Olga Krestinskaya
Olga`s research is focusing on reconfigurable neural network implementation on CMOS-memristive hardware.
Biography
Olga Krestinskaya (Graduate Student Member, IEEE) is a Ph.D. candidate at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. Her research focuses on software–hardware co-design for in-memory computing (IMC) architectures and AI hardware, with a particular interest in hardware-aware neural architecture search (NAS) algorithms, memristor-based systems, neuromorphic computing, and mixed-signal IMC implementations. She has authored several high-impact works on analog memristive neural networks, mixed-signal circuit-level implementations of in-memory computing architectures, quantized neural networks, and brain-inspired algorithms, with a focus on developing energy-efficient and scalable IMC hardware for AI applications.
Olga is the recipient of the 2019 IEEE CASS Predoctoral Award, the 2025 Web of Talents STEM Award (1st place), and multiple KAUST Dean’s Awards. Her work was recognized with the Best Poster Award at the 2nd Nature Conference on Neuromorphic Computing (2024), and she was shortlisted for the prestigious Rising Stars Women in Engineering Workshop (Asian Deans’ Forum 2024).
Research Interests
Olga`s research area is neuromorphic and brain-inspired algorithms, circuits, and architectures. In particular, she is interested in memristor-based architectures for neural networks and neuro-inspired systems. Currently, Olga is focusing on analog circuit-level implementations of reconfigurable memristive neural network architecture and optimization of hyperparameters.
Awards and Distinctions
- Erasmus Student Mobility Scholarship, Erasmus, 2018
- 2019 IEEE CASS Pre-Doctoral Grants, IEEE Circuits and Systems Society (IEEE CASS), 2019
Education
- Master of Science (M.S.)
- Electrical and Electronics Engineering, Nazarbayev University, Kazakhstan, 2016
- Bachelor of Science (B.S.)
- Electrical and Electronics Engineering, Nazarbayev University, Kazakhstan, 2018
Selected Publications
- Automating Analog AI Chip Design with Genetic Search
O. Krestinskaya, K.N. Salama and A.P. James, Advanced Intelligent Systems, 2020, Memristive GAN in Analog.O. Krestinskaya, B.Choubey, and A.P. James, Scientific Reports. 2020 Apr 3;10(1):1-4. - Neuro-Memristive Circuits and Architectures for Edge Computing: A Review
O. Krestinskaya, A.P. James, and L. Chua IEEE Transactions on neural networks and learning systems. 2019 Mar 14;31(1):4-23. - Learning in Memristive Neural Network Architectures using Analog Backpropagation Circuits
O. Krestinskaya, K.N. Salama and A.P. James IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 66, no. 2, pp. 719-732, Feb.2019. - Who is the winner? Memristive-CMOS hybrid modules: CNN-LSTM versus HTM.
K. Smagulova, O. Krestinskaya and A.P. James IEEE Transactions on Biomedical Circuits and Systems. 2019 Nov 28;14(2):164-72. - Hierarchical temporal memory using memristor networks: A survey.
O. Krestinskaya, I.Dolzhikova and A.P. James IEEE Transactions on Emerging Topics in Computational Intelligence. 2018 Sep 24;2(5):380-95. - Hierarchical temporal memory features with memristor logic circuits for pattern recognition.
O. Krestinskaya, T. Ibrayev and A.P. James IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 2017 Aug 31;37(6):1143-56.
