UCLA Department of Computational Medicine Celebrates a Milestone Trio of Graduations
The UCLA Department of Computational Medicine proudly announces three distinct graduations this month.
Empowering Next-Generation Researchers: The 2026 Bioinformatics Minor Graduation
The 2026 Bioinformatics Minor ceremony honored a group of undergraduate students who have successfully completed a training program covering in-depth study of both computer science and biology. Throughout their coursework, this year's minor graduates explored active research problems of modern medicine. Their studies included investigating the genetic determinants of complex human conditions like cancer and psychiatric diseases. They also developed computational methods to analyze expression data and the epigenome, while advancing their understanding of population genetics and evolution. Armed with these highly relevant skills, the graduates are well-prepared to enter top-tier research labs and innovative biotech firms.
2026 Graduates:
Ajay Krishnan
Yubin Lee
Udbhav Avadhani
Abdallah Ahmad Fares
Sailesh Gunaseelan
Cinyoung Huang
Malvika Iyer
Haotian Ji
Kiersten Jieun Kang
Kendall Madison Kay
Gianna Kim
Irina Kryukov
Boey Li
Matthew Link
Yuka Murakami
Jocelyn Jinyueran Ni
Jimmy Tian
Xinlin Ye
Honoring Doctoral Excellence: The 2026 Biomathematics PhD Graduation
The department also celebrated the graduation of one doctoral candidate Gaiting (Gary) Zhou from the Biomathematics PhD program, the flagship program of the Department of Computational Medicine which has been awarding PhDs continuously since 1979.
The First Graduating Class of the Data Science in Biomedicine MS Program
Marking a historic milestone for the department, the ceremony recognized the “pioneers” graduating from the Master of Science in Data Science in Biomedicine program. The program’s first cohort included a wide array of professionals, including IT staff, mathematics majors, and full-time data analysts.
Despite the program’s flexible, remote format designed to accommodate working professionals, it intentionally fostered a strong, tight-knit community. Through collaborative study groups and engaging in-person events, these students successfully advanced their academic credentials without pausing their careers.
Academically, the curriculum equipped these graduates with advanced data and modeling skills. They gained invaluable hands-on experience building machine learning models with electronic health records, as well as conducting genomic DNA and medical imaging analysis. Through initiatives like the Biodesign AI fellowship, students also gained crucial exposure to med-tech innovation and entrepreneurship, learning how to reverse-engineer solutions for complex healthcare business challenges.
These pioneering graduates can now apply their expertise to direct clinical and medical applications. Moving forward, they are prepared to translate their research into tangible improvements in the patient experience, predict post-operative mortality, and tackle chronic illnesses on a global scale.
2026 Graduating Students:
Rohan Chatterjee
Sarthika Chimmula
Benjamin Cooper
Laura Diao
Blake Dickerson
Noora El Sherif
Christopher Fu
Yasna Hajikarimian
Eugene Hsue
Waleed Khan
Clifford Andrew Kravit
Jordan Tatt Krestul
David Mastro
Demetri Nicolaou
Cynthia Nguyen
Anish Patel
Adi Pillai
Courtney Rauchman
Rukmini Alwar Ravi
Alexander Noor Sherzai
Ira Shirdhankar
Troy Sisson
Andrew John Soliman
Jarrett Brittis Sung
Margaret Clara Wang
Karen Zhou