CV

Education

• M.S. in Computational Biology and Quantitative Genetics, Harvard T.H. Chan School of Public Health, 2023
• B.S. in Computer Science, Wake Forest University, 2021
• B.S. in Biology, Wake Forest University, 2021

Work experience

• Fall 2022 - Present: Graduate Research Assistant -> Research Associate
  • Harvard Medical School
  • Type: Graduate Student -> Full-time
  • Duties includes:
    • Designed a novel LLM-agent-based antibiotic discovery pipeline incorporating inhibition prediction models, pharmacokinetics property prediction models, molecule generation models, and a molecular optimization algorithm to identify molecules with high antibiotic potential against Mycobacterium tuberculosis (M.tb).
    • Benchmarked state-of-the-art molecule property prediction models including Graph Neural Networks, Equivariant Neural Networks, and Transformers on M.tb inhibition prediction and constructed a conditional Equivariant Diffusion Generative model for generating M.tb inhibitory molecules.
  • Supervisor: Maha R. Farhat
• Fall 2024 - Present: Research Associate
  • Harvard Pilgrim Health Inc.
  • Type: Part-time
  • Duties included:
    • Constructed a conditional logistic regression model and an XGBoost model to predict hospitalization-onset infection risk using Electronic Health Record (EHR) data from Mass General Brigham.
    • Investigated the impact of hospital environmental factors, including colonization pressure and prior antibiotic exposure, on the risk of hospitalization-onset infections for 12 drug-susceptible and drug-resistant organisms.
  • Supervisor: Sanjat Kanjilal
• Fall 2023 - Fall 2024: Research Associate
  • Harvard Business School
  • Type: Part-time
  • Duties included:
    • Developed a novel early-stage pandemic forecasting model that integrates deep learning with traditional compartmental models, leveraging historical pandemic data to achieve state-of-the-art performance in early-stage forecasting tasks.
    • Created a comprehensive meta-dataset of past pandemic outbreaks, including time series case data for COVID-19, Ebola, SARS, Dengue Fever, Monkeypox, Influenza, Zika Virus, and Chikungunya. This dataset supports future research in areas such as pandemic comparison and transfer learning for pandemic forecasting.
  • Supervisor: Michael Lingzhi Li
• Summer 2015: Machine Learning Summer Intern
  • Philips Healthcare North America
  • Duties included:
    • Established the first joint evaluation pipeline for pairwise Clinical Decision Support (CDS) algorithm comparison at Philips CDS Team including cohort definition, model inputs extraction, model training, and model co-performance evaluation, enabled the pairwise comparison between any two CDS algorithm that has been published or will be published in Philips on EHR data.

Skills

• Machine Learning / Deep Learning Modeling
• Drug Discovery
• Biomedical Informatics
• Clinical Research
• System Biology
• Major Programming Languages - Python, C++, R, SQL

Publications

Hospital unit colonization pressure and nosocomial acquisition of drug susceptible and drug resistant pathogens

Sagers, L., Wei, Z., McKenna, C., Chan, C., Agan, A. A., Pak, R., Rhee, C., Klompas, M., & Kanjilal, S. (n.d.). Hospital unit colonization pressure and nosocomial acquisition of drug susceptible and drug resistant pathogens.

Fleming: An AI Agent for Antibiotic Discovery in Mycobacterium tuberculosis

Wei, Z., Ektefaie, Y., Zhou, A., Negatu, D., Aldridge, B., Dick, T., Skarlinski, M., White, A. D., Rodriques, S., Krieger, I., Sacchettini, J., & Zitnik, M. (n.d.). Fleming: An AI Agent for Antibiotic Discovery in Mycobacterium tuberculosis.

HG-DCM: History Guided Deep Compartmental Model for Early Stage Pandemic Forecasting

Wei, Z., & Li, M. L. (2024). HG-DCM: History Guided Deep Compartmental Model for Early Stage Pandemic Forecasting. https://doi.org/10.1101/2024.11.18.24317469

Analyzing the spatiotemporal interaction and propagation of ATN biomarkers in Alzheimer’s disease using longitudinal neuroimaging data.

Q. Liu, D. Yang, J. Zhang, Z. Wei, G. Wu and M. Chen, "Analyzing The Spatiotemporal Interaction And Propagation Of Atn Biomarkers In Alzheimer’s Disease Using Longitudinal Neuroimaging Data," 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), Nice, France, 2021, pp. 126-129, doi: 10.1109/ISBI48211.2021.9434021.

Talks

Fleming: An AI Agent for Antibiotic Discovery in Mycobacterium tuberculosis

May 22, 2025

Oral Presentation at TB Drug Accelerator (TBDA), Boston, Massachusetts

Deep learning for antibiotic discovery in Mycobacterium Tuberculosis.

December 08, 2023

Poster Presentation at Boston Area Antimicrobial Resistance Network Meeting, Boston, Massachusetts

Deep learning for antibiotic discovery in Mycobacterium Tuberculosis.

June 12, 2023

Poster Presentation at Boston Bacterial Meeting, Boston, Massachusetts

Teaching