Yifei Zhang

About Me

Welcome! I’m Yifei Zhang, a secondthird-year Ph.D. student in Computer Science at Emory University, where I have the fortune of working with Dr. Liang Zhao. Before this, I obtained my M.S. degree in Data Science from Columbia University and my B.E. degree in Engineering Mechanics from Dalian University of Technology. Additionally, I earned a Master of Engineering Management degree from Duke University.

My research focuses on Explainable AI (XAI) and Large Language Models (LLMs), with an emphasis on multimodal learning, model distillation, and evaluation methodologies. As a Ph.D. student at Emory University, I have contributed to multiple research projects and published in top-tier conferences, continuously pushing the boundaries of AI interpretability and efficiency.

I am actively seeking Research Scientist or Applied Scientist full-time roles for 2026. If you have any opportunities, feel free to reach out!

Research Interests

• Explainable AI (XAI): Multimodal Explanation-Guided Learning, Visual Explanation-Guided Learning
• Large Language Models (LLMs): Distillation, Multimodal LLMs, LLM Evaluation

News

• [Jan. 2025] I will rejoin Amazon as an Applied Scientist Intern in Boston for Summer 2025.
• [Sep. 2024] Taken on the role of Student Co-organizer for the Foundation Models for Biological Discoveries (FM4sBio) workshop at AAAI 2025.
• [Jul. 2024] One co-authored paper is accepted by CIKM 2024!
• [May. 2024] One first-author paper is accepted by Findings of ACL 2024, and one co-authored paper is accepted by KDD 2024!
• [May. 2024] I will join Amazon as a Research Scientist Intern at Boston in summer 2024!
• [Apr. 2024] One first-author paper Visual Attention Prompted Prediction and Learning is accepted by IJCAI 2024!
• [Apr. 2024] Taken on the role of Publicity Chair for the ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial’24)
• [Jan. 2024] Our survey paper Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models is available on Arxiv!
• [Dec. 2023] One co-author paper is accepted by SDM 2024!
• [Nov. 2023] Our work about Datasets and Benchmarks for Visual Explanation is available online!
• [Aug. 2023] Taken Reviewer Invitations for IEEE Transactions on Neural Networks and Learning Systems.
• [Jul. 2023] One first-author paper is accepted by ICCV 2023!
• [May. 2023] One co-first-author paper is accepted by KDD 2023!

Selected publications and preprints

Education Experience

	Emory University, 2022.08- Ph.D. in Computer Science
	Columbia University, 2020.09-2021.12 M.S. in Data Science
	Duke University, 2019.08-2020.05 Master of Engineering Management
	Dalian University of Technology, 2015.09-2019.06 B.E. in Engineering Mechanics (Excellence Program)

Internship Experience

	Amazon, 2024.06-2024.09 Research Scientist Intern
	Guotai Junan Securities, 2018.12-2019.03 Equity Research Intern

Services

Journal Reviewers

• ACM Transactions on Intelligent Systems and Technology
• IEEE Transactions on Big Data
• IEEE Transactions on Neural Networks and Learning Systems
• Journal of Applied Clinical Medical Physics

Conference Reviewers/Program Committee

• ICLR 2025
• CVPR 2025
• KDD 2025 Research Track
• KDD 2025 Datasets and Benchmarks Track
• ICCV 2025

Workshop Organizers

• Publicity Chair for 4th ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial’24)
• Student Co-organizer for the Foundation Models for Biological Discoveries (FM4sBio) workshop at AAAI 2025.

Awards

• KDD 2023 Student Travel Award
• DUTOAA Seagle Scholarship Award, DUTOAA Foundation
• Academic Excellence Scholarship Award, Dalian University of Technology
• Technological Innovation Scholarship Award, Dalian University of Technology

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