Samantha Coday

I am a PhD candidate in EECS studying next generation power converters to enable electric aircrafts and future space travel.

Dillion Acker-James

I’m a graduate student studying Micro Electro Mechanical Systems (MEMS) who has worked on medical devices and transformative micro switches. I grew up in Santa Barbara and Mariposa: two very different places in California. I didn’t code nor take a physics class until undergrad and actually chose my focus in electrical engineering because I mistakenly thought that my grandpa was an electrical engineer. He did work for HP, but in the marketing department. Nevertheless, I thrived as an EE at UC Santa Barbara, and made the switch from III-V devices to MEMS in graduate school. The physics at the micro scale interests me because so much is counterintuitive, when compared to macro-physics, and can greatly impact our daily lives. I’m striving to make positive impacts with my work and life.

Austin Patel

Austin was born in San Francisco and has grown up in Bay Area. He is a 4th year undergraduate at UC Berkeley studying electrical engineering and computer science (EECS). At Berkeley, he is involved with undergraduate research in a micro-robotics lab as well as a computer vision group. His research interests include deep learning, robotics, and computer vision and especially the intersection of those three subjects. In addition to research, Austin has enjoyed his time as a teaching assistant in an introductory electrical engineering course at Berkeley. Outside of academics, Austin enjoys running, biking, and exploring the outdoors.

Marius Julius Wiggert

Marius Wiggert is originally from Germany where he studied Engineering Science, Philosophy, and Technology Management during his undergraduate. He is an outdoor enthusiast, enjoys camping on mountain tops, skiing, kitesurfing, and is an avid learner. In his EECS PhD at Berkeley, Marius focuses on developing methods that enhance the type of systems which we can reliably operate in and control. As he feels deeply connected to nature specifically the ocean and mountains, he initiated and won funding for his main research project: developing algorithms to reliably control underactuated seaweed-growing platforms in the ocean. To make seaweed-based carbon-sequestration as affordable as possible the platforms have limited energy and thrust smaller than ocean currents. This inspired the idea of the platforms “hitchhiking” on non-linear ocean currents to achieve steering over distances of hundreds of kilometers.

Helen Fitzmaurice

My research concerns quantifying emissions from the transportation sector using a dense sensor network in the Bay Area. To analyze effective methods that we can use to make inferences and new information about CO2 and particulate emissions from the transportation sector.

Nathan Owen Lambert

I am a PhD Candidate at the University of California, Berkeley working at the intersection of machine learning and robotics. He is a member of the Department of Electrical Engineering and Computer Sciences, formally advised by Professor Kristofer Pister in the Berkeley Autonomous Microsystems Lab. Nathan also has worked extensively with and been advised by Roberto Calandra at Facebook AI Research. Nathan has joined Facebook AI and DeepMind for internships exploring his research interests.

Nathan is an active member of the Graduates for Engaged and Extended Scholarship in Computing and Engineering (GEESE) working to understand how technology interfaces with society, writing frequently at [https://robotic.substack.com]. During his Ph.D., he was awarded the UC Berkeley EECS Demetri Angelakos Memorial Achievement Award for Altruism.

Caleb Xavier Bugg

Caleb Xavier Bugg is a graduate student in the Department of Industrial Engineering and Operations Research (IEOR) at The University of California, Berkeley. We create mathematical models to optimize decision-making processes, using all the information and resources available at the time of decision. Ultimately, we hope to move Our society towards the equitable distribution of raw materials and production means.

Armando Avevalo

I study electronic structure, and from these calculations and other design principles known from this phenomena, I will be synthesizing new classes of honeycomb Kitaev quantum spin liquids,. The focus of this work will be in spin transport measurements of these materials.

Andrew Shi

Andrew Shi is a PhD student in the department of mathematics. His research is in numerical methods for partial differential equations in the application area of computational fluid dynamics. In particular, his main project is on the subject of high-order shock tracking, which encompasses many fields in applied and computational mathematics such as numerical optimization and mesh generation. Prior to graduate school, he was a financial analyst in New York City. His Bachelor’s degree was also earned at UC Berkeley and he is originally from Dallas, TX.

Daria Balatsky

As a physical chemistry graduate student, I am currently working on the growth and measurement of various materials. Of current interest is researching materials towards Maxtronics or magnetic MAX phases for spintronic applications. Materials of this group, have unknown mechanisms for electrical manipulation of the spin textures, which allows us to study their use in electronic applications while also facilitating a better understanding of the fundamental physics. The goal would be a device in which we can use the materials for information storage (similar to antiferromagnetic spintronic devices) that is more robust due to the remarkable physical properties of MAX materials.