Office 549A Boyd Research and Education Center
Email 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 NIH-supported 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

  • 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.
  • 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.

For a fuller overview, visit the Research, Teaching, Group, and Papers pages.