Portrait of Yingheng Wang

Yingheng Wang

PhD Candidate, Computer Science · Cornell University

About

I am a 4th-year PhD candidate in Computer Science at Cornell University with Carla P. Gomes. I also work closely with Volodymyr Kuleshov and Christopher De Sa. I am affiliated with Cornell AI for Science Institute and AI-LEAF Institute. My research studies knowledge-centric AI with an emphasis on scientific reasoning. I was also student researcher at Amazon Grand Challenge, AWS AI Lab, Microsoft Research, and NEC Lab America, where my research led to impactful papers and patents on computational antibody design, protein language models, time-series foundation models, and efficient neural architectures. My research has been generously supported by Cornell Presidential Life Science Fellowship.

Research Interests

My research centers on developing knowledge-centric AI methods for scientific reasoning, which integrate physical and domain knowledge into modern AI techniques to improve their efficacy, efficiency, robustness, and interpretability. Current research topics include:

These thrusts converge to build AI systems that can reason, learn efficiently, and generalize robustly in complex real-world scenarios, ultimately advancing scientific discovery and innovation.

Selected Publications

Iterative Multi-Objective Policy Optimization for Antibody Sequence Design

Yingheng Wang, Can Chen, Karla-Luise Herpoldt, Sukanya Sasmal, Tommi Jaakkola, Marcus D. Collins, Shang Shang

NeurIPS 2026
(Under Review)

Deep Scientific Reasoning under Physical Constraints: Structure-Aware Spectrum Prediction for Electronic Density of States

Yingheng Wang, Tao Yu, Shufeng Kong, Francesco Ricci, John M. Gregoire, Carla P. Gomes

ICML 2026

HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization

Hongzheng Chen*, Yingheng Wang*, Yaohui Cai*, Hins Hu*, Jiajie Li*, Shirley Huang, Chenhui Deng, Rongjian Liang, Shufeng Kong, Haoxing Ren, Samitha Samaranayake, Carla P. Gomes, Zhiru Zhang

ICLR 2026

LC-PLM: Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers

Yingheng Wang, Zichen Wang, Gil Sadeh, Luca Zancato, Alessandro Achille, George Karypis, Huzefa Rangwala.

ICLR 2026
🏆 TMLR Featured Certificate

Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors

Yingheng Wang*, Top Wasu Piriyakulkij*, Volodymyr Kuleshov

AAAI 2025

InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models

Yingheng Wang, Yair Schiff, Aaron Gokaslan, Weishen Pan, Fei Wang, Christopher De Sa, Volodymyr Kuleshov

ICML 2023

See full list →

Services

Area Chair: NeurIPS (AI4Science).

Conference Reviewer: ICML, NeurIPS, ICLR, AAAI, AISTATS, UAI, CVPR, ICCV, ECCV, COLM.

Journal Reviewer: IEEE Transactions on Knowledge and Data Engineering (TKDE), Bioinformatics, Journal of Biomedical Informatics (JBI), Smart Health, Acta Automatica Sinica.