Thanasin (Thomas) Bunnam
Memristor modelling.
Email: t.bunnam2@ncl.ac.uk
Supervisor
Project description
I am currently working on memristor modelling to include its temperature effect. It is the starting point of investigating temperature compensation. This is important in applications such as analog memory.
I am in a working group which is focusing on the Tsetlin machine, an alternative high-efficient machine learning approach. My role is to design and integrate a memory block into our hardware design for fabrication.
I am also a member of time-domain power-elastic perceptron for machine learning research. My role is to model our PWM perceptron hardware to implement a neural network to solve problems such as MNIST.
Publications
- Bunnam T, Soltan A, Sokolov D, Yakovlev A. Pulse controlled memristor-based delay element. In: 27th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS). 2017, Thessaloniki, Greece: IEEE.
- Bunnam T, Soltan A, Sokolov D, Yakovlev A. An Excitation Time Model for General-purpose Memristance Tuning Circuit. In: 2018 IEEE International Symposium on Circuits and Systems (ISCAS). 2018, Florence, Italy: IEEE.
- Bunnam T, Soltan A,Sokolov D,Maevsky O, Yakovlev A. Toward Designing Thermally-Aware Memristance Decoder. In: IEEE Transactions on Circuits and Systems I: Regular Papers 2019, 66(11), 4337-4347.
- Mileiko S,Bunnam T,Xia F,Shafik R,Yakovlev A, Das S. Neural Network Design for Energy-Autonomous AI Applications using Temporal Encoding. arXiv e-prints arxiv.org/abs/1910.07492, 15 October 2019.
Interests
- Memristor
- Memristive circuit
- Memristor temperature modelling
- Analog memory
- Delay element
- Machine learning
- Tsetlin machine
Qualifications
- B.Eng. (Computer Engineering), Mahidol University, Thailand, 2005.
- M.Eng. (Computer Engineering), Chulalongkorn University, Thailand, 2009.