Curriculum vitae

Academic CV

Yanjie Huang 黄䶮杰

I am an undergraduate researcher at Shanghai Jiao Tong University. My research lies at the intersection of generative AI and scientific discovery, with a focus on reasoning, alignment and molecular design.

Email me Download CV (PDF) GitHub Selected work

Education: SJTU · CS
Expected: June 2027
GPA: 3.98 / 4.30
Focus: AI & AI for Bio

Education

Shanghai Jiao Tong University

Bachelor of Computer Science and Technology

Sep 2023 – Jun 2027

GPA: 3.98 / 4.30 · Shanghai, China

Selected for the Bolè Plan (Elite Scientific Talent Program) as one of 30 students from 18,584 undergraduates, recognizing exceptional scientific potential and dedication.

Research Experience

Stanford University · Yejin Choi Group

Research Intern

Apr 2026 – Present

Mentored by Fang Wu & Yejin Choi.

Researching biological reasoning models, diffusion models, and post-training, with an emphasis on reasoning-centered molecular intelligence and training methods for scientific generative models.

Bio reasoning Diffusion Post-training AI for Science

Lin Gang Laboratory · AI Research Division

Research Intern · Shanghai

Sep 2025 – Present

Optimized Model Context Protocol design for the Origene scientific agent.
Worked on CAR-T stability and expression potency in mRNA and circRNA vaccine platforms.

Selected Research

RNA foundation model

EVA

Team leader and first author. Designed a 1.4B-parameter long-context MoE model for universal RNA modeling and controllable design.

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Multimodal protein model

PhaseFlow

Team leader and co-first author. Built a unified sequence-and-flow model for phase-separating protein understanding and design.

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Biological reasoning

Proteo-R1 / Proteo-R2

Developing chain-of-thought data and reasoning-centered methods for antibody, enzyme, and synthetic protein design.

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Diffusion post-training

What Matters in RL for Diffusion Models?

Studying noise-driven optimization signals and efficient trajectory selection for RL post-training of diffusion models.

View project →

Selected Publications

EVA: A Long-Context Generative Foundation Model Deciphers RNA Design Principles

Y. Huang*, G. Lv*, et al. · Nature Machine Intelligence, under revision · 2026

Preprint

PhaseFlow: A Unified Model for Multi-modal and Multi-scale Phase-separating Protein Understanding and Design

Y. Zhu*, Y. Huang*, et al. · Nature, submitted · 2026

Project page

ProteoCraft: Proposal-Verification Search for Protein Design with Diffusion Structure Predictors

F. Wu*, H. Lin*, B. Duan*, Y. Huang*, Y. Li*, et al. · Submitted to NeurIPS 2026

Project page

What Matters in RL for Diffusion Models? The Dominant Role of Noise

Research collaborator · Submitted to NeurIPS 2026

Project page

Capturing Natural Evolution in RNA Design via Genomic Foundation Models

Y. Huang, B. Zhang, et al. · Preprint · 2025

Preprint

Honors

SJTUBolè Plan
Elite Scientific Talent Program, Shanghai Jiao Tong University.
2022Bronze Medal
Chinese Mathematical Olympiad.
IMMCFirst Prize · International Round
The 7th International Mathematical Modeling Challenge.

Technical Focus

Models

MoE Transformers, multimodal Transformers, flow matching, mechanistic interpretability, scientific agents.

Training

Pretraining, SFT, LoRA, full-parameter tuning, DPO, GRPO, inference-time optimization, vLLM.

Scientific Computing

Large-scale data processing, SELEX/NGS pipelines, metagenomic mining, structure-based data mining.

Molecular Design

RNA design, CRISPR-Cas, phase-separating proteins, protein binders, CAR-T, and biological sequence-structure modeling.

Programming

Python, C++, Shell scripting, and LaTeX.

Languages

Chinese (native), English (TOEFL 99), Japanese (JLPT N3).

PhD & research opportunities

Let's talk about ambitious models for living systems.

I am happy to discuss research collaborations, PhD opportunities, and research engineering roles in AI for science.

huangyanjie@sjtu.edu.cn