Explorer Categories: EECS

I was born and raised in Southern California, and I became interested in electrical and computer engineering after developing a strong passion for music technology. When experimenting with digital synthesizers and audio effects, I was fascinated by the mathematics that made all of the signal processing possible. I went on to study engineering at Brown University, along with playing lacrosse on the club team and being a part of the Brown Space Engineering club. Now, at UC Berkeley, I am working on a project with Professor Anant Sahai that studies deep learning models from a signal processing perspective.

Philothei is a PhD student in EECS at Berkeley, advised by Professor Ana Arias. Her research focuses on developing scalable energy and sensing devices through wet solution processing techniques, with the goal of making energy and environmental monitoring more accessible. She earned her undergraduate degree in Materials Science and Engineering from Georgia Tech, where her international experiences studying, working, and researching in Singapore, Liechtenstein, and France shaped her commitment to inclusive research with a global impact. In her free time, Philothei enjoys hiking, reading, and gardening.

Hila Mor is a researcher, designer and artist. She is currently working on her  Ph.D. advised by Professor Eric Paulos at the Hybrid Ecologies Lab, EECS, UC Berkeley. Her work centers on Human-Computer Interaction and the design of interactive computational materials. She is developing powerless sensors and displays that harness ubiquitous material dynamics in novel ways. Hila’s research aims to not only uncover new forms of interaction through programmable materials but also to democratize these technologies, making them more accessible to diverse communities. She holds a Master of Media Arts and Sciences from the MIT Media Lab, where she was part of the Tangible Media Group, and a B.Des Cum Laude in Product Design from the Bezalel Academy of Art and Design.

Haifah Sambo is a PhD student in the Electrical Engineering and Computer Sciences department (EECS) at UC Berkeley, advised by Professor Robert Pilawa-Podgurski. She previously received the B.S degree in Electrical Engineering at the University of Oklahoma in 2021. Haifah’s work is focused on the design and control of 48 V DC-DC converters with an emphasis on computing and data center power delivery applications. Using high-bandwidth analog and digital circuits, she has developed several closed-loop control techniques aimed at increasing the efficiency and robustness of hybrid switched-capacitor converters. Outside of research, Haifah currently serves as the Student Membership Chair for the IEEE Power Electronics Society.

Mihir grew up in the Bay Area, and is a third year undergraduate student studying Electrical Engineering and Computer Sciences (EECS). He is currently working with Professor Kris Pister on using MEMS to develop novel microrobots. In the past, he has worked on materials science research where he investigated optoelectronic properties of various heterostructures and monolayers. His research interests include combining the fields of robotics and microprocessor design to make devices that can help with energy efficiency and minimally invasive surgeries. In his free time, he loves to watch and play basketball and go for hikes.

Yiyang Zhi is a graduate student in the EECS department advised by Professor Ming C. Wu. His research focuses on integrated optics co-fabricated with control electronics for trapped ions systems. Individual ionic species confined and addressed by electromagnetic fields are a promising platform for quantum information, sensing, and computation due to high operation fidelity and long coherence time. He is developing an architecture that embodies a pathway towards scaling up while preserving key performance metrics. Outside of the lab, Yiyang enjoys playing basketball and hosting events for Photobears, a professional joint student chapter of SPIE, Optica, and IEEE Photonics Society.

I am a PhD student in the EECS department, working at the intersection of machine learning and the physical sciences. On the one hand, I am interested in how our knowledge of physics can inspire new machine learning algorithms. On the other hand, I am developing machine learning methods that can simulate molecules and materials thousands of times faster and at comparable accuracy to first principles quantum mechanical calculations. Being able to efficiently simulate and understand atomic worlds will open the door for material discovery, drug design, and beyond. Outside of my research, I enjoy playing soccer and tennis, and I am learning how to play the guitar.

I am a Design PhD student at UC Berkeley, advised by Prof. Kosa Goucher-Lambert and affiliated with the Berkeley Institute of Design. I hold a B.S. in Mechanical Engineering from the University of Texas at Austin. During my PhD, I have collaborated with professors and researchers from CityU of Hong Kong, Carnegie Mellon University, and AutoDesk Research. I have also conducted research as an intern at HP Inc. and NASA Langley Research Center. My research primarily focuses on the intersection of human-AI interaction, design theory, and machine learning. Outside of research, I enjoy hiking, dancing, and weightlifting.

Margarita Geleta is an AI researcher affiliated to the Berkeley AI Research (BAIR) laboratory and the Stanford Department of Biomedical Data Science (Stanford DBDS), currently pursuing her PhD in Computer Science at the University of California, Berkeley. Previously, she interned at Amazon as an Applied Scientist at the Home Innovation Team, specializing in large-scale generative models, including the development of the state-of-the-art method for GAN inversion. She also developed XR applications for spatial audio manipulation while interning at Dolby Laboratories at the Advanced Technology Group (ATG) in R&D, and co-founded a defense tech startup backed by Founders, Inc.