Anisha Iyer

WORK HISTORY

EDUCATION

ABOUT ANISHA IYER

Hi, I’m Anisha!🧸 I\'m a UC Berkeley graduate in Computer Science and Molecular & Cell Biology (Neurobiology), pursuing research at the intersection of computation, neurobiology, and medicine. My goal is to bridge theory, computation, and engineering to make meaningful contributions to basic science, clinical medicine, and the applied tech ecosystem.🧠 I am driven by a motivation to understand complex behaviors of intelligent systems through computational, theoretical, data-driven, electrophysiological, and biological lenses — and to develop technologies that advance both basic science and clinical care. I’m fascinated by the theoretical foundations of machine learning and neuroscience, and the underlying logic and structure of biological systems, from signaling cascades to emergent neural representations. At Berkeley, I led Neurotech@Berkeley’s Software Division, mentoring 50+ developers on projects in speech prosthetics, computational neuroscience, and multimodal neuroimaging pipelines. As a Research Officer at Machine Learning @ Berkeley, I led the org’s largest research initiative and hosted 30+ ML research workshops. I’ve also published articles with Berkeley Scientific Journal, contributing to scientific discourse on therapeutics, bioengineering, neuroAI, and neurotech for psychiatry, neuro-oncology, and neuroscience. As President of MedTech@Berkeley, I founded a technical org at the intersection of computation, engineering, and medicine — recruiting 80+ members and leading an 11-person Executive Board with international org partnerships and a private workspace at Berkeley\'s Health Tech CoLab. I built a full-stack project for Stanford Global Emergency Medicine and piloted undergrad training programs in software and ML for medicine as well as a Berkeley DeCal course. I presented our work at INTED 2024 and led a team to publish our findings as first author. Outside of student orgs, I’ve conducted deep RL research with Harvard\'s Intelligent Systems / Neural Network Group, jointly with NTT Research\'s PHI Lab and Harvard\'s NSF-Simons MathBioSys Research Center, interned with Harvard\'s Systems Biology REU program, and pursued wetlab research in sensory neuroimmunology at Berkeley\'s Helen Wills Neuroscience Institute, culminating in a thesis on automating deep learning-based pain detection for SARS-CoV-2 studies. I\'m currently seeking pre-doctoral research roles in machine learning, bioengineering, and neurobiology and am always eager to collaborate on exciting problems in science, tech, and medicine!