I am a PhD candidate at Harvard University co-advised by Prof. Jia Liu and Prof. Xiao Wang. My research lies at the intersection of artificial intelligence and biology, focusing on stem cell engineering, brain-machine interfaces, and bio-inspired and agentic AI. I collaborate closely with the research groups of Prof. Na Li, Prof. Richard Lee, Prof. Juan Rene Alvarez Domínguez and Prof. Jie Ding.

Before beginning my doctoral studies, I worked in the tech industry with a focus on product development and marketing analytics at leading companies and startups. Looking ahead, my goal is to advance the integration of biological systems and AI, driving translational impact through technologies that bridge fundamental discovery and real-world application.

Academia

Publications and Preprints

Stem Cell Engineering

Liu, R.#, Ren, Z.#, Zhang, X.#, Li, Q., Wang, W., Lin, Z., Lee, R.T., Ding, J., Li, N.* and Liu, J.*, 2024. An AI-Cyborg System for Adaptive Intelligent Modulation of Organoid Maturation. bioRxiv, pp.2024-12.
Li, Q.#, Liu, R.#, Lin, Z.#, Zhang, X.#, Silva, I.G., Pollock, S.D., Alvarez-Dominguez, J.R.* and Liu, J.*, 2024. Cyborg islets: implanted flexible electronics reveal principles of human islet electrical maturation. bioRxiv, pp.2024-03.

Brain-Machine Interfaces

Liu, R., Zhang, X., Sheng, H. and Liu, J., 2024, December. In Vivo Neural Stimulation and Recording using Flexible Bioelectronics. In 2024 IEEE International Electron Devices Meeting (IEDM) (pp. 1-4). IEEE.
Zhao, S.#, Shen, H.#, Qin, S., Jiang, S., Tang, X., Lee, M., Zhang, X., Lee, J., Chen, J. and Liu, J., 2024. Realigning representational drift in mouse visual cortex by flexible brain-machine interfaces. bioRxiv, pp.2024-05.
Marin-Llobet, A., Manasanch, A., Sanchez-Manso, S., Tresserras, L., Zhang, X., Hua, Y., Zhao, H., Torao-Angosto, M., Sanchez-Vives, M.V. and Porta, L.D., 2025. Riemannian Geometry for the classification of brain states with intracortical brain-computer interfaces. arXiv preprint arXiv:2504.05534.

Bio-Inspired and Agentic AI

Du, J., Zhang, X., Shen, H., Xian, X., Wang, G., Zhang, J., Yang, Y., Li, N., Liu, J.* and Ding, J.*, 2024. Drift to Remember. arXiv preprint arXiv:2409.13997.
Aljovic, A.# Lin, Z.#, Wang, W., Zhang, X., Marin-Llobet, A., Liang, N., Canales, B., Lee, J., Baek, J., Liu, R., Li, C., Li, N., Liu, J., 2025, An autonomous AI agent for universal behavior analysis. bioRxiv, pp.2025-05.
Lin, Z.#, Wang, W.#, Marin-Llobet, A., Li, Q., Pollock, S.D., Sui, X., Almir Aljovic, Lee, J., Baek, J., Liang, N., Zhang, X., Wang, C.K., Huang, J., Liu, M., Gao, Z., Sheng, H., Du, J., Lee, S.J., Wang, B., He, Y., Ding, J., Wang, X., Alvarez-Dominguez, J.R.* and Liu, J.*, 2025. Spatial transcriptomics AI agent charts hPSC-pancreas maturation in vivo. bioRxiv, pp.2025-04.
Lin, Z.#, Marin-Llobet, A.#, Baek, J., He, Y., Lee, J., Wang, W., Zhang, X., Lee, A.J., Liang, N., Du, J., Ding, J., Li, N. and Liu. J., 2025. Spike sorting AI agent. bioRxiv, pp.2025-02.

Misc.

Tang, X.#, Zhang, J.#, He, Y.#, Zhang, X., Lin, Z., Partarrieu, S., Hanna, E.B., Ren, Z., Shen, H., Yang, Y., Wang, X., Li, N., Ding, J.* and Liu, J.*, 2023. Explainable multi-task learning for multi-modality biological data analysis. Nature communications, 14(1), p.2546.
Bu, T.#, Zhang, X.#, Mertz, C. and Dolan, J.M., 2021, September. Carla simulated data for rare road object detection. In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) (pp. 2794-2801). IEEE.

Talks

2025 Eric and Wendy Schmidt Center Biomedical Science and AI Symposium (Poster)
2025 National Science Foundation Workshop on Reinforcement Learning (Poster)
2024 National Institutes of Health BRAIN NeuroAI Workshop (Poster)
Fall 2024 BE131 Neuroengineering at Harvard University (Guest lecture)
Spring 2024 BE129 Introduction to Bioelectronics at Harvard University (Guest lecture)

Awards and Honors

The Eric and Wendy Schmidt Center Symposium: Biomedical Science and AI
- Poster Presentation Third Place
National Institutes of Health BRAIN NeuroAI Workshop
- Early-Career Scholar Honorarium
- Best Poster Award Runner-Up
National Science Foundation EFRI BEGIN OI Award
- Proposal Co-Author
Carnegie Mellon University
- University Honors
- Carnegie Institute of Technology Research Honors
- ECE Grace Hopper Conference Scholarship
IEEE-Eta Kappa Nu Honor Society Sigma Chapter
- Corresponding Secretary
- Elected Member

Education

Since 2021, Doctor of Philosophy, Engineering Sciences, Harvard University
2021-2024, Master of Science, Engineering Sciences, Harvard University
2019-2020, Master of Science, Electrical and Computer Engineering, Carnegie Mellon University
2014-2018, Bachelor of Science, Electrical and Computer Engineering, Carnegie Mellon University

Teaching

Teaching Fellow, Harvard University

Fall 2025, Neuroengineering
Fall 2024, Neuroengineering
Fall 2022, Systems Development for Computational Science

Teaching Assistant, Carnegie Mellon University

Fall 2020, Deep Reinforcement Learning
Spring 2020, Signals and Systems (Head TA)
Fall 2019, Signals and Systems
Spring 2018, Signals and Systems
Spring 2017, Fundamentals of Programming
Fall 2016, Signals and Systems
Spring 2016, Fundamentals of Programming
Fall 2015, Fundamentals of Programming
Summer 2015, Principles of Computing

Tutoring, Carnegie Mellon University

2015-2020, College Reading and Learning Association Certified Level 2 Advanced Tutor

Mentorship

2022-2024, First-Year Advisor, Harvard University
2020, Academic Peer Advisor, Carnegie Mellon University

Industry

Entrepreneurship

2017-2019, Talent Pool, Startup Co-Founder

Healthcare

Summer 2019, Guangdong Sanjiu Brain Hospital, Tech Intern

Product Development and Marketing

2021, JPMorgan Chase & Co. Software Engineer
2018-2019, Duolingo, Android Developer
Fall 2018, Expii, Engineer Intern
Summer 2018, Facebook (Now Meta), Software Engineer Intern
Summer 2017, Google, Software Engineer Intern
Summer 2016, Google, Engineering Practicum Intern