Jingchen Sun （孙精辰） Ph.D. Student Department of Computer Science and Engineering University at Buffalo, State University of New York Email: jsun39@buffalo.edu

About Me

I am a Ph.D. student in Computer Science at University at Buffalo, State University of New York, fortunate to be supervised by Prof. Changyou Chen. Prior to this, I obtained my Master's degree from Zhejiang University and my Bachelor's degree from North China Electric Power University.

My research broadly focuses on Transfer Learning for Multimodal Large Language Models (LLMs), particularly on employing techniques such as prompt tuning, support set construction, and knowledge distillation to enhance their application in various downstream tasks, such as image classification, visual question answering (VQA), and multimodal retrieval.

Recently, I am exploring how to leverage reinforcement learning and on-policy distillation to enhance the reasoning capabilities of multimodal LLMs. If you are also interested in related topics and would like to collaborate, feel free to drop me an email!

I am on the job market and looking for a full-time industry opportunity in 2026 !

News [Update!]

• 05/13/2026: I was recognized as an ICML Silver Reviewer!
• 03/19/2026: One paper was accepted to CVPR Workshop 2026!
• 02/21/2026: One paper were accepted to CVPR 2026!
• 01/17/2026: One paper were accepted to ICASSP 2026!
• 11/07/2025: One paper were accepted to AAAI 2026!
• 12/20/2024: Two papers were accepted to ICASSP 2025!
• 10/28/2024: A paper was accepted to WACV 2025!
• 09/25/2024: A paper was accepted to NeurIPS 2024!
• 08/23/2024: I finished the intern at NEC Labs, great summer at Princeton !

Highlight Publications

• Beta-KD: Uncertainty-Aware Knowledge Distillation for Multimodal Large Language Models Jingchen Sun, Shaobo Han, Deep Patel, Wataru Kohno, Can Jin, Changyou Chen. We propose a novel uncertainty-aware knowledge distillation method, which can improve the performance of the student model by leveraging the uncertainty of the teacher model. CVPR 2026 Code PDF

• CLAP-S: Support Set-Based Adaption for Downstream Fiber-Optic Acoustic Recognition Jingchen Sun, Shaobo Han, Wataru Kohno, Changyou Chen. We introduce a support set–based adaptation approach to enhance domain adaptation performance in audio-language models. ICASSP 2025 Code PDF

• Craft: Cross-modal Aligned Features Improve Robustness of Prompt Tuning Jingchen Sun, Rohan Sharma, Vishnu Suresh Lokhande, Changyou Chen We propose a novel cross-modal feature alignment method that mitigates the overfitting issue in visual-language model prompt tuning across different domains. WACV 2025 Code PDF

• PIDNet: An Efficient Network for Dynamic Pedestrian Intrusion Detection Jingchen Sun, Jiming Chen, Tao Chen, Jiayuan Fan, Shibo He We propose a novel dynamic pedestrian intrusion detection network, which can efficiently detect the pedestrian intrusion in the video. ACM MM 2020 Code PDF

Internship

• 
  Bytedance
  Research Scientist Intern
  Bellevue, WA, May 2026 - August 2026
• 
  NEC Labs America
  Research Intern
  Princeton, NJ, June 2024 - Aug 2025
• 
  Nokia Bell Labs
  Applied AI Researcher Intern
  Murray Hill, NJ, June 2023 - Aug 2023

Conference Reviewrs

• ML Conference: NeurIPS 2024, 2025; ICLR 2025, 2026; ICML 2025, 2026; AISTATS 2025; IJCAI 2025; IJCNN 2025
• CV Conference: CVPR 2026; ICCV 2025; WACV 2025
• Audio Conference: ICASSP 2025, 2026

Journal Reviewrs

• Transactions on Machine Learning Research (TMLR): 2024, 2025, 2026
• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI): 2026

Teaching Asistant

• CSE 474/574: Introduction to Machine Learning (2024 Spring, 2022 Fall)
• CSE 676: Deep Learning (2022 Spring)