Kristofer S.J. Pister (Advisor)

Research Advised by Professor Kristofer S.J. Pister

Pister Group:  List of Projects | List of Researchers

Hani Gomez

Postdoctoral Researcher
Electrical Engineering and Computer Sciences
Professor Kristofer S.J. Pister (Advisor)
Ph.D. 2020, PostDoc 2024 to 2025

Originally from Cochabamba, Bolivia, Hani obtained her BS in Electrical Engineering at the University of South Carolina, Columbia. In 2020, Hani graduated with a PhD from UC Berkeley, where she focused on the design, fabrication and assembly of walking silicon microrobots using MEMS technology. Now, she is once again working with Kristofer Pister, developing a six-axis controlled, electrostatically levitated 1g mass system.

Multi-Objective Mission Planning for Solar Sails and Swarm Networks

Mostafa Sedky
Maya Horii
Thomas Hosmer
Kristofer S.J. Pister
Tarek Zohdi
2025

Solar sails, which use optical pressure from the sun as propulsion, have great potential to be an inexpensive and sustainable way of exploring the universe. Recent advancements in the semiconductor industry have given rise to small and light actuators, sensors, and cameras, which make it possible to design high-performance, low-cost solar sails. For example, the Berkeley Low-cost Interplanetary Solar Sail (BLISS) is a sail design that takes advantage of lightweight electronics to enable a high sail area-to-mass ratio. Being low-cost and propellant-free, this design is well suited for rapid...

Time Constant Estimation on a Low-Cost, Low-Power Microcontroller Using the Matrix Pencil Method

Kelly L. Tou
Titan Yuan
Kristofer S.J. Pister
2025

An algorithm to accurately determine the time constant of a circuit simplifies reading out resistive and capacitive sensors. However, implementing such an algorithm on low-cost, low-power microcontrollers requires overcoming hardware limitations, such as ADC noise, limited memory, and the lack of a floating-point unit. This work utilizes the Matrix Pencil Method (MPM) to estimate the time constant of a decaying exponential signal and outlines the non-trivial firmware implementation of the algorithm on a low-cost, low-power microcontroller. Experimental results show that time constants over...

BSAC's Best: Fall 2024 Awards Announced

September 19, 2024

BSAC is pleased to announce the outstanding paper and presentation award recipients from the Fall 2024 Research Review on September 18th. The Industrial Advisory Board was highly impressed by the quality of research, and the recipients’ work stood out in a competitive field.

We sincerely thank all the researchers who presented their innovative projects. These contributions are key to advancing research and fostering collaboration between academia and industry.

After careful evaluation, BSAC Industrial Members have voted, and we congratulate the Fall 2024 Best of BSAC honorees...

Titan Yuan

Graduate Student Researcher
Electrical Engineering and Computer Sciences
Professor Kristofer S.J. Pister (Advisor)
Ph.D. 2027 (Anticipated)

Titan received his B.S. and M.S. in EECS from UC Berkeley in 2019 and 2020, respectively, advised by Prof. Kris Pister. After graduating, he spent two years in industry working on radar embedded software and signal processing for autonomous vehicles. He is currently pursuing a Ph.D. in EECS, also advised by Prof. Kris Pister, with an interest in wireless sensor networks, RFICs, and RF/wireless sensing.

BSAC Spring 2025 Research Review...

Daniel Teal

Alumni
Electrical Engineering and Computer Sciences
Professor Kristofer S.J. Pister (Advisor)
Ph.D. 2024, PostDoc 2025

EECS PhD student under Prof. Kristofer Pister; previously earned a BS mechanical engineering / math from the University of Texas at Austin. Studies MEMS and microfabrication. Interested in making microfabrication faster and easier.

Benjamin Cook

Visiting Scholar Researcher
Electrical Engineering and Computer Sciences
Professor Kristofer S.J. Pister (Advisor)
Ph.D. 2007, Visiting Scholar 2025 to present.

BPN915: Control of Microrobots with Reinforcement Learning

Yichen Liu
Kesava Viswanadha
Zhongyu Li
Emily Tan
Nelson Lojo
Derrick Han Sun
Aviral Mishra
Rushil Desai
2025

Developing task schedulers and low-level end-to-end controllers for microrobots operating in complex environments often demands extensive system and environment knowledge, leading to prolonged design cycles for specialized controllers. To expedite the generation of general controllers without requiring domain-specific expertise, we propose utilizing model-based reinforcement learning (MBRL) trained within simulated environments. Our research advances microrobot control through two key approaches: modeling the long-term dynamics of robots and distilling computationally intensive model...