Team

🧑‍🔬 Principal Investigator

Huixin Zhan, Ph.D.

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.

🎓 Join the Lab!

We are currently recruiting for Fall 2026 and welcome inquiries from enthusiastic researchers and students who are passionate about AI, biomedicine, and interdisciplinary discovery.

🧑‍🎓 Prospective Ph.D. Students

Apply to the Ph.D. Program in Computer Science at New Mexico Tech. Positions in the lab are fully funded, including tuition support, stipend, and opportunities for research assistantships and immersive research experience with advanced AI technologies. If you are interested in joining, feel free to reach out via email to discuss potential research directions.

🧑‍🎓 Prospective Master’s Students

Master’s thesis students are also welcome to join the lab! Our positions are fully funded, with support via teaching assistantships or research assistantships, and provide exposure to cutting-edge interdisciplinary work in machine learning and biomedicine. To express interest, please email your CV and a brief description of your research interests.

🧑‍💼 Postdoctoral Researchers

The lab currently does not have dedicated funding for postdocs. However, if you have external funding or are interested in applying for a fellowship together, please don’t hesitate to get in touch.

👩‍🔬 Undergraduate Students

Funded research assistant positions will become available starting Fall 2025, ideal for students seeking research experience in AI, medicine, and robotics. Mentored projects can lead to co-authorship opportunities.
Stay tuned or email to express early interest.

👥 Current Team Members

🧑‍🎓 Ph.D. Students

Rakibul Islam
Hemanth Reddy Madduri

🧑‍🎓 Master’s Students

Ethan Peterson

🧑‍🎓 Undergraduate Students

Long Nguyen
Clovis Barbour

🎓 Past Students

I mentored the following students on various research projects:

Liyuan Gao (with Victor S. Sheng) – Ph.D. student: Worked on Explainable AI and Neuro-symbolic AI, resulting in two first-author conference papers and one second-author paper.
Zekarias Setotaw (with Victor S. Sheng) – Master’s student: Completed a project on Compression of Semantic Graphs for Graph-based Abstractive Summarization.
Siddhartha Ireddy (with Victor S. Sheng) – Master’s student: Led a project on Abstractive Text Summarization via Stacked LSTM, which resulted in a first-author conference paper.
Madhuri Gangadharan (with Victor S. Sheng) – Master’s student: Completed a project on Opinion Summarization Techniques for Social Media.
Apoorva Tyagi (with Victor S. Sheng) – Master’s student: Completed research on Privacy-preserving Algorithms.
Himaja Reddy Thatiparthi (with Victor S. Sheng) – Master’s student: Conducted research on Privacy-Preserving Text Representations for Medical Records.
Fei Zhou (with Victor S. Sheng) – Master’s student: Worked on Ensemble Summarization Models for CoronaNet, resulting in a second-author conference paper and a completed Master’s thesis.

🤝 Collaborators

Jun Zheng, Ph.D.

Professor and Chair, Computer Science & Engineering, New Mexico Tech

Dr. Jun Zheng specializes in AI/ML, cybersecurity, cyber-physical systems, and biomedical signal and image processing. Huixin collaborates with him on building intelligent assistive robotic platforms that leverage AI for rehabilitation and human-in-the-loop care delivery.

Lorie Liebrock, Ph.D.

Director, New Mexico Cybersecurity Center of Excellence (MOCCoE)
Professor, Computer Science, New Mexico Tech

Dr. Lorie Liebrock is the director of MOCCoE and brings expertise in trustworthy AI and secure computing. Huixin collaborates with her on developing adversarially robust biomedical foundation models to ensure secure and generalizable AI for health applications.

Jason H. Moore, Ph.D., FACMI, FIAHSI, FASA

Chair, Department of Computational Biomedicine, Cedars-Sinai Medical Center

Dr. Jason H. Moore is the Chair of the Department of Computational Biomedicine at Cedars-Sinai Medical Center and a pioneer in translational bioinformatics and machine learning. Huixin collaborates with him on agentic AI systems for scientific reasoning, knowledge discovery, and clinical translation. The joint work bridges human-centered AI design with biomedical applications, aiming to develop intelligent, ethical, and adaptive systems that improve quality of life and independence for vulnerable groups.

Julia (Wei) Cui, Ph.D.

Julia Cui is an Assistant Professor of Business Communication at the Leeds School of Business, University of Colorado Boulder. She investigates the intersections of communication, media, technology, and business practices.

She holds a Ph.D. in Media and Communication from Texas Tech University, an M.S. in Mass Communication from San Jose State University, and a B.A. in Communication and Journalism from the University of Utah. Dr. Cui’s interdisciplinary training informs her expertise in interpersonal, intercultural, and mass communication, as well as business communication pedagogy and practice. In addition to her academic credentials, she is also a trained vocalist, which enriches her appreciation for the expressive and performative dimensions of human interaction. Dr. Cui’s current research explores human-machine communication and AI-human interaction across culturally diverse business environments. She examines how emerging technologies—such as large language models and AI-driven communication platforms—are reshaping leadership discourse, cross-cultural collaboration, and organizational resilience. Her work also investigates how individuals from diverse cultural backgrounds interpret meaning, establish trust, and build relationships through AI-mediated communication, raising important implications for ethical practice and business effectiveness.

Yifan Wang, Ph.D.

Yifan Wang is a faculty member at Texas Tech University with expertise in applied mathematics and scientific computing. Huixin collaborates with him on applying diffusion models for solving PDEs and generating scientific data. Their joint research explores integrating deep generative models into physics-informed learning frameworks.

Yufei Wu, OTD, OTR/L

Dr. Yufei Wu is a clinical occupational therapist at Cedars-Sinai’s Outpatient Neurological Rehabilitation Center. As a licensed OTD, she brings deep clinical insights into neurorehabilitation. Huixin collaborates with her on research involving agentic AI and rehabilitation robotics for stroke and neurological recovery.

Zhong Chen, Ph.D.

Zhong Chen is a faculty member at Southern Illinois University, focusing on scalable data mining and big streaming data algorithms. He collaborates with Huixin on developing, analyzing, and evaluating large-scale streaming algorithms to support high-throughput scientific discovery from real-time biomedical signals and systems.

Xi Li

Xi is a Research Data Scientist at Cedars-Sinai Medical Center, specializing in databases, graph analytics, and clinical data science. Huixin collaborates with her on research projects focused on knowledge graphs and digital twins.

🐾 Lab Pets

Zhupi

Title: Unity Game Supervisor

Zhupi is the lab's early riser and keyboard critic. Frequently spotted during Unity debugging sessions, she ensures no script is left unchecked.