What comes after Commencement
Tufts University’s Department of Computer Science recently graduated eight PhD students. The new alumni’s interests have sent them in a number of exciting directions.
Matthew Ahrens is now at Worcester Polytechnic Institute (WPI) as an assistant teaching professor in computer science. In addition to teaching introductory programming to first year students and ethics in information technology to soon-to-be graduates, he conducts computer science education research with an NSF-funded nonprofit encouraging challenge-seeking learning strategies in demographics traditionally underserved in STEM education.
David Buckingham successfully defended his dissertation on multiagent epistemic planning in August 2022. He currently resides in Wisconsin.
Tyler Frasca completed a joint PhD in Human-Robot Interaction and Computer Science. He is now working as a robotics engineer in the Human-Robot Interaction Lab at Tufts, focusing on developing algorithms to improve the versatility of robots and human-robot interaction.
Evana Gizzi has a joint PhD in Computer Science and Cognitive Science. She is currently working at NASA Goddard Space Flight Center where she has developed a multi-year project for using AI for fault mitigation. She currently serves as the Mission Resilience lead for a constellation mission design concept, which will develop swarms of satellites.
Dan Kasenberg graduated with his PhD in August 2022 and launched his career as a research scientist at DeepMind in Montreal, Quebec.
After defending his dissertation in May, Sam Lasser became a senior member of the technical staff at Draper, a nonprofit research and engineering organization in Cambridge, MA. He is currently working on several projects related to binary program analysis.
Xinmeng Li is now employed at Montai Health in Cambridge as a machine learning scientist. She works with data to create machine learning models to help invent breakthrough technologies in order to transform health care and sustainability.
Linfeng Liu works as a research scientist at Meta’s (Facebook) Cambridge office. In this role, he is responsible for designing a scalable machine learning system to better recommend ads/context to users in real-time.