School of Engineering


Showing 11-20 of 469 Results

  • Youssef Allouah

    Youssef Allouah

    Graduate Visiting Researcher Student, Computer Science

    BioYoussef Allouah is a visiting researcher at Stanford University, and a third-year PhD student at EPFL. He previously graduated from Ecole polytechnique in Mathematics and Computer Science in 2021, with a research internship at Amazon. His research interests lie in trustworthy machine learning, with a focus on the theoretical aspects of robustness and privacy in distributed settings.

  • Claire Anderson

    Claire Anderson

    Postdoctoral Scholar, Civil and Environmental Engineering

    BioAs a postdoctoral scholar interested in the intersections of human health, animal health, and the environment, I work across disciplines in Environmental Engineering (with Alexandria Boehm) and Epidemiology (with Jade Benjamin-Chung). My current work focuses on understanding the mechanisms of pathogen survival (including parasites and viruses) in the environment and microbial source tracking. My dissertation work centered on enveloped viruses, with a particular focus on understanding their persistence in the environment, transmission dynamics, and intervention strategies, especially in resource-constrained environments. Beyond my academic pursuits, I'm dedicated to increasing diversity, equity, and inclusion through outreach programs for students in every level of their education.

  • Rika Antonova

    Rika Antonova

    Postdoctoral Scholar, Computer Science

    BioI am a postdoctoral scholar at Stanford University and a recipient of the NSF/CRA Computing Innovation Fellowship. Currently, I work at the Interactive Perception and Robot Learning (IPRL) lab headed by Jeannette Bohg. In the summer of 2024, I will be transitioning to a faculty position at the University of Cambridge.

    I completed my PhD work on data-efficient simulation-to-reality transfer at the Robotics, Perception and Learning lab at KTH (Stockholm, Sweden), working in the group headed by Danica Kragic. During my PhD, I also had an opportunity to intern at NVIDIA Robotics (Seattle, USA) and Microsoft Research (Cambridge, UK).

    Previously, I was a Masters student at the Robotics Institute at Carnegie Mellon University, developing data-efficient approaches for learning controllers for bipedal locomotion (with Akshara Rai and Chris Atkeson). During my time at CMU, my MS advisor was Emma Brunskill, and in her group I also worked on developing reinforcement learning algorithms for education.

    Prior to that, I was a software engineer at Google, first in the Search Personalization group and then in the Character Recognition team (developing open-source OCR engine Tesseract).

  • Marta Arenas Jal

    Marta Arenas Jal

    Postdoctoral Scholar, Bioengineering

    BioMarta holds a PhD in pharmaceutical technology and an Executive MBA. She is passionate about healthcare research and innovation and has several years of experience in leading R&D projects within the pharmaceutical industry. Prior to joining Stanford Biodesign, Marta worked at CIMTI which is an accelerator for health startups that supports innovators to develop and implement solutions that improve healthcare quality and patient outcomes.

    Throughout her career, she has demonstrated a strong track record of successfully translating research and innovation into real-world impact. She is a curious, creative, and open-minded person who is always seeking to solve complex problems in order to make a positive impact on patients’ lives. In her current role as Innovation Fellow at Stanford Byers Center for Biodesign, she is part of a team working on developing innovative solutions to address unmet needs in healthcare.

  • Mansur Arief

    Mansur Arief

    Postdoctoral Scholar, Aeronautics and Astronautics

    BioI am a postdoctoral scholar at Stanford Intelligent Systems Lab (SISL). I received my Ph.D. degree in Mechanical Engineering from Carnegie Mellon in 2023 and a master's degree in Industrial and Operations Engineering at the University of Michigan, Ann Arbor. Much of my work combines machine learning and rare-event theories to efficiently simulate rare catastrophic events. The applications of this line of work include the accelerated testing of intelligent systems. Currently, I am working on AI for safety and sustainability projects, which merge efficient simulation frameworks with optimization and decision-making algorithms.