PhD in ECE at Purdue, 2024
Interests
Machine learning, optimization, computer engineering, device design
Interim CEO of Zephram
Santa Barbara, CA
Research site
Blake Anthony Wilson
Co-founder & interim CEO, Zephram · Oxford, UK
I am a computer engineer often working in algorithmic optimization and machine learning, with a focus on physics-informed AI, inverse-design and hardware-software co-design. My research is deeply-interdisciplinary, involving collaborations with physicists, engineers, and mathematicians from institutions such as Oxford, Cambridge, and Harvard to develop optimized software and models for complex scientific problems, having published in venues such as Applied Physics Reviews, Nature Partner Journal, American Controls Conference, CLEO, and APS. I have led cross-functional efforts at the intersection of AI and hardware—including founding the NanoML team at Purdue and serving as PGA team lead at the Quantum Science Center while developing ML-driven quantum circuit synthesis at QuEra. My industry experience spans research roles at Purdue SoCET, QuEra, and Quantinuum, and I currently serve as interim CEO of Zephram, where I focus on full-stack multi-agent systems and inference optimization for science at large. My proprietary work while at Quantinuum includes collaborations with NVIDIA and DeepMind-aligned teams for advancing RL and transformers for quantum circuit synthesis. My work has been supported by NASA Ames, AFRL, NSF, DOE, ORNL (OLCF), and AWS Braket. To date, I have mentored 200+ researchers through programs such as SURF, SoCET alongside my personal capacity. My students have won numerous best first-time researcher awards and poster awards at conferences and internal symposiums.
Collaborators & affiliations
In the news
- RAPTOR takes a bite out of global counterfeit semiconductor market
Purdue Research Foundation
Recent publications
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Deep learning in photonic device development: nuances and opportunities
Iyer, V., Wilson, B.A., Chen, Y., Kildishev, A.V., Shalaev, V.M., Boltasseva, A.
npj Nanophotonics 3, 5 (2026), 2026
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PearSAN: A Machine Learning Method for Inverse Design Using Pearson Correlated Surrogate Annealing
Bezick, M., Wilson, B.A., Iyer, V., Chen, Y., Shalaev, V.M., Kais, S., Kildishev, A.V., Lackey, B., Boltasseva, A.
Advanced Optical Materials (2026): e00249, 2026
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Machine-learning-assisted photonic device development: a multiscale approach from theory to characterization
Chen, Y., Montes McNeil, A., Park, T., Wilson, B., Iyer, V., Bezick, M., Choi, J., Ojha, R., Mahendran, P., Singh, D.K., Chitturi, G., Chen, P., Do, T., Kildishev, A., Shalaev, V., Moebius, M., Cai, W., Liu, Y., Boltasseva, A.
Nanophotonics, Vol. 14, Issue 23 (July 2025), 2025
Mentees
- Advay WellingPurdue SoCET and AMD
- Daksh Kumar SinghPurdue MS student under Boltasseva/Shalaev group
- Daria ShkelCornell PhD student
- David CzerwonkiPurdue PhD student and Senior Graduate Professional at EURO
- Geetika ChitturiPurdue NanoML and NanoX
- Lee DongeunVM
- Michael BezickIncoming PhD student at University of Maryland
- Rachel ZhangUniversity of Michigan Medical School
- Rohan MalavathuAmazon
- Rohan OjhaConway
- Sarthak TandonPurdue and AMD
- Seoyoung ChoKAIST
- Trang DoPurdue and ORNL
- Vaishnavi IyerPurdue PhD student at Boltasseva/Shalaev group



