Roles and responsibilities
I am a Research Officer in the Data Science for Complex Systems team at NRC, Digital Technologies. As part of this role I occasionally manage R&D projects that include internal and/or external collaborators. Currenty, I'm the lead of the AI-assisted Photonic Component Design master project as part of the AI for Design program.
Current research and/or projects
- Machine Learning enhanced optimization methods for the design of nanophotonic components
- Active learning with complex objective functions
Research and/or project statements
I am primarily interested in advancing the machine learning state of the art to address problems in Physics and Engineering.
Design and optimization of complex structures (nano or macro) or processes (e.g. fabrication) still require a lot human effort despite the availability of relevant model/process simulators. Through its ability to “see” the patterns in data, machine learning can be effective in assisting with these tasks, potentially overhauling the overall structure/process design flow entirely.
Education
Ph.D. in Computer Science, McGill University, Canada, 2014.
M.Sc. (Hons.) in Computer Science, Tel Aviv University, Israel, 2008.
B.Sc. in Computer Science, Academic College of Tel Aviv – Yaffo, 2002.
Professional activities/interests
Recurrent program committee member of the following conferences: ICML, IJCAI, NeurIPS
Occassional reviewer for other conferences like ICRA, EWRL.
Awards
NSERC Postdoctoral Fellowship Award, 2014
Key publications
D Melati, Y Grinberg, S Janz, P Cheben, JH Schmid, A Sánchez-Postigo, ... , Mapping the global design space of nanophotonic components using machine learning pattern recognition. Nature Communications (2019). To appear.
Y Grinberg, TJ Perkins, Fully polynomial-time computation of maximum likelihood trajectories in Markov chains. Information Processing Letters 118, 53-57 (2017)
Y Grinberg, D Precup, M Gendreau, Optimizing energy production using policy search and predictive state representations. Advances in Neural Information Processing Systems, 2969-2977 (2014)
MM Fard, Y Grinberg, J Pineau, D Precup, Compressed least-squares regression on sparse spaces. Twenty-Sixth AAAI Conference on Artificial Intelligence (2012)
Previous work experience
Before joining NRC I was fortunate to have a postdoctoral fellowship position in Ottawa Hospital Research Institute, Perkins Lab.
Prior to my doctorate studies I held various system and software engineering roles in the industry and defense sector in Israel for 7 years.
