PeopleofSuperintelligence

Researcher

Bei Yu

Bei Yu is a computer science professor whose machine-learning work spans electronic design automation, computer vision and hardware-efficient language-model inference. He earned an M.S. in computer science at Tsinghua in 2010, completed a Ph.D. in electrical and computer engineering at UT Austin in 2014, and held a postdoctoral appointment in its Design Automation group from August 2014 to July 2015. His papers include EPIC, a framework for machine-learning and pattern-matching hotspot detection, a CNN-based mask-optimization framework, and HAPE, a hardware-aware method for pruning large language models. In July 2024, he was named to the RGC Research Fellow Scheme for VLSI mask optimization; as of October 2026, he is an assistant dean at CUHK.

Works
578

Publication numbers from OpenAlex, as of 22 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.

Timeline

  1. 2010–2014

    Tsinghua and Texas degrees

    He earns an M.S. in computer science at Tsinghua in 2010 and completes a Ph.D. in electrical and computer engineering at the University of Texas at Austin in 2014.

  2. 2012

    An IBM PhD Fellowship

    As a UT ECE graduate student, he receives the 2012 IBM PhD Fellowship.

  3. 2014

    EPIC combines hotspot detectors

    In 2014, he coauthors EPIC, a framework that combines machine-learning and pattern-matching methods to detect integrated-circuit manufacturing hotspots.

  4. 2014–2015

    Postdoctoral work at UTDA

    He works as a postdoctoral researcher in UT Austin's Design Automation group from August 2014 to July 2015.

  5. 2020

    Deep learning for mask optimization

    In 2020, he coauthors a convolutional-neural-network framework that predicts layout printability for simultaneous layout decomposition and mask optimization.

  6. July 2024

    A research fellowship for VLSI AI

    In July 2024, he is named to the Research Grants Council's Research Fellow Scheme for a project on machine-learning-driven VLSI mask optimization.

  7. July 2025

    HAPE prunes language models

    In July 2025, he coauthors HAPE, a hardware-aware post-training pruning framework for efficient large language model inference on hardware and edge devices.

  8. As of October 2026

    Professor and assistant dean

    As of October 2026, he is a professor in CUHK's Department of Computer Science and Engineering and assistant dean (Mainland Affairs) in its Faculty of Engineering. His research applies machine learning to VLSI computer-aided design and computer vision.

Career

  1. NowChinese University of Hong KongProfessor
  2. 2014–2015University of Texas at AustinPostdoctoral researcher

Education

  1. 2014University of Texas at AustinPh.D. in electrical and computer engineering
  2. 2010Tsinghua UniversityM.S. in computer science

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Chinese University of Hong Kong. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes Chinese University of Hong Kong. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  3. The United States employs an estimated 48% of people shaping AIIncludes Chinese University of Hong Kong. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Chinese University of Hong Kong. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Bei Yu yet. Send us a free-licensed photo.

  1. Bei YU - The Chinese University of Hong Kong research.cuhk.edu.hk. Checked 20 October 2026.
  2. UT ECE Graduate Student Bei Yu Receives 2012 IBM PhD Fellowship | Texas ECE - Electrical & Computer Engineering at UT Austin ece.utexas.edu. Checked 20 October 2026.
  3. [1402.2904] EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation arxiv.org. Checked 20 October 2026.
  4. UTDA - Univerity of Texas Design Automation cerc.utexas.edu. Checked 20 October 2026.
  5. Deep learning-driven simultaneous layout decomposition and mask optimization - The Chinese University of Hong Kong research.cuhk.edu.hk. Checked 20 October 2026.
  6. Four CUHK scholars named RGC Senior Research Fellows and Research Fellows | CUHK Communications and Public Relations Office cpr.cuhk.edu.hk. Checked 20 October 2026.
  7. HAPE: Hardware-Aware LLM Pruning for Efficient On-Device Inference Optimization - The Chinese University of Hong Kong research.cuhk.edu.hk. Checked 20 October 2026.
  8. Bei Yu@CUHK-CSE cse.cuhk.edu.hk. Checked 20 October 2026.