About me

I am a PhD candidate in the Electrical and Computer Engineering Department at the University of Texas at Austin.

My research is mainly focused on machine learning and its applications in VLSI CAD, autonomous system validation, and medical data analytics.

I am a member of UTDA research group working under the supervision of Prof. David Z. Pan. I am also a collaborator at Stroke Thrombectomy and Aneurysm Registry (STAR) as part of the STAR-AI team.


News

  • 09/2020: Our Work, “Re-examining VLSI Manufacturing and Yield through the Lens of Deep Learning”, will be presented in a special session @ ICCAD 2020.

  • 07/2020: My co-authored article “Automatic Selection of Structure Parameters of SOI LDMOS Using Bayesian Optimization” is accepted for publication in IEEE Electron Device Letters.

  • 07/2020: I presented my PhD work @ DAC 2020 PhD Forum.

  • 06/2020: My co-authored paper “TEMPO: Fast Mask Topography Effect Modeling with Deep Learning,” received Best Paper Award @ ACM International Symposium on Physical Design (ISPD), 2020

  • 05/2020: Our article “GAN-SRAF: Sub-Resolution Assist Feature Generation using Generative Adversarial Networks” is accepted for publication in IEEE Transactions on Computer Aided Design (TCAD).

  • 05/2020: My co-authored article “Critical Evaluation of Single Point Measurement-Based Quantitative Analyses in Forensic Breath Alcohol”, is accepted for publication in Forensic Science International: Reports.

  • 02/2020: Our recent work “Wafer Map Defect Patterns Classification using Deep Selective Learning” is accepted @ DAC'20!

Honors & Awards

  • 2020: Best Paper Award, International Symposium on Physical Design

  • 2019: Best Paper Award Nomination, Design Automation Conference (DAC)

  • 2014: High Distinction, American University of Beirut

Education

B.E. in Electrical and Computer Engineering

2014, GPA 4.0

M.S. in Electrical and Computer Engineering

2016, GPA 3.75

Ph.D. in Electrical and Computer Engineering

In progress

* Logo Design Credit Zahraa Alawieh* Header Photo Credit https://wallpapercave.com