| Office | 549A Boyd Research and Education Center |
| jin.lu@uga.edu | |
| Google Scholar | Profile |
| CV | Current CV |
I am an Assistant Professor in the School of Computing at the University of Georgia and a Faculty Fellow in the Institute for Artificial Intelligence at UGA. My research develops rigorous, efficient, and deployable machine learning methods for real-world settings. I work on optimization for AI, foundation model adaptation, federated and distributed learning, multimodal sensing, and trustworthy AI systems for health, agriculture, and edge computing.
My group is especially interested in problems where theory, systems, and applications have to meet: efficient learning under resource constraints, robust and interpretable AI, and machine learning methods that can operate outside idealized lab environments.
Research Themes
- Optimization methods for AI, including convex and nonconvex optimization, derivative-free optimization, and bilevel optimization.
- Efficient adaptation of foundation models and LLMs, including zeroth-order methods, quantization-aware training, and memory-efficient fine-tuning.
- Federated, distributed, and on-device learning for heterogeneous and communication-constrained environments.
- Multimodal AI for health sensing, physiological signal understanding, precision agriculture, and Internet of Things systems.
Openings
- PhD applicants: apply through the UGA School of Computing PhD program and list me as a potential advisor.
- Master’s project applicants: use this project interest form.
- UGA undergraduates: students interested in research should build strong foundations in machine learning, algorithms, and mathematical optimization, then reach out with a transcript, CV, and a brief statement of interests.
Selected Highlights
- Recent work has appeared in venues including CVPR, ICCV, NeurIPS, EMNLP, MobiCom, SenSys, PerCom, ICCAD, GLSVLSI, and PAKDD.
- Current projects span optimization for foundation models, federated learning, multimodal medical AI, contactless health sensing, and AI for precision agriculture.
- Awarded projects include the CARE-TRAC collaboration and multiple University of Georgia internal research awards.
- I received the University of Georgia Student Career Success Influencer Award in 2024.
Recent News
- Oct 2026: “GlycoGLF: Measuring and Modeling Context-Dependent Opposing Labels in Glycan Disease” was accepted as a regular paper at IEEE BigData 2026.
- Oct 2026: Know-Your-Scene (KYS)-SLAM: Hierarchical Semantic-Motion Priors for Feature Matching in Stereo Visual SLAM was accepted to WACV 2027.
- Oct 2026: Online Skill Learning for Web Agents via State-Grounded Dynamic Retrieval was accepted to the NeurIPS 2026 TTCL Workshop.
- Oct 2026: LastAct: Trajectory-Guided Latest-Activity Localization for Real-Time Smart-Home Activity Recognition is now available in the ACM Digital Library (PACM IMWUT).
- Sep 2026: Two papers, Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs and DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition, were accepted to the NeurIPS 2026 main track.
- Sep 2026: I will serve as an Area Chair for ICLR 2027. My service also includes the AAAI 2027 program committee and reviewing for AISTATS 2027.
- Sep 2026: “Paraphrase-Induced Retrieval Instability: Systematic Measurement and the Limits of Inference-Time Mitigation” was accepted as an archival paper at UncertaiNLP 2026 at EMNLP. Accepted papers
- Sep 2026: Contra-Phy: Re-Introducing Boundary Awareness in Infrared Image Classification via Physics-Informed Contrastive Learning appeared in the ICPR 2026 International Workshops and Challenges proceedings.
- Aug 2026: “SCOPE: Stepwise Calibration of Reasoning Confidence with Outcome-Grounded Prefix Evidence” was accepted to the EMNLP 2026 main conference, and End-to-End On-Device Quantization-Aware Training for LLMs at Inference Cost was accepted to Findings of EMNLP 2026.
- Jun 2026: “Pecan-Agent: Closed-Loop Industrial Shelling with MLLM-Optimized Morphological Priors” was accepted to IROS 2026.
- Jun 2026: Our interdisciplinary team received a Rural Engagement Workshop Seed Grant.
- Mar 2026: Spring offering of CSCI/ARTI 8950 Machine Learning is underway, with continued emphasis on theory, implementation, and research readiness.
- Feb 2026: New papers accepted to CVPR 2026, PAKDD 2026, SenSys 2026, and PerCom 2026.
- Feb 2026: Our interdisciplinary project on AI-assisted breeding for anthracnose resistance in pepper received a UGA Institute for Artificial Intelligence seed grant. UGA announcement
- Jan 2026: Our CARE-TRAC collaboration received support through USC’s Clinical Trial Recruitment Lab for AI-enhanced rural Alzheimer’s research recruitment. Project
- 2025: Work accepted to ICCV, EMNLP, NeurIPS, ICCAD, and GLSVLSI, expanding our research in efficient LLM adaptation, contrastive learning, and machine unlearning.
- 2025: Continued growth in interdisciplinary collaborations across health, agriculture, AI systems, and scientific computing.
- 2024: Our work on proximal federated learning for BMI monitoring using commodity WiFi appeared at MobiCom 2024.
- 2024: I received the Student Career Success Influencer Award at UGA.
- Fall 2023: I joined the University of Georgia as an Assistant Professor in the School of Computing.
Read our latest research analysis with worked mathematics and a comic.
For a fuller overview, visit the Research, Teaching, Group, and Papers pages.