Next generation innovator pursuing the development of "intelligent" machines by reverse engineering the human neocortex and creating equivalent structures in silicon
Independent machine learning researcher currently based in Irvine, California, specializing in neuromorphic computing and AI accelerator hardware
Elegant Circuits: Simple Chaotic Oscillators (with J.C Sprott), World Scientific (2022)Download LTSpice Simulations
My current interests involves investigating our modern understanding of cortical columns to design novel neural networks that can solve dynamic problems requring continuous learning. The development of intelligent machines will not only lead to advancements in health care through a better understanding of brain cognition, but is existentially important in continuing our legacy as a human species in gathering knowledge and exploring the universe.
M.S Electrical and Computer Engineering, University of Michigan (2022)
B.S Electrical and Computer Engineering, Ohio State University (2018)
Semi-finalist for "Use it!" category Lemelson-MIT Student Prize for 2018
Winner of Tech Hub 2017 Student Project Grant (Won $4000 of funding for project: "A New Generation of Flexible Batteries)"
AI accelerator research using Memristor/RRAM devices at the University of Michigan with Prof. Wei Lu – Worked on implementing the "Thousand Brains theory", an algorithm describing how intelligence works, on RRAM crossbars to explore possible improvements in performance (Sept 2018 – May 2022)
Electrochemistry research at the Ohio State University with Prof. Anne Co - Developed fabric batteries for wearable technology and hydrogen peroxide generator. Filed patent applications (July 2016 – August 2018)
Internship at National Taiwan University with the Solid-State Laser Crystal and Device Research Group with Prof. Sheng-Lung Huang : Constructed a Ti:Sapphire laser cavity with wavelength tuning (May 2016 – June 2016)
Internship in Catania, Italy at Universit degli Studi di Catania with the Dipartimento di Ingegneria Elettrica Elettronica ed Information with Prof. Mattia Frasca: Studied chaotic circuits and published “A Simple Chaotic Flow with a Continuously Adjustable Attractor Dimension” (May 2015)
Session Chair, IEEE International Symposium on Circuits & Systems, Virtual (October 2020)
Neural Networks and Deep Learning, Coursera MOOC by deeplearning.ai, [Certificate] (November 2020)
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Coursera MOOC by deeplearning.ai, [Certificate] (November 2020)