About

I recently graduated from Carnegie Mellon University in May 2026 with an M.S. in Computational Biology, where I worked with Prof. Carl Kingsford and Prof. Wei Wu. I am now a Software Engineer at Google.

My work sits at the intersection of production software engineering, machine learning, and computational biology. I am especially interested in building AI systems that are reliable, measurable, and useful in real workflows.

Before joining Google full-time, I was a Software Engineering Intern at Google, where I built an AI-powered accessibility validation system using Gemini and achieved >0.95 recall. My research background includes controllable mRNA sequence design, shortcut learning mitigation, protein design, and cancer genomics.

I received my B.S. in Bioinformatics from the ZJU-University of Edinburgh Joint Institute in 2024. My cancer genomics research at ZJU-Edinburgh resulted in a co-first author publication in Gut.

News

• [July 2026] Joined Google as a Software Engineer
• [May 2026] Graduated from Carnegie Mellon University with an M.S. in Computational Biology
• [Aug 2025] Started new research project on shortcut learning in NLP with Prof. Carl Kingsford at CMU
• [Jun-Aug 2025] Software Engineering Intern at Google - built AI-powered accessibility validation system using Gemini, achieving >0.95 recall
• [May 2025] Contributed to the ARCADE paper on controllable mRNA sequence design
• [Aug 2024] Co-first author paper published in Gut: MED12 loss sensitizes pancreatic cancer to immunotherapy

Focus Areas

Selected Publications

Models Know Their Shortcuts: Deployment-Time Shortcut Mitigation
Li J, Tang S, Kaynar G, Du S, Kingsford C. arXiv:2604.12277, 2026. [Paper]

CodonRL: Multi-Objective Codon Sequence Optimization Using Demonstration-Guided Reinforcement Learning
Du S, Kaynar G, Li J, You Z, Tang S, Kingsford C. bioRxiv, 2026. [Paper]

ARCADE: Controllable Codon Design from Foundation Models via Activation Engineering
Li J, Lai HS, Liang L, Du S, Tang S, Kingsford C. bioRxiv, 2025. [Paper]

MED12 loss activates endogenous retroelements to sensitise immunotherapy in pancreatic cancer
Tang Y*, Tang S*, Yang W, et al. Gut, 2024. [DOI] (*co-first author)

Research Experience

Carnegie Mellon University — Research Assistant (Aug 2025 – May 2026)
Advisors: Prof. Carl Kingsford
Developed LLM-based methods to mitigate shortcut learning in NLP models, improving inference accuracy from 0.80 to 0.94.

Carnegie Mellon University — Research Assistant (Dec 2024 – May 2025)
Advisor: Prof. Carl Kingsford
Contributed to ARCADE, a controllable mRNA sequence design framework. Implemented parallel computing for RNA MFE and CAI optimization across multiple species codon databases and developed MFE predictors leveraging secondary structure features.

University College London — Research Assistant (Jun – Sep 2023)
Advisor: Prof. Christine Orengo
Applied deep learning and protein language models (ESM, AlphaFold2) for enzyme design and protein function prediction. Incorporated the SAM optimizer and performed statistical analysis of training dynamics.

ZJU–Edinburgh Joint Institute — Research Assistant (Jun 2022 – Jun 2023)
Advisors: Dr. Chaochen Wang & Dr. Jing Xue
Performed integrative multi-omics analysis characterizing MED12’s role in histone regulation and immune evasion in pancreatic cancer, resulting in a co-first author publication in Gut.

Personal Interests

Outside of work, I enjoy astrophotography and travel photography with my Canon G7X Mark III.