About Me

My name is Huixin Zhan. I am a tenure-track Assistant Professor in the Department of Computer Science & Engineering at New Mexico Tech, where I lead the Zhan Lab. Previously, I was a Postdoctoral Scientist in the Department of Computational Biomedicine at Cedars-Sinai Medical Center, advised by Prof. Jason Moore. I obtained my Ph.D. in Computer Science from the Department of Computer Science at Texas Tech University, where I was advised by Prof. Victor Sheng. Previously, I had the pleasure to work with Zijun Frank Zhang, who is now at Natera. I earned my MS at the University of Texas at San Antonio, and my BEng at Nanjing University of Science and Technology.

I am broadly interested in machine learning, large language models, and graph neural networks, particularly their applications in text summarization, security, and privacy in both text mining and genomics data. My current research focuses on variant effect prediction using large language models, combining machine learning with genomics and biomedicine to develop predictive tools for cardiomyopathy and arrhythmia. Additionally, I explore the application of large language models to biomedical challenges, focusing on enhancing in-context learning and retrieval-augmented generation (RAG) for more effective knowledge graph-based reasoning.

Recent News

• [Jul, 2025]. Invited to serve as a PC member for NeurIPS-2025, ICML-2025, and AAAI-2026!
• [Mar, 2025]. "A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics" is published in Nature Machine Intelligence!
• [Mar, 2025]. Invited to serve as a reviewer for ACL-2025 and Nature Scientific Reports!
• [Jun, 2024]. Invited to serve as a PC member for AAAI-2025 and a reviewer for both Machine Learning and Autonomous Agents and Multi-Agent Systems!
• [Jan, 2024]. Invited to serve as a TPC member for IJCNN-2024, and a reviewer for ACM Transactions on Human-Robot Interaction!
• [Oct, 2023]. Invited to serve as a PC member for AAAI-2024, SDM-2024, and ICKG-2023!
• [Aug, 2023]. "Simplex2vec Backward: From Vectors Back to Simplicial Complex" is accepted by CIKM-2023!
• [Jul, 2023]. Invited to serve as a PC member for IEEE-SMC 2023 and HICSS-2024, as well as a subreviewer for CIKM-2023!
• [Jul, 2023]. Start a new job as a Postdoctoral Scientist at Cedars-Sinai!
• [Apr, 2023]. Invited to serve as a PC member for IJCAI-2023!
• [Dec, 2022]. Received the AAAI-23 Student Scholarship!
• [Dec, 2022]. Invited to serve as a Program Committee (PC) member for KDD-2023 Research Track!
• [Dec, 2022]. "Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks" has been selected as one of the finalists!
• [Nov, 2022]. "Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks" is accepted by AAAI-2023 Student Abstract and Poster Program!
• [Nov, 2022]. "Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes" is accepted by AAAI-2023 Doctoral Consortium!
• [Nov, 2022]. "Towards Fair and Selectively Privacy-Preserving Models Using Negative Multi-Task Learning" is accepted by AAAI-2023 Student Abstract and Poster Program!