Selected Student Publications
Year 2026
- The Road Less Seen: Segment Exploration for Weakly Supervised Video Anomaly Detection.
Anusha Acharya, Hitesh Sapkota, Qi Yu, Xumin Liu.
CVPR, 2026 - Class-Mixed Diffusion Augmentation for Shortcut-Breaking in Continual Learning.
Abhinab Acharya, Dayou Yu, Qi Yu, Xumin Liu
NeurIPS, 2026 - Mixing Expertise with Confidence: A Mixture of Experts Framework for Robust Multi-Modal Continual Learning.
Md Abdullah Al Forhad, Yuansheng Zhu, Abhinab Acharya, Xumin Liu, Qi Yu, Weishi Shi
ICML, 2026 - Do Privacy Policies Match with the Logs? An Empirical Study of Privacy Disclosure in Android Application Logs.
Z. Chen, L. J. Ahir, A. D. Suleiman, K. Yao, Y. Tang, W. Shang, D. Hou.
EASE, 2026 - Exploring LLMs’ Potential for Privacy Leakage Detection in Android App Logs: An Empirical Study.
Zhiyuan Chen, Vanessa Nava-Camal, Tiash Roy, Zhe Li, Yiming Tang, Xueling Zhang, Haibo Yang.
IEEE Software, 2026 - SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics.
Yicheng Zhu, Yang Chen, Tao Li, Zilin Bian
NeurIPS 2026 - A Large-Scale Social-Web Audit of AI-Generated-Text Detection Systems.
A. Dutta, U. Jaimini, U. Bhatt, S. S. Muthuselvam, A. Das, A. R. KhudaBukhsh.
ICWSM, 2026 - Auditing LLM Response to Harmful Stereotypes Targeting Mental Health Groups.
A. Dutta, R. Magu, S. Kim, S. Yoon, M. De Choudhury, A. R. KhudaBukhsh.
ACL, 2026 (Findings) - How Can You Tell if Your Large Language Model Could Be a Closet Antisemite? A Framework to Bias-Audit Large Language Models.
A. Dutta, R. Fayyazi, S. Yang, A. R. KhudaBukhsh.
AAAI, 2026 - What About the Scene with the Hitler Reference? HAUNT: A Framework to Probe LLMs' Self-consistency in Closed Domains via Adversarial Nudge.
A. Dutta, S. Dutta, R. Magu, S. Datta, M. De Choudhury, A. R. KhudaBukhsh.
ACL, 2026 (Main) - Categorizing Experience Management Problem Difficulty Using Graph Analysis.
Valentina Genoese-Zerbi, Justus Robertson, Rogelio E. Cardona-Rivera
IEEE Conference on Games (CoG) - Best Paper, 2026 - A Taste of Formal Methods for Computer Science Students using Jupyter Notebooks.
Z. Fitzsimmons, Z. R. Hassan, E. Hemaspaandra, C. R. Rivero.
SIGCSE TS, 2026 - The Complexity of Edge-Induced Greedy Subgraph Building Algorithms within P.
Zohair Raza Hassan, Edith Hemaspaandra
MFCS, 2026 - The Complexity of Ramsey Arrowing: A Computational Approach for Hardness Proofs.
Zohair Raza Hassan
In WG, 2026 - Beyond the Naked Eye: Empirical Study of How People Perceive, Detect, and Respond to AI-Manipulated Videos.
Fatima Kaniz, Y. Kelly Wu, and Ersin Uzun.
CHI Conference on Human Factors in Computing Systems, 2026 - Been There, Scanned That: Nostalgia-Driven Point Cloud Compression for Self-Driving Cars.
Ali Khalid, Jaiaid Mobin, Sumanth Rao Appala, Avinash Maurya, Stephany Berrio Perez, Fawad Ahmad.
ACM SenSys, 2026 - ARC: Accurate, Real-Time, and Scalable Multi-Vehicle Cooperative Perception.
K. N. Khan, F. Ahmad.
ACM/IEEE SenSys, 2026 - InteFL: Framework for AI-Assisted Design of Trustworthy and Efficient Federated Learning Applications.
D. Korobeinikov, R. Zatsarenko, S. Chuprov, A. Barea, L. Reznik.
IEEE WCCI, 2026 - Beyond Raw Bytes: Towards Large Malware Language Models.
Luke Kurlandski, Harel Berger, Yin Pan, and Matthew Wright.
NDSS, 2026 - Converge Faster, Talk Less: Hessian-Informed Federated Zeroth-Order Optimization.
Zhe Li, Bicheng Ying, Zidong Liu, Chaosheng Dong, Haibo Yang.
ICLR, 2026 - Learning Dynamics of Zeroth-Order Optimization: A Kernel Perspective.
Zhe Li, Bicheng Ying, Zidong Liu, Haibo Yang.
ICML, 2026 - An Efficient Architecture-Agnostic Quasi-Metric for Task Transferability.
E. Lima, M. Kwon.
AAAI, 2026 - DMin: Scalable Training Data Influence Estimation for Diffusion Models.
Huawei Lin, Yingjie Lao, Weijie Zhao.
CVPR, 2026 (Findings) - Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning.
Ziwen Liu, Huawei Lin, Yide Ran, Denghui Zhang, Jianwen Xie, Chuan Li, Weijie Zhao, Zhaozhuo Xu.
ICLR, 2026 - Understanding SAM's Robustness to Noisy Labels through Gradient Down-weighting.
Hoang-Chau Luong, Thuc Nguyen-Quang, Dat Ba Tran, Minh-Triet Tran.
AISTATS, 2026 - Why LoRA Fails to Forget: Regularized Low-Rank Adaptation Against Backdoors in Language Models.
Hoang-Chau Luong, Lingwei Chen.
ACL, 2026 (Findings) - InsCal: Calibrated Multi-Source Fully Test-Time Prompt Tuning for Object Detection.
Xiaofan Que, Dingrong Wang, Daniel Krutz, Qi Yu.
CVPR, 2026 - Do People Appropriately Rely on AI-Advice? An Analytical Review of HCI Research on Human-AI Decision-Making.
Muhammad Raees, Vassilis-Javed Khan, Ioanna Lykourentzou, Konstantinos Papangelis
ACM CHI, 2026 - Trust to Reliance: Measurement Constructs for Human-AI Appropriate Reliance.
Muhammad Raees, Konstantinos Papangelis
ACM CHI, 2026 (Extended Abstracts) - Calibrated Knowledge Aggregation in Bayesian Mixture-of-Experts for Continual VQA.
Mahsa Mozaffari, Hitesh Sapkota, Yu Kong, Xumin Liu, Qi Yu
ICML, 2026 - Knowledge Exchange with Confidence: Cost-Effective LLM Integration for Reliable and Efficient Visual Question Answering
Mahsa Mozaffari, Hitesh Sapkota, Xumin Liu, Qi Yu
ICLR, 2026 - Frequency Estimation of Correlated Multi-attribute Data under Local Differential Privacy.
Shafizur Rahman Seeam, Ye Zheng, Yidan Hu.
PETS, 2026 - PrivAR: Client-Side Privacy Framework for Real-Time Location-Based Augmented Reality.
Shafizur Rahman Seeam, Ye Zheng, Zhengxiong Li, Yidan Hu.
ICDCS, 2026 - ProReGen: Progressive Residual Generation under Attribute Correlations.
R. Shrestha, A. Gopi, C. Meisenzahl, B. Lekhak, L. Wang.
ICLR, 2026 - Adoption-Ready Project-Based Learning for Computing Education: The FORAP Framework and a Multi-Scale Project Portfolio.
Ahmad D. Suleiman, Jan DeWaters, David Shepherd, Turgay Korkmaz, Faraz Hussain, Yu Liu, Daqing Hou.
IEEE Frontiers in Education Conference, 2026. Accepted. - IF-Prune: Information-Flow Guided Token Pruning for Efficient Vision-Language Models.
Guohao Sun, Yufei Wang, Zhiqiang Tao, Jian Wang.
CVPR, 2026 - Information-Regularized Attention for Visual-Centric Reasoning.
Guohao Sun, Xiaofang Wang, Yash Patel, Mengchen Liu, Zhiqiang Tao, Praveen Krishnan.
ECCV, 2026 - Investigating Memetic Scheduling Strategies for Distributed Neuroevolution.
Diana Velychko, Travis Desell.
GECCO, 2026. - Meta-iLaD: Identifiable Latent Dynamics via Meta-Learning of Dynamics Environments.
Yubo Ye, Sweekar Piya, Xiajun Jiang, Linwei Wang
ICML, 2026. - AV-Play: Co-Designing VR Games to Study Audiovisual Integration in Children with ADHD.
Huadong Zhang, Nishant Joshi Dinesha, Ziming Li, Roshan L Peiris, Emily J Knight, Chao Peng
ACM CHI, 2026. - Performance-driven Foveated VR Rendering System for Large 3D Meshes.
Huadong Zhang, Chao Peng
Virtual Reality, Springer, 2026 - AUDAGENT: Automated Auditing of Privacy Policy Compliance in AI Agents.
Ye Zheng, Yimin Chen, Yidan Hu.
PETS, 2026 - Quantifying Classifier Utility under Local Differential Privacy.
Ye Zheng, Yidan Hu.
PETS, 2026 - TraCS: Trajectory Collection in Continuous Space under Local Differential Privacy.
Ye Zheng, Yidan Hu.
PETS, 2026
Year 2025
- Locality-Sensitive Indexing for Graph-Based Approximate Nearest Neighbor Search.
Jun Woo Chung, Huawei Lin, Weijie Zhao.
SIGIR, 2025 - All You Need Is S P A C E: When Jailbreaking Meets Bias Audit and Reveals What Lies Beneath the Guardrails (Student Abstract).
A. Dutta, A. Priyanshu, A. R. KhudaBukhsh.
AAAI, 2025 - Towards a Bipartisan Understanding of Peace and Vicarious Interactions.
A. Dutta, S. M. Sualeh Ali, U. Naseem, A. R. KhudaBukhsh.
IJCAI, 2025 (AI for Good) - On the parallelizability of approval-based committee rules.
Z. Fitzsimmons, Z. R. Hassan, Edith Hemaspaandra.
ECAI, 2025 - Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization.
Zhe Li, Bicheng Ying, Zidong Liu, Chaosheng Dong, Haibo Yang.
ICLR, 2025 - FAST: A Lightweight Mechanism Unleashing Arbitrary Client Participation in Federated Learning.
Zhe Li, Seyedsina Nabavirazavi, Bicheng Ying, Sitharama Iyengar, Haibo Yang.
IJCAI, 2025 - Exact and Linear Convergence for Federated Learning under Arbitrary Client Participation is Attainable.
Bicheng Ying, Zhe Li, Haibo Yang.
NeurIPS, 2025 - Exploring Large Language Model-driven Agents for Environment-aware Spatial Interactions and Conversations in Virtual Reality Role-play Scenarios.
Ziming Li, Huadong Zhang, Chao Peng, Roshan L Peiris
IEEE VR, 2025. - Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach.
Dandan Liang, Jianing Zhang, Evan Chen, Zhe Li, Rui Li, Haibo Yang.
NeurIPS, 2025 - ALinFiK: Learning to Approximate Linearized Future Influence Kernel for Scalable Third-Party LLM Data Valuation.
Yanzhou Pan, Huawei Lin, Yide Ran, Jiamin Chen, Xiaodong Yu, Weijie Zhao, Denghui Zhang, Zhaozhuo Xu.
NAACL, 2025 - Learning State-Based Node Representations from a Class Hierarchy for Fine-Grained Open-Set Detection.
Spandan Pyakurel, Qi Yu
ICML, 2025 - CaLMPhosKAN: Prediction of General Phosphorylation Sites in Proteins via Fusion of Codon-Aware Embeddings with Amino Acid-Aware Embeddings and Wavelet-based Kolmogorov–Arnold Network
Pratyush P., Carrier C., Pokharel S., Ismail H., Chaudhari M., KC, D.B.
Bioinformatics (Oxford), 2025. - Exploring Persuasive Engagement to Reduce Over-Reliance on AI-Assistance in a Customer Classification Case.
Muhammad Raees, Vassilis-Javed Khan, Konstantinos Papangelis
ACM UMAP, 2025 - UX Challenges in Implementing an Interactive B2B Customer Segmentation Tool.
Muhammad Raees, Vassilis-Javed Khan, Konstantinos Papangelis
ACM CHI, 2025 (Extended Abstracts) - GLEN: Generalized Focal Loss Ensemble of Low-Rank Networks for Calibrated Visual Question Answering.
Mahsa Mozaffari, Hitesh Sapkota, Qi Yu
AAAI, 2025 - PLM-DBPs: enhancing plant DNA-binding protein prediction by integrating sequence-based and structure-aware protein language models
Pokharel S., Barasa K., Pratyush P., KC, D.B.
Briefings in Bioinformatics, 2025. - Factors Impacting Faculty Adoption of Project-Based Learning in Computing Education: A Survey.
Ahmad D. Suleiman, Yiming Tang, Daqing Hou.
IEEE Frontiers in Education Conference, 2025. - Systematic Literature Review on Project-Based Learning in Computing Education.
Ahmad D. Suleiman, Daqing Hou, Yu Liu, Jan DeWaters, David C. Shepherd, Juliana G. De Souza.
ACM Transactions on Computing Education, 2025. - Latent Chain-of-Thought for Visual Reasoning.
Guohao Sun, Hang Hua, Jian Wang, Jiebo Luo, Sohail Dianat, Majid Rabbani, Raghuveer Rao, Zhiqiang Tao.
NeurIPS, 2025 - Structured Policy Optimization: Enhance Large Vision-Language Model via Self-Referenced Dialogue.
Guohao Sun, Can Qin, Yihao Feng, Zeyuan Chen, Ran Xu, Sohail Dianat, Majid Rabbani, Raghuveer Rao, Zhiqiang Tao.
ICCV, 2025 - Evaluating dry-electrode electroencephalography system for auditory neuroscience using speech-in-noise tasks.
Takeuchi, A., Shim, H., Choi, I., & Kim, S.
Proceedings of Meetings on Acoustics, 2025 - Evaluating dry-electrode electroencephalography system for auditory neuroscience using speech-in-noise tasks.
Takeuchi, A., Shim, H., Choi, I., & Kim, S.
The Journal of the Acoustical Society of America, 2025 - The role of self-construal in auditory spatial attention: Neural responses to masking noise in speech-in-noise tasks.
Takeuchi, A., Shim, H., Choi, I., & Kim, S.
The Journal of the Acoustical Society of America, 2025 - Harnessing Heterogeneous Statistical Strength for Personalized Federated Learning via Hierarchical Bayesian Inference.
Mahendra Singh Thapa, Rui Li.
ICML, 2025 - Conservative Evidential Exploration of Long-Term User Interest in Dynamic Recommender Systems.
Dingrong Wang, Krishna Prasad Neupane, Qi Yu.
ICLR, 2025 - Understanding and empowering intelligence analysts: User-centered design for deepfake detection tools.
Y. Kelly Wu, Saniat Javid Sohrawardi, Candice R. Gerstner, Matthew Wright.
CHI Conference on Human Factors in Computing Systems, 2025 - Lunar Roving Adventure: Stepping into Historic Apollo Missions in Virtual Reality.
Huadong Zhang, Lizhou Cao, Xuhang Yuan, Chao Peng
ACM SIGGRAPH '25: Immersive Pavilion, 2025. - UltraMeshRenderer: Efficient Structure and Management of GPU Out-of-core Memory for Real-time Rendering of Gigantic 3D Meshes.
Huadong Zhang, Lizhou Cao, Chao Peng
ACM SIGGRAPH '25: TOG Journal-Track, 2025. - Hierarchical Multi-Source Uncertainty Aggregation for Interactive Video Captioning.
Ervine Zheng, Qi Yu
AAAI, 2025 (Oral) - Locally Differentially Private Frequency Estimation via Joint Randomized Response.
Ye Zheng, Shafizur Rahman Seeam, Yidan Hu, Rui Zhang, Yanchao Zhang.
PETS, 2025 - Optimal Piecewise-based Mechanism for Collecting Bounded Numerical Data under Local Differential Privacy.
Ye Zheng, Sumita Mishra, Yidan Hu.
PETS, 2025
Year 2024
- Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection.
Abhinab Acharya, Dayou Yu, Qi Yu, Xumin Liu
ICML, 2024 - Service Composition Orchestration, Service Caching, and Computation Reuse at the Edge.
Carlos Barrios, Mohan Kumar
IEEE PerCom Workshops (PhD Forum), 2024 - Hierarchical Spherical Cross‐Parameterization for Deforming Characters.
Lizhou Cao, Chao Peng
Computer Graphics Forum (Eurographics), 2024. - Ellic's Exercise Camp: Engaging Children in Physical Activity Through Virtual Reality Gaming.
Lizhou Cao, Cielo Serna, Huadong Zhang, Chao Peng
ACM SIGGRAPH ’24: Immersive Pavilion, 2024. - Down the Toxicity Rabbit Hole: A Framework to Bias-Audit Large Language Models.
A. Dutta, A. Khorramrouz, S. Dutta, A. R. KhudaBukhsh.
IJCAI, 2024 (AI for Good) - Approaching Code Search for Python as a Translation Retrieval Problem with Dual Encoders.
Khan, M. M., & Yu, Z.
Empirical Software Engineering, 2024. - VRF: Vehicle Road-side Point Cloud Fusion
K. N. Khan, A. Khalid, Y. Turkar, K. Dantu, F. Ahmad.
ACM MobiSys, 2024 - Fundamental Convergence Analysis of Sharpness-Aware Minimization.
Pham Duy Khanh, Hoang-Chau Luong, Boris S. Mordukhovich, Dat Ba Tran.
NeurIPS, 2024 - Token-wise Influential Training Data Retrieval for Large Language Models.
Huawei Lin, Jikai Long, Zhaozuo Xu, Weijie Zhao.
ACL, 2024 - Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation
Krishna Prasad Neupane, Ervine Zheng, Qi Yu
NeurIPS, 2024 - Hierarchical Novelty Detection via Fine-Grained Evidence Allocation.
Spandan Pyakurel, Qi Yu
ICML, 2024 - Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models.
Deep Pandey, Spandan Pyakurel, Qi Yu
NeurIPS, 2024 - MULTICOLLAB-ASL: Towards Affective Computing for the Deaf Community.
Hayden Orr, Michel Peechatt, Cecilia Alm.
ACM ASSETS, 2024 - Integrating Embeddings from Multiple Protein Language Models to Improve Protein O-GlcNAc Site Prediction.
Pokharel P., Pratyush P., Ma J., KC, D.B.
Intelligent Systems for Molecular Biology, 2024 - LMCrot: an enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language model.
Pratyush P., Bahmani S., Pokharel S., Ismail H., KC, D.B.
Bioinformatics, Vol 40, Issue 5, 2024 - Optimal Transport of Diverse Unsupervised Tasks for Robust Learning from Noisy Few-Shot Data.
Xiaofan Que, Qi Yu
ECCV, 2024 - Dual-Level Curriculum Meta-Learning for Noisy Few-Shot Learning Tasks.
Xiaofan Que, Qi Yu
AAAI, 2024 - From explainable to interactive AI: A literature review on current trends in human-AI interaction.
Muhammad Raees, Inge Meijerink, Ioanna Lykourentzou, Vassilis-Javed Khan, Konstantinos Papangelis
International Journal of Human-Computer Studies, 2024. - Meta Evidential Transformer for Few-Shot Open-Set Recognition.
Hitesh Sapkota, Krishna Prasad Neupane, Qi Yu
ICML, 2024 - Dungeons & deepfakes: Using scenario-based role-play to study journalists' behavior towards using AI-based verification tools for video content.
Saniat Javid Sohrawardi, Y. Kelly Wu, Andrea Hickerson, Matthew Wright
CHI conference on human factors in computing systems, 2024 - Aligning Out-of-Distribution Web Images and Caption Semantics via Evidential Learning.
Guohao Sun, Yue Bai, Xueying Yang, Yi Fang, Yun Fu, Zhiqiang Tao.
The Web Conference (WWW), 2024 - SQ-LLaVA: Self-Questioning for Large Vision-Language Assistant.
Guohao Sun, Can Qin, Jiamian Wang, Zeyuan Chen, Ran Xu, Zhiqiang Tao.
ECCV 2024 - Prototypical Transformer As Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun, James Chenhao Liang, Zhiwen Cao, Qifan Wang, Qiang Guan, Sohail Dianat, Raghuveer Rao, Tong Geng, Zhiqiang Tao, Dongfang Liu.
ICML 2024, 2024. - STLLaVA-Med: Self-Training Large Language and Vision Assistant for Medical Question-Answering
Guohao Sun, Can Qin, Huazhu Fu, Linwei Wang, Zhiqiang Tao.
EMNLP 2024 - DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks.
M. Toloubidokhti, Y. Ye, R. Missel, X. Jiang, N. Kumar, R. Shrestha, L. Wang.
ICLR, 2024 - Artificial Intelligence Based Emergency Identification Computer System.
Velychko D., Osukhivska H., Palaniza Y., Lutsyk N., Sobaszek L.
Advances in Science and Technology Research Journal, 2024. - Adaptive Important Region Selection with Reinforced Hierarchical Searching for Dense Object Detection.
Dingrong Wang, Hitesh Sapkota, Qi Yu.
NeurIPS, 2024 - LIBR+: Improving Intraoperative Liver Registration by Learning the Residual of Biomechanics-Based Deformable Registration.
Dingrong Wang, Soheil Azadvar, Jon Heiselman, Xiajun Jiang, Michael Miga, Linwei Wang.
MICCAI, 2024 - Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness.
Dingrong Wang, Hitesh Sapkota, Zhiqiang Tao, Qi Yu.
KDD, 2024 - Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval.
Jiamian Wang, Guohao Sun, Pichao Wang, Dongfang Liu, Sohail Dianat, Majid Rabbani, Raghuveer Rao, Zhiqiang Tao.
CVPR, 2024 - The development of thermodynamically consistent and physics-informed equation-of-state model through machine learning
J Hinz, Dayou Yu, Deep Shankar Pandey, Hitesh Sapkota, Qi Yu, DI Mihaylov, VV Karasiev, SX Hu
APL Machine Learning. 2(2)2024 - Deep energy-pressure regression for a thermodynamically consistent EOS model
Dayou Yu, Deep Shankar Pandey, Joshua Hinz, Deyan I. Mihaylov, Valentin V. Karasiev, S. X. Hu, Qi Yu
Mach. Learn. Sci. Technol. 5(1): 15031 (2024) - Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity
Dayou Yu, Minghao Li, Weishi Shi, Qi Yu
NeurIPS, 2024