Peter is a PhD student at Berkeley EECS working with Professor Gopala Anumanchipalli on neural decoding. His current research focuses on helping people with paralysis communicate.
I am a PhD student in EECS studying deep learning and artificial intelligence. I’m interested in developing reliable and robust methods for machine learning from large amounts of data and compute. I’m also very excited about the practical applications of these new technologies and how they might augment our innate abilities to understand the world and each other.
Alicia is a PhD candidate in Computer Science affiliated with the Berkeley AI Research (BAIR) Lab. She focuses on optimization, new computational models, and algorithms for machine learning, with a focus on efficiency and robustness.
Why I’m Here I am a Ph.D. EECS student in Professors Kris Pister’s lab. My research area is low power wireless radios. My vision is to make wireless sensors 5 times smaller than a grain of rice while making it reliable and robust enough to use. I believe that our society could benefit greatly from having small affordable sensors to make informed decisions on fires, natural disasters, etc. About Me I am a Ph.D. student in EECS focused on integrated circuit design for low power wireless radios. I enjoy dancing salsa/bachata, biking, running, rock climbing and playing guitar.
I am an undergraduate student studying computer science and physics who is interested in using these two fields to better understand our immune system. I leverage multi-omics single cell datasets from patients with immune-mediated diseases to increase our understanding of pathogenesis in these diseases. Since these datasets are heavily influenced by biases and patient heterogeneity, I am also developing computational methods for analyzing these datasets more robustly. After college, I hope to pursue a PhD in computational biology and continue using computational tools to help treat immune-mediated diseases.
I’m a 2nd-year Ph.D. student in Computer Science affiliated with the CS Theory Group and the Berkeley AI Research (BAIR) Lab. I do research in theoretical computer science (TCS), artificial intelligence (AI), mathematical economics, and their intersections. Most recently, graph theory, algorithmic game theory, statistical learning, and combinatorial optimization. I also think about how tools and techniques from TCS, AI, and economic design can yield insights about and help solve important societal problems.
I grew up in Lagos, Nigeria before moving to the US in 2017 to attend Oberlin College and Conservatory, from which, I graduated in May 2021 with a BA in Math and Computer Science (Highest Honors). In my spare time, I’m an avid enjoyer of fantasy novels, manga/manhwa, comics, and world history.
Ritwik is a second year Ph.D. student at UC Berkeley focused on efficient computer vision for humanitarian assistance and disaster response, and technology-policy co-design to ensure the safe and reliable use of these technologies in developing countries. Ritwik’s research has been used widely by over a hundred organizations such as CAL FIRE and the United Nations.
2nd year Vision Science PhD student, studying theoretical neuroscience advised by Bruno Olshausen.
I am a PhD candidate in EECS studying next generation power converters to enable electric aircrafts and future space travel.
I’m a PhD student in EECS. I currently work on accelerating computational chemistry with machine learning