, Rohit Pandey, Yinda Zhang, Ruofei Du, Feitong Tan, Chetan Ramaiah, Tian Guo, Sean Fanello. “Portrait Expression Editing With Mobile Photo Sequence.” SIGGRAPH Asia 2023 Technical Communications.
Yiqin Zhao and Tian Guo. 2024. “Demo: ARFlow: A Framework for Simplifying AR Experimentation Workflow.” In Proceedings of the 25th International Workshop on Mobile Computing Systems and Applications (HOTMOBILE '24).
Ashkan Ganj, Yiqin Zhao, Hang Su, and Tian Guo. 2024. “Mobile AR Depth Estimation: Challenges & Prospects.” In Proceedings of the 25th International Workshop on Mobile Computing Systems and Applications (HOTMOBILE '24).
Yiyang Zhao, Linnan Wang, and Tian Guo. “Multi-Objective Neural Architecture Search by Learning Search Space Partitions.” Journal of Machine Learning Research (JMLR), 2024.
Seyed Morteza Nabavinejad, Sherief Reda, and Tian Guo. "MediatorDNN: Contention Mitigation for Co-Located DNN Inference Jobs." 2024 IEEE 17th International Conference on Cloud Computing (CLOUD), 2024.
Seyed Morteza Nabavinejad, Sherief Reda and Tian Guo. “FairCIM: Fair Interference Mitigation by DNN Switching for Latency-Sensitive Inference Jobs.” 5th IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 2024.
Ashkan Ganj, Hang Su, Tian Guo. “Toward Robust Depth Fusion for Mobile AR With Depth from Focus and Single-Image Priors.” Poster paper. The 23rd IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2024.
Yiqin Zhao, Ashkan Ganj, Tian Guo. “Towards In-context Environment Sensing for Mobile Augmented Reality.” The 2nd ACM Workshop on Mobile Immersive Computing, Networking, and Systems (ImmerCom), 2024.
Yasra Chandio, Noman Bashir, Tian Guo, Elsa Olivetti, Fatima M. Anwar. “Scoping Sustainable Collaborative Mixed Reality.” IEEE International Symposium on Emerging Metaverse (ISEMV), 2024.
Yiyang Zhao, Yunzhuo Liu, Bo Jiang, Tian Guo. “CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework.” the Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.

ltharrison

Prof. Lane Harrison’s Publications:

Rakotondravony, N., Pöhls, H.C., Pfeifer, J. and Harrison, L., 2024, June. Viz 4 NetSec: Visualizing Dynamic Network Security Configurations of Everyday Interconnected Objects in Home Networks. In International Conference on Human-Computer Interaction (pp. 164-185). Cham: Springer Nature Switzerland.
Chen, M., Li, Y., Shrestha, H., Rakotondravony, N., Teixeira, A., Harrison, L. and Dempski, R.E., 2024. FlowAR: A Mixed Reality Program to Introduce Continuous Flow Concepts. Journal of Chemical Education, 101(5), pp.1865-1874.
Alebri, M., Noëlle, R. and Lane, H., 2024, October. Design Patterns in Right-to-Left Visualizations: The Case of Arabic Content. In IEEE Transactions on Visualization and Computer Graphics. IEEE.
Ge, L.W., Hedayati, M., Cui, Y., Ding, Y., Bonilla, K., Joshi, A., Ottley, A., Bach, B., Kwon, B.C., Rapp, D.N. Harrison. L and Peck, E., 2024, May. Toward a More Comprehensive Understanding of Visualization Literacy. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7).
Cui, Y., Lily, W.G., Ding, Y., Harrison, L., Yang, F. and Kay, M., 2024. Promises and Pitfalls: Using Large Language Models to Generate Visualization Items.
Alkhathlan, M., Cachel, K., Shrestha, H., Harrison, L. and Rundensteiner, E., 2024, June. Balancing Act: Evaluating People’s Perceptions of Fair Ranking Metrics. In The 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 1940-1970).

nth

Prof. Neil Heffernan’s Publications:

Journal Articles:

Zhang, F., Li, C., Henkel, O., Xing, W., Baral, S., Heffernan, N., & Li, H. (2024). Math-LLMs: AI Cyberinfrastructure with Pre-trained Transformers for Math Education. International Journal of Artificial Intelligence in Education, 1-24. https://doi.org/10.1007/s40593-024-00416-y
Vanacore, K. P., Gurung, A., Sales, A., & Heffernan, N. (2024). Effect of Gamification on Gamers: Evaluating Interventions for Students Who Game the System: Evaluating Interventions for Students Who Gaming the System. Journal of Educational Data Mining, 16(1), 112–140. https://doi.org/10.5281/zenodo.11549799
Cheng, L., Croteau, E., Baral, S., Heffernan, C., & Heffernan, N. (2024). Facilitating Student Learning With a Chatbot in an Online Math Learning Platform. Journal of Educational Computing Research, 0(0). Author's Copy https://doi.org/10.1177/07356331241226592

Book Chapters:

Cheng, L., Prihar, E., Baral, S., Gurung, A., Botelho, A. T., Haim A., Heffernan, C., Patikorn, T., Sales, A., & Heffernan, N. T. (2023). Authoring Tools for Crowdsourcing from Teachers to Enhance Intelligent Tutoring Systems. In Sinatra, A.M., Graesser, A.C., Hu, X., Townsend, L.N. and Rus, V. (Eds.), Design Recommendations for Intelligent Tutoring Systems: Volume 11 - Professional Career Education, Orlando, FL: US Army Combat Capabilities Development Command - Soldier Center. ISBN 978-0-9977258-5-8. Available at: https://gifttutoring.org/documents/167

Conference Papers:

Gurung, A., Vanacore, K., Mcreynolds, A. A., Ostrow, K. S., Worden, E., Sales, A. C., & Heffernan, N. T. (2024, March). Multiple Choice vs. Fill-In Problems: The Trade-off Between Scalability and Learning. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 507-517). https://doi.org/10.1145/3636555.3636908
Lee, M., Siedahmed, A., & Heffernan, N. (2024). Expert Features for a Student Support Recommendation Contextual Bandit Algorithm. In Proceedings of the 14th Learning Analytics and Knowledge Conference (LAK '24). Association for Computing Machinery, New York, NY, USA, 864–870. https://doi.org/10.1145/3636555.3636909
Li, H., Li, C., Xing, W., Baral, S., & Heffernan, N. (2024, March). Automated Feedback for Student Math Responses Based on Multi-Modality and Fine-Tuning. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 763-770). https://doi.org/10.1145/3636555.3636860
Li, H., Xing, W., Li, C., Zhu, W., Heffernan, N. (2024). Positive Affective Feedback Mechanisms in an Online Mathematics Learning Platform. In Proceedings of the Eleventh ACM Conference on Learning @ Scale (L@S '24). Association for Computing Machinery, New York, NY, USA, 371–375. PDF.
Ritter, S., Fancsali, S. E., Murphy, A., Heffernan, N., Motz, B., Mallick, D. B., Roschelle, J., McNamara, D., Williams, J. J. (2024). Fifth Annual Workshop on A/B Testing and Platform-Enabled Learning Research. In Proceedings of the Eleventh ACM Conference on Learning @ Scale (L@S '24). Association for Computing Machinery, New York, NY, USA, 565–566. PDF.
Vanacore, K., Gurung, A., Sales, A., & Heffernan, N. T. (2024, March). The Effect of Assistance on Gamers: Assessing the Impact of On-Demand Hints & Feedback Availability on Learning for Students Who Game the System. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 462-472). https://doi.org/10.1145/3636555.3636904
Zambrano, A. F., Baker, R. S., Baral, S., Heffernan, N. T., Lan, A. (2024). From Reaction to Anticipation: Predicting Future Affect. In Proceedings of the 17th International Conference on Educational Data Mining (EDM'24), 566-574. Paper.

dkorkin

Prof. Dmitry Korkin’s Publications:

Joglekar, A., Hu, W., Zhang, B., Narykov, O., Diekhans, M., Marrocco, J., ..., Korkin, D., Ross, M.E. & Tilgner, H. U. Single-cell long-read sequencing-based mapping reveals specialized splicing patterns in developing and adult mouse and human brain. Nature Neuroscience, 27, 1051–1063 (2024).
Cui, H., Srinivasan, S., Gao, Z. & Korkin, D. The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations. Biomolecules, 14(1): 40-63 (2023)

kmlee

Prof. Kyumin Lee’s Publications:

Yichuan Li, Kaize Ding, Jianling Wang, and Kyumin Lee. "Empowering Large Language Models for Textual Data Augmentation." Annual Meeting of the Association for Computational Linguistics. 2024.
Guanyi Mou, Yun Yue, Kyumin Lee, and Ziming Zhang. "Wildlife Product Trading in Online Social Networks: A Case Study on Ivory-Related Product Sales Promotion Posts." In Proceedings of the International AAAI Conference on Web and Social Media, vol. 18, pp. 1096-1109. 2024.
Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu, and Chenlei Guo. "MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning." In The Twelfth International Conference on Learning Representations. 2024.
Di You, and Kyumin Lee. "Alleviating Confounding Effects with Contrastive Learning in Recommendation." In European Conference on Information Retrieval, pp. 465-480. 2024.
Wen Ge, Guanyi Mou, Emmanuel O. Agu, and Kyumin Lee. "Deep Heterogeneous Contrastive Hyper-Graph Learning for In-the-Wild Context-Aware Human Activity Recognition." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, no. 4 (2024): 1-23.
Yichuan Li, Kaize Ding, and Kyumin Lee. "GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs." In Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 2745-2757. 2023.
Yichuan Li, Jialong Han, Kyumin Lee, Chengyuan Ma, Benjamin Yao, and Xiaohu Liu. "KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness." In Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 6864-6876. 2023.

yli15

Prof. Yanhua Li’s Publications:

Xinbo Zhao, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Yanhua Li, Jun Luo, Urban-Focused Multi-Task Offline Reinforcement Learning with Contrastive Data Sharing. The 30th SIGKDD conference on Knowledge Discovery and Data Mining (KDD 2024), Barcelona, Spain, August 25 - 29, 2024.
Mingzhi Hu, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo. Only Attending What Matter within Trajectories -- Memory-Efficient Trajectory Attention. SIAM International Conference on Data Mining (SDM 2024), Houston, TX April 18 - 20, 2024.
Nasrin Kalanat, Yiqun Xie, Yanhua Li, Xiaowei Jia, Spatial-Temporal Augmented Adaptation via Cycle-Consistent Adversarial Network: An Application in Streamflow Prediction. SIAM International Conference on Data Mining (SDM 2024), Houston, TX April 18 - 20, 2024.
Runlong Yu, Chonghao Qiu, Robert Ladwig, Paul Hanson, Yiqun Xie, Yanhua Li, and Xiaowei Jia, Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations. IEEE International Conference on Data Mining (ICDM 2024), Abu Dhabi, UAE, Dec. 9 - Dec 12, 2024.
Yuhang Liu, Yingxue Zhang, Xin Zhang, Yu Yang, Yiqun Xie, Sahar Ghanipoor Machiani, Yanhua Li, and Jun Luo, Align Along Time and Space: A Graph Latent Diffusion Model for Traffic Dynamics Prediction. IEEE International Conference on Data Mining (ICDM 2024), Abu Dhabi, UAE, Dec. 9 - Dec 12, 2024.

Xiaozhong

Prof. Xiaozhong Liu’s Publications:

Yang Wu, Chenghao Wang, Ece Gumusel, and Xiaozhong Liu. Knowledge-infused legal wisdom: Navigating LLM consultation through the lens of diagnostics and positive-unlabeled reinforcement learning. In The 62nd Annual Meeting of the Association for Computational Linguistics (findings), 2024.
Yongqiang Ma, Lizhi Qin, Jiawei Liu, Yangyang Kang, Yue Zhang, Wei Lu, Xiaozhong Liu, and Qikai Cheng. From model-centered to human-centered: Revision distance as a metric for text evaluation in llms-based applications. In The 62nd Annual Meeting of the Association for Computational Linguistics (findings), 2024.
Pengwei Yan, Yangyang Kang, Zhuoren Jiang, Kaisong Song, Tianqianjin Lin, Changlong Sun, and Xiaozhong Liu. Modeling scholarly collaboration and temporal dynamics in citation networks for impact prediction. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 2522–2526, 2024.
Zilong Lin, Zhengyi Li, Xiaojing Liao, XiaoFeng Wang, and Xiaozhong Liu. MAWSEO: Adversarial wiki search poisoning for illicit online promotion. In 2024 IEEE Symposium on Security and Privacy (SP), pages 388–406. IEEE, 2024.
Kaihang Pan, Juncheng Li, Wenjie Wang, Hao Fei, Hongye Song, Wei Ji, Jun Lin, Xiaozhong Liu, Tat-Seng Chua, and Siliang Tang. I3: Intent-introspective retrieval conditioned on instructions. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 1839–1849, 2024.
Weikang Yuan, Junjie Cao, Zhuoren Jiang, Yangyang Kang, Jun Lin, Kaisong Song, tianqianjin lin, Pengwei Yan, Changlong Sun, and Xiaozhong Liu. Can large language models grasp legal theories? Enhance legal reasoning with insights from multi-agent collaboration. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (findings), 2024.
Kai Zhang, Fubang Zhao, Yangyang Kang, and Xiaozhong Liu. LLM-based Medical Assistant Personalization with Short- and Long- Term Memory Coordination. In Proceedings of The 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024.
Kai Zhang, Pengcheng Li, Kaisong Song, Xurui Li, Yangyang Kang, Xuhong Zhang, and Xiaozhong Liu. Biomed- ical Knowledge Derivation from Scientific Publications via Dual-Graph Resonance. In Proceedings of 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (COLING), 2024.
Pengwei Yan, Kaisong Song, zhuoren Jiang, Yangyang Kang, Tianqianjin Lin, Changlong Sun, and Xiaozhong Liu. Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence. AAAI, 2024.
Tianqianjin Lin, Kaisong Song, Zhuoren Jiang, Yangyang Kang, Weikang Yuan, Xurui Li, Changlong Sun, Cui Huang, and Xiaozhong Liu. Towards human-like perception: Learning structural causal model in heterogeneous graph. Information Processing & Management, 61(2):103600, 2024.
Heng Huang, Yunhan Bai, Hongwei Liang, and Xiaozhong Liu. IR embedding fairness inspection via contrastive learning and human-ai collaborative intelligence. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, pages 142–153. Springer, 2024.
Yuehan Zhang, Yongqiang Ma, Jiawei Liu, Xiaozhong Liu, Xiaofeng Wang, and Wei Lu. Detection vs. anti-detection: Is text generated by AI detectable? In International Conference on Information, pages 209–222. Springer, 2024.
Weikang Yuan, Zhuoren Jiang, Tianqianjin Lin, Pengwei Yan, Siqi Luo, and Xiaozhong Liu. Do information dissemination patterns differ among platforms with distinct mechanisms? A comparative study based on dynamics of trending topics. iConference 2024. Proceedings, 2024.

Raha

Prof. Raha Moraffah’s Publications:

Zhen Tan*, Chengshuai Zhao*, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, and Huan Liu. “Glue pizza and eat rocks”–Exploiting Vulnerabilities in Retrieval‑Augmented Generative Models”. To appear in EMNLP (2024).
Raha Moraffah, and Huan Liu. "Exploiting Class Probabilities for Black-box Sentence-level Attacks". European Chapter of the Association for Computational Linguistics (EACL) 2024, pages 1557–1568.
Raha Moraffah, Shubh Khandelwal, Amrita Bhattacharjee, and Huan Liu. “Adversarial Text Purification: A Large Language Model Approach for Defense”. The Pacific‑Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2024. pp. 65-77.
Paras Sheth, Raha Moraffah, Tharindu Kumarage, Aman Chadha, and Huan Liu. “Causality Guided Disentanglement for Cross‑Platform Hate Speech Detection”. ACM International Conference on Web Search and Data Mining (WSDM) 2024. pp 626-635.
Zhen Tan*, Chengshuai Zhao*, Raha Moraffah, Yifan L, Yu Kong, Tianlong Chen, and Huan Liu. “The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative”. IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) ‑ ReGenAI 2024.
Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, and Huan Liu. “Towards LLM‑guided Causal Explainability for Black‑box Text Classifiers”. Association for the Advancement of Artificial Intelligence (AAAI)‑ReLM 2024.
Amrita Bhattacharjee, Tharindu Kumarage, Raha Moraffah, and Huan Liu. 2023. ConDA: Contrastive Domain Adaptation for AI-generated Text Detection. In Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, pages 598–610, Nusa Dua, Bali, Outstanding Paper Award.
Tharindu Kumarage, Paras Sheth, Raha Moraffah, Joshua Garland, and Huan Liu. “How Reliable Are AI‑Generated‑Text Detectors? An Assessment Framework Using Evasive Soft Prompts”. Findings of the Association for Computational Linguistics: EMNLP 2023. pages 1337–1349, Singapore.

Fabricio

Prof. Fabricio Murai's Publications:

Olulana Oluseun, Kathleen Cachel, Fabricio Murai, Elke Rundensteiner. “Hidden or Inferred: Fair Learning-To-Rank With Unknown Demographics”. AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES 2024). 12 pages.
Chiman Salavati, Shannon Song, Willmar Sosa Diaz, Scott A. Hale, Roberto E. Montenegro, Fabricio Murai, Shiri Dori-Hacohen. “Reducing Biases towards Minoritized Populations in Medical Curricular Content via Artificial Intelligence for Fairer Health Outcomes”. AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES 2024). 12 pages.
Caio M. C. Viana, Carlos Henrique Gomes Ferreira, Fabricio Murai, Aldri Santos, Lourenço Alves Pereira, Jr. “Devil in the Noise: Detecting Advanced Persistent Threats with Backbone Extraction”. IEEE Symposium on Computers and Communications (ISCC 2024). 6 pages. best paper award.
Gavin Butts, Pegah Emdad, Jethro Lee, Shannon Song, Chiman Salavati, Willmar Sosa Diaz, Shiri Dori-Hacohen, Fabricio Murai. “Towards Fairer Health Recommendations: finding informative unbiased samples via Word Sense Disambiguation”. FAccTRec Workshop on Responsible Recommendation at RecSys, 2024. 6 pages.
(Poster) Gavin Butts, Pegah Emdad, Jethro Lee, Shannon Song, Chiman Salavati, Willmar Sosa Diaz, Roberto Montenegro, Scott Hale, Shiri Dori-Hacohen, Fabricio Murai. “Diagnosing Bias: Predictive AI Models for Identifying Biased Health Information in Medical Curriculum”. IEEE MIT Undergraduate Research and Technology Conference (URTC), 2024.

Prof. Rodica Neamtu’s Publications:

Stephen Price**, Kiran Judd**, Matthew Gleason**, Kyle Tsaknopoulos, Danielle L. Cote, Rodica Neamtu, Analyzing Impact of Processing Parameters and Material Properties on Symmetry of Wire-Arc Directed Energy Deposit Beads, in Metals Journal Special Issue Editorial Board Members’ Collection Series: Additive Manufacturing Technology, 2024.
Stephen Price *, Kiran Judd*, Matt Gleason*, Kyle Tsaknopoulos, Danielle L. Cote, Rodica Neamtu,
Advancing Wire Arc DED: Analyzing Impact of Materials and Parameters on Bead Shape, In Metals Special Issue: Optimization of Metal Additive Manufacturing Processes (Volume 2), 2024.
Mehrnoush Alizadeh*, Stephen Price*, Rishabh Kheni*, Bryer Sousa, Danielle Cote, Rodica Neamtu, A Comparative Study of Clustering Methods for Nanoindentation Mapping Data, In Integrating Materials and Manufacturing Innovation 2024.
Adrianna Staszewska**, Deepali Patil*, Akshatha Dixith*, Rodica Neamtu, Diana Lados, A machine learning methodology for porosity classification and process map prediction in metal additive manufacturing. In Proceedings of "Progress in Additive Manufacturing" 2023. https://link.springer.com/article/10.1007/s40964-023-00544-2
Rodica Neamtu, Where Story-Telling Meets Project-Based Learning: Incorporating Projects into CS Curriculum, SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2 Pages 1257https://doi.org/10.1145/3545947.3573361

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Prof. Daniel Reichman’s Publications:

Daniel Reichman, Joshua C. Peterson, Thomas L. Griffiths. Machine learning for human decision modeling. Decision, to appear.
Dan Mikulicner, Daniel Reichman. Size and Depth of Monotone Neural Networks: Interpolation and Approximation." IEEE Transactions on Neural Networks and Learning Systems (2024). DOI: 10.1109/TNNLS.2024.3387878

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Prof. Charles Davis Roberts’ Publications:

Charlie D. Roberts. “Screamer: a programming language for live coding ray marchers.” https://charlieroberts.github.io/screamer/playground/

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Prof. Elke Rundensteiner’s Publications:

Peter Van NoStrand, Dennis Hofmann, Lei Ma, Belisha Genin, Randy Huang, and Elke Rundensteiner. “Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions,” Demonstration, VLDB 2024, Guangzhou, China.
Lei Ma. Lei Cao, Peter Van NoStrand, Dennis Hofmann, Su Yao, and Elke Rundensteiner. “Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data.” ACM SIGMOD 2025.
Thomas Considine, Rob Jensen, Jim Snyder, John Kelley, Nicholas Josselyn, Biao Yin, Elke Rundensteiner, and Ziming Zhang. “Smart AI-Driven Materials Science Analytics for the US Army.” Artificial Intelligence for Materials Science and Engineering, ASM Handbook, 2024.
Kathleen Cachel and Elke Rundensteiner. “Wise Fusion: Group Fairness Enhanced Rank Fusion.” 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024) Full Research Track.
Oluseun Olulana, Kathleen Cachel, Fabricio Murai and Elke Rundensteiner. “Hidden or Inferred: Fair Learning-To-Rank With Unknown Demographics.” AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society Conference (AIES 2024) San Jose, CA. October 21-23, 2024. Full Research Paper.
Kathleen Cachel and Elke Rundensteiner. “FairRankTune: A Python Toolkit for Fair Ranking Tasks, Wise Fusion: Group Fairness Enhanced Rank Fusion.” 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), Demo Paper Track.
Dennis M. Hofmann, Peter M. VanNostrand, Lei Ma, Huayi Zhang, Joshua C. DeOliveira, Lei Cao, Elke A. Rundensteiner. “Agree to Disagree: Robust Anomaly Detection with Noisy Labels.” ACM SIGMOD 2025.
H. Shrestha, M. Alkhathlan, K. Cachel, L. Harrison, and E. Rundensteiner. “Exploring Fairness across Many Rankings.” IEEE VIS 2024, Poster Paper.
M. Alkhathlan, K. Cachel, H. Shrestha, L. Harrison, and E. Rundensteiner, “Balancing Act: Evaluating People's Perceptions of Fair Ranking Metrics.” 2024 ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT 2024), Rio de Janeiro, Brazil, 2024.
Peter VanNostrand, Dennis Hofmann, Lei Ma and Elke Rundensteiner. “Actionable Recourse for Automated Decisions: Examining the Effects of Counterfactual Explanation Type and Presentation on Lay User Understanding.” 2024 ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT 2024), Rio de Janeiro, Brazil, 2024.
K. Cachel and E. Rundensteiner. “PreFAIR: Combining Partial Preferences for Fair Consensus Decision-making.” 2024 ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT 2024), Rio de Janeiro, Brazil, 2024.
Liang Zhang, Mohamed Y. Eltabakh and Elke A. Rundensteiner. “CLIMBER: Pivot-Based Approximate Similarity Search over Big Data Series.” IEEE ICDE 2024.
Huayi Zhang, Binwei Yan, Lei Cao, Samuel Madden, and Elke Rundensteiner. “MetaStore: Analyzing Deep Learning Meta-Data at Scale.” VLDB 2024.
Dongyu Zhang, Ruofan Hu, and Elke Rundensteiner. “CoLafier: Collaborative Noisy Label Purifier With LID Guidance.” SIAM International Conference on Data Mining (SDM24), April 18 - 20, 2024, Houston, TX, U.S.
Jidapa Thadajarassiri, Walter Gerych, Xiangnan Kong, and Elke Rundensteiner. “Amalgamating Multi-Task Models with Heterogeneous Architectures.” AAAI 2024, Vancouver, Canada, Feb 2024.

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Prof. Gabor Sarkozy’s Publications:

Andras Gyarfas, Ryan Martin, Miklos Ruszinko, Gabor Sarkozy. “Proper edge colorings of planar graphs with rainbow C_4-s." Accepted for publication in the Journal of Graph Theory.

Roee

Prof. Roee Shraga’s Publications:

Brinkmann, Alexander, Roee Shraga, and Christina Bizer. "SC-block: Supervised contrastive blocking within entity resolution pipelines." European Semantic Web Conference. Cham: Springer Nature Switzerland, 2024. (Spotlight paper).
Fan, Grace, Roee Shraga, and Renée J. Miller. "Finding Support for Tabular LLM Outputs." Proceedings of the VLDB Endowment. ISSN 2150 (2024): 8097.
Pal, Koyena, Aamod Khatiwada, Roee Shraga, and Renée J. Miller. "ALT-GEN: Benchmarking Table Union Search using Large Language Models." Proceedings of the VLDB Endowment. ISSN 2150 (2024): 8097. (Best paper, TADA Workshop).
Yael Amsterdamer, Sourav S. Bhowmick, Renata Borovica-Gajic, Jesús Camacho-Rodríguez, Jinli Cao, Barbara Catania, Panos K. Chrysanthis, Carlo Curino, Amr El Abbadi, Avrilia Floratou, Juliana Freire, Stratos Idreos, Vana Kalogeraki, Sujaya Maiyya, Alexandra Meliou, Madhulika Mohanty, Fatma Özcan, Liat Peterfreund, Soror Sahri, Sana Sellami, Roee Shraga, Utku Sirin, Wang-Chiew Tan, Bhavani Thuraisingham, Yuanyuan Tian, Genoveva Vargas-Solar, Meihui Zhang, Wenjie Zhang, Sihem Amer-Yahia„ Divyakant Agrawal. Diversity, equity and inclusion activities in database conferences: A 2023 report. ACM SIGMOD Record 53.2 (2024): 63-67.
G. Fan, R. Shraga and R. J. Miller, "Gen-T: Table Reclamation in Data Lakes," 2024 IEEE 40th International Conference on Data Engineering (ICDE), Utrecht, Netherlands, 2024, pp. 3532-3545, doi: 10.1109/ICDE60146.2024.00272.

esolovey

Prof. Erin Solovey’s Publications:

Christopher Micek, Erin T Solovey. “Examining the Impact of Digital Jury Moderation on the Polarization of U.S. Political Communities on Social Media.” Interacting with Computers, 2024; iwae036.
Chen, K., Taylor, D., Solovey, E.T. (2024). “Research Experiences for Teachers (RET) Site at WPI: Engineering for People and the Planet as Inspiration to Teach Integrated STEM.” Proceedings of the American Society for Engineering Education (ASEE’24).
Micek, C., Solovey, E.T., Rodrigues, L., Eilks, A., Warnke, L., Putze, F. (2024). “Team Cognitive Informatics: Leveraging Brain Sensing to Assess and Augment Team Performance in Creative Collaboration.” ACM CHI’24 Workshop on the Future of Cognitive Personal Informatics. 6 pages.
Micek, C., Solovey, E.T. (2024). “Physiological Signals for Teamwork: User-Centered Design of a Brain-Computer Interface to Enhance Creative Collaboration.” ACM CHI’24 Workshop on PhysioCHI: Towards Best Practices for Integrating Physiological Signals in HCI. 12 pages.

xsun7

Prof. Xiaoyan Sherry Sun’s Publications:

Qingtian Zou, Lan Zhang, Anoop Singhal, Xiaoyan Sun and Peng Liu, “Analysis of Neural Network Detectors for Network Attacks", Journal of Computer Security. 2023.
Lan Zhang, Qingtian Zou, Anoop Singhal, Xiaoyan Sun and Peng Liu. “Evaluating Large Language Models for Real-World Vulnerability Repair in C/C++ Code", 10th ACM International Workshop on Security and Privacy Analytics (IWSPA 2024).
Qingtian Zou, Lan Zhang, Xiaoyan Sun, Anoop Singhal, Peng Liu. “Using Explainable AI for Neural Network Based Network Attack Detection". IEEE Computer. 2024.

Prof. Shubbhi Taneja’s Publications:

Anurag Dasgupta and Venkat Margapuri and Simon Shamoun and Shubbhi Taneja and Matthew Toups. “Hands-on Learning: Teaching Parallel and Distributed Computing through Unplugged Activities in Undergraduate CS Courses.” EduHPC Workshop, SC 2024.
Aliza Lisan, Tapasya Patki, Stephanie Brink, Henry Yang, Spencer Greene, Konstantinos Parasyris, Shubbhi Taneja, Hank Child. “PerfFlowAspect: A User-Friendly Performance Tool for Scientific Workflow.” Student poster, SC 2024.

jrwhitehill

Prof. Jacob Richard Whitehill’s Publications:

Wang, J. Dudy, S., He, X., Wang, Z., Southwell, R., and Whitehill, J. "Speaker Diarization in the Classroom: How Much Does Each Student Speak in Group Discussions?" Educational Data Mining. Winner of Best Student Short Paper Award.
He, X., Wang, J., Trinh, V.A., McReynolds, A., and Whitehill, J. "Tracking Classroom Movement Patterns with Person Re-Id.” Educational Data Mining. PDF.
Whitehill, J., and LoCasale-Crouch, J. "Automated Evaluation of Classroom Instructional Support with LLMs and BoWs: Connecting Global Predictions to Specific Feedback.” Journal of Educational Data Mining. PDF.
Southwell, R. Ward, W., Trinh, V.A., Clevenger, C., Clevenger, C., Watts, E., Reitman, J., D'Mello, S., and Whitehill, J. "Automatic Speech Recognition Tuned for Child Speech in the Classroom.” International Conference on Sound, Speech, and Signal Processing (ICASSP).
D'Mello, S., Biddy, Q., Breideband, T., Bush, J., Chang, M., Cortez, A., Flanigan, J., Foltz, P., Gorman, J., Hirshfield, L., Ko, M., Krishnaswamy, N., Lieber, R., Martin, J., Palmer, M., Penuel, W., Philip, T., Puntambekar, S., Pustejovsky, J., Reitman, J., Sumner, T., Tissesnbaum, M., Walker, L., and Whitehill, J. "From learning optimization to learner flourishing: Reimagining AI in Education at the Institute for Student‐AI Teaming (iSAT)". AI Magazine 45, no. 1. PDF.

hzhan

Prof. Hanmeng Zhan’s Publications:

Q. Chen, C. Godsil, M. Sobchuk, H. Zhan. Hamiltonians of bipartite walks. Electronic Journal of Combinatorics. In press.

Professional Engagements and Leadership: 

Prof. Jun Dai serves on the Career Kickstart (CK) Cyber Advisory Committee for College Board, the non-profit organization that clears a path for all students to own their future through the Advanced Placement (AP) Program, the SAT, and more. The committee is tasked with expanding the AP model to establish course frameworks in Networking Fundamentals and Cybersecurity Fundamentals.
Prof. Jun Dai serves on the Committee of ACM Update to Cybersecurity Curricula 2017: Curriculum Guidelines for Post-Secondary Degree Programs in Cybersecurity (CSEC 2017). The update focuses on “Foundations in Cybersecurity,” which will lead to a forthcoming curriculum guideline titled “Supplement to CSEC 2017: Content for a Foundational Cybersecurity Degree Course.”
Prof. Jun Dai serves on the planning committee and contributes to the “E3C: A Report of Early College Cybersecurity Credit,” investigating early college credit in cybersecurity (E3C) to expand the quantity and quality of the high school-to-college pipeline in cybersecurity.
Prof. Neil Heffernan is featured in an article titled “Talking Math: WPI Researcher Neil Heffernan Leads Effort to Develop AI Math Tutor”. April 24, 2024, WPI Press Release by Colleen Wamback.
Prof. Neil Heffernan is featured in an article titled “Husband and wife to develop AI math tutor with WPI, $4M in funding.” April 25, 2024, Worcester Business Journal.
Prof. Neil Heffernan is featured in an article titled “US Dept. Of Ed Releases ‘Designing for Edu with AI’ Developer Guide.” July 12, 2024, Ed Tech Digest.
Prof. Neil Heffernan served as an NSF reviewer for two panels: (1) Innovations in Graduate Education (IGE) (May 23-24), and (2) Personalized Engineering Learning (PEL) Ideas Lab (June 11-12, 2024).
Prof. Neil Heffernan was invited to speak at the Robertson Foundation “Frontiers” Roundtable. September 12, 2024.
Prof. Dmitry Korkin participated in a month-long summer international School for Molecular and Theoretical Biology for gifted high-school students hosted by Sabanci University in Turkey. His group of 6 high-school and 3 undergraduate students studied the evolution of repeat proteins and their functional impact by alternative splicing.
Prof. Dmitry Korkin was invited to give a talk at WPI-hosted Nature conference “Cracking the Code: The Dawn of Nucleic Acid Medicines” on October, 2023.
Prof. Xiaozhong Liu led the panel - “Social Risks in the Era of Generative AI” at 87th Annual Meeting of the Association for Information Science and Technology (ASIST).
Prof. Xiaozhong Liu led the panel - “Human Subjectivity in Information Practice and AI Governance” at 87th Annual Meeting of the Association for Information Science and Technology (ASIST).
Prof. Xiaozhong Liu is invited to serve as a guest editor for special issue at on “Generative Artificial Intelligence (AI) for Cybersecurity”. MDPI Journal.
Prof. Raha Moraffah is co-organizing a tutorial on “Defending Against Generative AI Threats in NLP’’ at SBP-BRiMS 2024, September 18-20.
Prof. Raha Moraffah was invited to give a talk on “Adversarial Attacks in the Era of Language Models” at Arizona State University, Special seminar event, September 2024.
Prof. Raha Moraffah was invited to give a talk on “Causal Feature Selection in the Era of Big Data” at Causal inference for time series data Workshop@UAI, Barcelona, Spain, July 15-19, 2024.
Prof. Raha Moraffah was invited to give a talk on “Causality and Feature Selection” at 2024 SIAM Annual Meeting (AN24), July 18-20, 2024.
Prof. Raha Moraffah is invited to serve as a guest editor for special issue at on “Generative Artificial Intelligence (AI) for Cybersecurity”. MDPI Journal.
Prof. Raha Moraffah’s dissertation on “Responsible Machine Learning: Security, Robustness, and causality” has been awarded the 2024 Dean’s Dissertation Award from the Ira A. Fulton Schools of Engineering at Arizona State University and is selected as ASU’s nominee for the “CGS/ProQuest Distinguished Dissertation Awards 2024” in the category of Mathematics, Physical Science & Engineering.
Prof. Fabricio Murai delivered an invited talk at the Shrewsbury Public Library to inaugurate their Distinguished Lecture Series in AI, on January 23, 2024.
Prof. Fabricio Murai delivered an invited talk at the Marlborough Public Library entitled " A Journey into AI and its Impact on our Lives", on April 30, 2024.
Prof. Fabricio Murai delivered a talk entitled "Devil in the Noise: Detecting Advanced Persistent Threats with Backbone Extraction" at the Universidade Federal de Minas Gerais in Belo Horizonte (Brazil), on June 11, 2024. The talk is based on his work that has received the best paper award at the IEEE ISCC 2024.
Prof. Fabricio Murai delivered a lightning talk on "Fostering a Disability-Inclusive Research Culture with Dynamic Mutual Micro-Accommodations (DyMMAs)" at the CMD-IT/ACM Richard Tapia Conference, on September 19, 2024.
Prof. Fabricio Murai co-organized a Birds-of-a-Feather session to introduce " Disabled In Computing - a New Community for Faculty and Graduate Students with Disabilities", a community he helped co-found with Prof. Shiri Dori-Hacohen (UConn), on September 20, 2024.
Prof. Rodica Neamtu delivered the keynote address to more than 300 professionals in the insurance industry at the New England Employee Benefits Council (NEEBC) 2024 Summit in Norwood in May 2024. Her keynote address, "Racing to the Future: AI Trends Shaping HR and Employee Benefits," explored the dynamic landscape of employee benefits in the face of accelerated change. The keynote delved into futuristic trends, artificial intelligence, and the speed at which the workforce and skills are evolving.
Prof. Rodica Neamtu was invited to give a talk "Harnessing the Power of Machine Learning to Solve Global Problems" at Materials Science for Global Development -- Health, Energy, and Environment: An SMD Symposium in Honor of Wole Soboyejo: Materials for Global Development - Metal, TMS 2024.
Prof. Rodica Neamtu was invited to give a talk followed by collaborative research and teaching conversations at Sorbonne, Universite Paris de Cite hosted by Data Intelligence Institute de Paris, an IdEx-funded (Initiative of Excellence) interdisciplinary institute that includes the University Sorbonne Paris Nord, the Universite Paris Cite, Sciences Po university, and the French Institute for Demographic Studies (INED). Topics included AI at the crossroads of research and teaching, using AI to solve global problems, predictability in the age of AI, April 2024.
Prof Rodica Neamtu was invited for a talk and research meetings at EMPA Research Institute in Zurich on the topic of “Using Machine Learning to Solve Problems in Materials Science”, June 2024.
Over the summer, Prof Rodica Neamtu and the PASS-CS team welcomed the first cohort of an NSF-funded program called Creating a Path to Achieving Success and Sense of Belonging in Computer Science. This six-year program offers financial scholarships to Pell-grant students interested in studying computer science, while offering shared academic experience and research opportunities.
Prof Rundensteiner is featured in the article called: Training the workforce: Central Mass. Universities are infusing AI into curricula, as they navigate the ethical and technical issues, that appeared In Worcester Business Journal, July 22, 2024, by Matt Wright. Elke Rundensteiner has been one of the leaders at Worcester Polytechnic Institute who have implemented AI into the curriculum.
Prof Rundensteiner is featured in the article called: Meeting the Growing Demand for Expertise, WPI Establishes New Master’s Degree in Artificial Intelligence; Program Builds on Deep History of AI Expertise at WPI; Will Offer Cutting-Edge MS, BS/MS, and Graduate Certificate Options to Prepare Students for Fast-Growing Field. Dec 2023, WPI press release, written by Colleen Bamford Wamback.
Prof Rundensteiner is featured in the article called: WPI's new AI master's program to focus on ethics and innovation. In Spectrum News, Written BY DEVIN BATES. PUBLISHED DEC. 19, 2023.
Prof Rundensteiner is featured in the article called: The future is now - WPI to launch AI degree program this fall; WPI creates new degree program focused on Artificial Intelligence, in Gardner News, Worcester Telegram & Gazette, Written by Veer Mudambi, published Jan 7, 2024.
Prof Rundensteiner is featured in the story “Students Solve Real World Problems with Summer AI Research; Undergraduates Spend Summer at WPI Building Impactful Better AI Models”, WPI News, Neuron Expert News; published Aug. 27, 2024, https://www.wpi.edu/news/students-solve-real-world-problems-summer-ai-research (and YouTube).
Prof. Roee Shraga organized the HILDA (Human-In-the-Loop Data Analytics) workshop at the 2024 ACM SIGMOD/PODS.
Prof. Erin Solovey was the moderator for a panel on AI & Healthcare at the Women in Data Science Conference in Worcester, MA. March 13, 2024.
Prof. Erin Solovey was invited to give keynote talk at the Neureality Hackathon on Neurotech and Virtual Reality in New York, NY. Marh 8, 2024.
Prof. Erin Solovey was invited to speak on Human-AI Collaboration in Complex Environments: Advancing Interaction Modalities at the Dagstuhl Seminar on Human-AI Interaction for Work. November 6, 2023.
Prof. Erin Solovey served as the leader of the working group on “Managing Booming Enrollments without Damaging Diversity Efforts” at the CRA LEVEL UP Boston Workshop.
Prof. Erin Solovey was featured in an article in AI Business on October 12, 2023, titled “AI Helps Neuroscientists Understand Depression Better”.
Prof. Erin Solovey served on the organizing committee for the 2024 Symposium on Human-Computer Interaction and the Future of Work (CHI WORK’24) as the Student Consortium Co-chair. She will be the Technical Program Co-Chair for CHI WORK2025.
Prof. Erin Solovey served as an Associate Chair for the 2024 ACM SIGCHI Conference on Human Factors in Computing Systems (CHI). She is serving as the Subcommittee Co-Chair for the “Understanding People – Statistical and Quantitative Methods” subcommittee for CHI 2025.
Prof Xiaoyan (Sherry) Sun is featured in the article called “Top 5 Benefits of a Managed Detection and Response Service in 2024”, that appeared in Techopedia, May 14, 2024, by Linda Rosencrance.
Prof. Hanmeng Zhan organized the session “Quantum Information on Graphs” in the Women in Combinatorics Virtual Conference 2024, with co-organizer Xiaohong Zhang.
Prof. Hanmeng Zhan organized the session “Algebraic Graph Theory for Walking on Graphs” in CMS Winter Meeting, 2023, with co-organizers Sooyeong Kim, Hermie Monterde, Christopher Van Bommel, Xiaohong Zhang.
Prof. Hanmeng Zhan was invited to be a guest editor for the special issue “Numerical Analysis, Spectral Graph Theory, Orthogonal Polynomials, and Quantum Algorithms" of the journal Philosophical Transactions A.
Prof. Hanmeng Zhan was invited to give a talk “Epsilon-Uniform Mixing on Strongly Regular Graphs via Coined Quantum Walks” in 05C50 Online, University of Manitoba, Winnipeg, MB, Canada, September 13, 2024.
Prof. Hanmeng Zhan was invited to give a talk “Generating Quantum Uniform Mixing in Association Schemes” in CMS Summer Meeting, University of Saskatchewan, Saskatoon, SK, Canada, May 31 - June 3, 2024.
Prof. Hanmeng Zhan was invited to give a talk “Discrete Quantum Walks in Schemes” in AMS Sectional Meeting, University of Wisconsin-Milwaukee, Milwaukee, WI, United States, April 20 - 21, 2024.
Prof. Hanmeng Zhan was invited to give a talk “Quantum Walks: from Continuous to Discrete” in Godsil75, University of Waterloo, Waterloo, ON, Canada, March 15 - 17, 2024.
Prof. Hanmeng Zhan was invited to give a talk “Strongly Cospectral Vertices and Their Phantom Mates” in Joint Mathematics Meetings, Moscone Center, San Francisco, CA, United States, January 3 - 6, 2024.
Prof. Hanmeng Zhan was invited to give a talk “Quantum Search: An Averaging Perspective” in Joint Mathematics Meetings, Moscone Center, San Francisco, CA, United States, January 3 - 6, 2024.
Prof. Hanmeng Zhan was invited to give a talk “Spectra of Line Digraphs and Their Applications” in CMS Winter Meeting, Montreal, QC, Canada, December 1 - 4, 2023.
Prof. Hanmeng Zhan was invited to give a talk “How Graph Spectra Determine the Behavior of Discrete Quantum Walks” in 10th International Workshop of Quantum Simulation and Quantum Walks, Tsukuba International Congress Center, Tsukuba, Japan, November 10 - 12, 2023.
Prof. Hanmeng Zhan was invited to give a talk “On the second largest eigenvalue of a tree” in On-line Combinatorics Seminar, University of Wisconsin-Madison, Madison, WI, October 23, 2023.

Student News: 

Ph.D. Students – Graduated: 

Ashish Gurung graduated in August 2023 from the Computer Science PhD Program. In the Fall of 2023, Ashish began a postdoctoral fellowship with Vincent Aleven and Ken Koedinger at Carnegie Mellon University. Dr. Gurung was advised by Prof. Neil Heffernan.
Yunsen Lei graduated in May 2024 and began a postdoctoral fellowship at George Washington University. Dr. Lei was advised by Prof. Craig Shue.
Xiwen Lu graduated in August 2023 from the Learning Sciences & Technology PhD Program. Xiwen completed her PhD as a part-time student while working as a full-time Chinese teacher at Brandeis University. She continues to teach at Brandeis and serves as the Director of the Chinese Language Program. Dr. Lu was advised by Prof. Neil Heffernan.
Hamid Mansoor, who received his PhD in the WPI Computer Science Department in 2022, is now a tenure track assistant professor in the Computer Science Department, University of Manitoba, Canada. Dr. Mansoor was advised by Prof. Emmanuel Agu and Prof. Elke Rundensteiner. https://umanitoba.ca/science/directory/computer-science/hamid-mansoor
Yiyang Zhao graduated in June 2024 from the Computer Science Department and joined Meta as a research scientist. Dr. Zhao was advised by Prof. Tian Guo.