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
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.
I am a PhD student in EECS working on integrated circuits for biomedical applications. My research focuses on the development of electronic platforms for cancer diagnosis and treatment by utilizing electromagnetic waves for sensing and stimulating biological samples at the single cell and tissue levels.