About me

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I am a staff machine learning engineer at Synopsys, a global leader in electronic design automation and semiconductor intellectual property (IP). I received my doctoral degree in Electrical Engineering at University of Southern California (USC) in 2022, advised by Prof. Pierluigi Nuzzo. Prior to my Ph.D. degree, I received my BSEE from Nankai University in 2017, and MSEE from USC in 2019.

At Synopsys, I conduct research on artificial intelligence (AI) and machine learning (ML) algorithms specifically for chip design. My work focuses on developing and integrating AI and ML algorithms into DSO.ai, the industry’s first autonomous AI application for chip design. This work complements my Ph.D. research interests, which focus on hardware security solutions for IP protection against threats on the integrated circuit (IC) supply chain, including the design and formal analysis of circuit obfuscation methods to prevent IC reverse-engineering. You may find a list of my publications here.

I currently serve on the Technical Program Committee for prestigious conferences, including the Design Automation Conference (DAC) and IEEE International Symposium on Hardware Oriented Security and Trust (HOST). In addition, I am also an External Reviewer for leading IEEE journals, specifically the IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) and the IEEE Transactions on VLSI Systems (TVLSI).

Recent posts

First day of internship at Synopsys

Today marks the first day of my summer internship at Synopsys Looking forward to this experience and working with people with great minds in the next 12 ...

Selected as DAC 2020 Young Fellow

I feel excited to share the news that I have been selected as a Young Fellow at the Design Automation Conference (DAC) 2020. DAC is recognized as the pre...