CMNS Doctoral Commencement Ceremony
Tuesday, May 19, 2026
10:30 a.m.
Reckord Armory
Light reception to follow.
- Graduates will walk across the stage during this ceremony. Regalia is required.
- The ceremony will be live-streamed at youtube.com/user/cmnsumd.
- Keynote Speaker: Susan Gregurick (Ph.D. ’95, Chemistry), Associate Director for Data Science and Director of the Office of Data Science Strategy, National Institutes of Health
- Student Speaker: Pooja Guhan (Ph.D. ’25, Computer Science)
Schedule
- 9:45 a.m. - Ph.D. graduates and hooders arrive, enter Reckord Armory through the ground floor (see map below), and proceed to graduate check-in.
- 10 a.m. - Guests begin arriving at Reckord Armory through the front door by the steps (see map below)
- 10:30 a.m. - Procession of Platform Party and Ceremony begins
- ~12 p.m. - Reception immediately following the ceremony
The ceremony will last approximately 1 hour and 30 minutes. Graduates and guests are expected to remain and stay seated for the entirety of the ceremony.
Read the full Armory bag policy and prohibited items, parking and accessibility information.
Parking
- The closest parking is Regents Drive Garage. The Reckord Armory is a ~10-minute walk from Regents Drive Garage or a short ride on the UM Shuttle’s Armory/Chapel Loop (see the parking and shuttle map for route details; times are subject to change).
- Parking permits are not required and meters will be turned off on campus. Be sure to obey all posted signage throughout campus as details may change.
Accessibility
- Accessible parking spaces will be available in most lots on a first-come, first-served basis and still require a state-issued license plate or hang tag.
- Guests with limited mobility can be dropped off before parking.
- ADA access is located on the access lane (parking Lot QQ) between the Miller Administration Building and the Armory. Guests with limited mobility can be dropped off here before parking.
- Accessible parking is located at Regents Drive Garage.
- Wheelchair-accessible shuttles are available between Regents Drive Garage and Reckord Armory.
- All seats in the Armory are ADA-accessible via the building's rear entrance.
- More information and accessibility resources, such as wheelchair rentals, are available at https://commencement.umd.edu/main-ceremony/accessibility.
- If you need special arrangements for hearing impairment or other disabilities, please contact Amy Chester (alevine@umd.edu).
Program
Processional
Presiding
Amitabh Varshney
Dean, College of Computer, Mathematical, and Natural Sciences (CMNS)
Keynote Speaker
Susan Gregurick
Ph.D. ’95, Chemistry
Associate Director for Data Science and Director of the Office of Data Science Strategy, National Institutes of Health
Student Speaker
Pooja Guhan
Ph.D. ’25, Computer Science
Recognition of Doctoral Degree Recipients
Reading of Recipients:
Gene Ferrick, Director of Operations, CMNS
Recessional
Reception (outside)
Keynote Speaker: Susan Gregurick
Susan Gregurick (Ph.D. ’95, chemistry) is the associate director for data science and director of the Office of Data Science Strategy at the National Institutes of Health (NIH), where she orchestrates the NIH-wide efforts to harness high-performance computing (HPC), data science and artificial intelligence (AI) for human health. Since 2019, she has overseen the NIH’s Strategic Plan for Data Science, building partnerships that range from AI-ready cloud platforms to the proposed National AI Research Resource.
Prior to her current role, she directed the Division of Biophysics, Biomedical Technology, and Computational Biosciences at the NIH’s National Institute of General Medical Sciences, and she worked at the Department of Energy. Prior to government service, Gregurick was a professor of computational chemistry at the University of Maryland, Baltimore County.
Gregurick was named to HPCwire’s 35 Legends Class of 2025, awarded an HPCwire Outstanding Leadership in HPC Award in 2022 and received the 2020 Leadership in Biological Sciences Award from the Washington Academy of Sciences.
[Read more about Dr. Gregurick]
Student Speaker: Pooja Guhan
Pooja Guhan's research focused on computer vision, multimodal learning, affective computing and generative artificial intelligence (AI), with an emphasis on methods that improve how visual media is edited and understood. Advised by Distinguished University Professor Dinesh Manocha, her dissertation focused on developing AI-driven algorithms for contextual video editing. She studied how models can interpret creative intent, adapt visual styles and suggest meaningful edits using visual and multimodal cues. Her work explored how machine learning can serve as a useful tool in the creative process, empowering creators to explore ideas more freely, expand their creative potential and engage more deeply with the storytelling process.
During her time at UMD, Guhan worked on research problems spanning video editing, image styling, telehealth engagement estimation and multimodal understanding. Her work has been published in venues including the European Conference on Computer Vision, the Association for Computational Learning, the Computer Vision and Pattern Recognition Conference, Scientific Reports, JMIR and the IEEE Virtual Reality Conference. She also collaborated with researchers across academia and industry on projects at the intersection of vision, language and human-centered AI.
Her academic achievements have been recognized through several honors, including the University of Maryland Summer Research Fellowship, the Computing Research Association's Committee on Widening Participation Grad Cohort for Women Scholarship, the Grace Hopper Celebration Scholarship and the Richard Tapia Celebration of Diversity in Computing Conference Scholarship.
In addition to her academic work, Guhan gained industry experience through research internships at Dolby Laboratories, Adobe Research and IBM Research, where her work led to patents and publications. She currently serves as a senior researcher at Dolby Laboratories in Atlanta, where she focuses on 3D modeling and video enhancement for next-generation media systems.
Guhan remains dedicated to contributing to the research community through mentorship, teaching and service. She serves as a reviewer for leading AI conferences and journals and is involved in mentoring initiatives that support aspiring researchers. In her free time, she enjoys drawing, painting, playing chess and traveling.