https://scholar.google.com/citations?view_op=list_works&hl=en&hl=en&user=eKs-ZGQAAAAJ

https://github.com/AaronWhy

https://www.linkedin.com/in/hengyi-wang-86605b175/

https://x.com/HENGYIWANG24776

hengyi DOT wang AT rutgers DOT edu

Bio

I am Hengyi Wang (恒屹 王), Senior Applied Scientist at Microsoft AI working on scalable and efficient AI for ranking and search.

My work focuses on post-training and evaluation of large language models, with an emphasis on alignment, agentic systems, and scalable evaluation pipelines.

Previously collaborated with Microsoft Research, and have had the opportunity to collaborate with https://www.microsoft.com/en-us/research/people/akshayn/, https://www.microsoft.com/en-us/research/people/taganu/ on long-context multimodal evaluation (Multimodal Needle-in-a-Haystack), deploying and stress-testing foundation models through Azure OpenAI.

Computer Science PhD graduated at Rutgers University. My research explores trustworthy and interpretable multimodal foundation models. I graduated with a B.S. in computer science from Turing Honor Class, https://english.pku.edu.cn/. I am fortunate to be advised by http://www.wanghao.in/.

Research Interests

My research focuses on the intersection of probabilistic machine learning and AI safety. I am currently working on interpretability and evaluation in areas such as multimodal large language models and personalized recommendation systems. The aim of my research is to develop understandable and controllable Artificial General Intelligence systems, with a particular emphasis on interpretability and alignment for the benefit of humanity.

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