Basic Information

• We currently have openings for truly outstanding and highly motivated PhD students, starting at Spring 2025 and Fall 2025 semesters. Incoming PhD students will be funded as Graduate Research Assistantship (GRA). Please fill in this Form
• Interested candidates for PhD opportunities are strongly encouraged to contact Dr. Gu by email before sending in applications. Please attach your CV, transcript, publications (if any) and clearly discuss your research interest and experiences.
• Self-funded visitors and interns are welcome to apply, and will be evaluated case by case. We are always open to working with ASU undergraduates and master students for projects. Please contact Dr. Gu by email and specify your interest and experience.

What we expect from good candidates?

• True enthusiasm for learning new things and in-depth investigation, devotion to research, commitment to rigorous academic integrity, being highly self-motivated, proactive towards challenges, and strong information acquisition and processing capabilities
• Two other important things that we look for: (1) a truly deep understanding of your problem of interest; (2) a solid background in coding, ML, hardware (arch), and mathematics. Our research is cross-disciplinary in nature and heavily involves linear algebra, optimization, ML/DL, coding, computer architecture, analog circuits, and physics (e.g., optics).

Professor Jiaqi Gu [Google Scholar] is currently Assistant Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. He received Ph.D. degree from the Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA, and B.E. degree in Microelectronic Science and Engineering from Fudan University, Shanghai, China in 2018.

Prof. Gu has broad research interests spanning from emerging hardware design for efficient computing (photonics, post-CMOS electronics, quantum), hardware-algorithm co-design, AI/ML algorithms, and electronic-photonic design automation.

Prof. Gu has received Best Paper Award at ASP-DAC 2020, selected as one out of 6 Best Paper Finalists at DAC 2020, won First Place at the ACM/SIGDA Student Research Competition (SRC) held at ICCAD 2020, received the Best Poster Award at NSF Workshop on Machine Learning Hardware 2020, won First Place at the ACM Student Research Competition Grand Finals 2021, received the Best Paper Award at IEEE TCAD 2021, won the Robert S. Hilbert Memorial Optical Design Competition 2022, and won Margarida Jacome Dissertation Prize at UT Austin ECE (2023).