Can Jin
Ph.D. Student in Computer Science, Rutgers University

I’m a Computer Science Ph.D. student, starting in Fall 2024 at Rutgers University, New Brunswick, under the guidance of Professor Dimitris N. Metaxas. I hold both a Bachelor’s and a Master’s degree in Mathematics from the University of Science and Technology of China. Prior to my Ph.D., I spent two years as a Machine Learning Engineer at Meituan Dianping Corporation. My research interests include LLM reasoning/generalization/reliability, Efficient AI, and 3D/image/video/multimodal generation.
I am excited to announce that I will be joining Adobe Research as a Research Scientist Intern in Summer 2025.
I’m also open to collaborating on related projects. Please contact me via email if you share similar interests.
Research
🧠 Large Language Models
Reasoning | Generalization | Reliability
Developing advanced techniques to improve LLM capabilities, including:
- Training innovations: Supervised fine-tuning (SFT), reinforcement learning with human/AI feedback (RLHF/RLAIF), Direct Preference Optimization (DPO)
- Post-training refinement: Self-critique mechanisms, iterative self-refinement
- Reliability: Robustness, Harmlessness, Helpfulness
Recent progress: NeurIPS 2024, submitted to ICML 2025
⚡ Efficient AI
Computational Efficiency | Effectiveness
Exploring methods to improve the efficiency of ML models, including:
- Model compression via distillation/pruning
- Prompt (engineering) for task adaptation
Recent progress: AAAI 2025, ICLR 2025
🎨 Multimodal Generation
3D | Video | Image | Multimodal generation
Exploring methods to generate 3D, video, image, and multimodal content using generative models. This is an ongoing research direction.
Academic Services
Teaching
- 24Fall: CS210: Data Management for Data Science
- 25Spring: CS534: Computer Vision
Peer Review
- Reviewer: CVPR 2025, ICML 2024 Workshop, Alexandria Engineering Journal, Information Fusion, Pattern Recognition, Signal Processing