Gamze is an Assistant Professor in the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge. She previously served as the Herbert Irving Assistant Professor in the Department of Biomedical Informatics at Columbia University. Prior to joining Columbia, she completed a K99/R00 postdoctoral fellowship in computational biology at Yale University with Mark Gerstein and earned her Ph.D. in Bioinformatics from the University of Illinois at Chicago under the supervision of Jie Liang.

Kirill is a an associate research scientist at Columbia University Medical Center, working in Prof. Noemie Elhadad’s lab and he is a close collaborator with us. Previously, he completed a postdoctoral research associate position in our lab at the New York Genome Center. He obtained his PhD in computer science at EPFL, advised by Bryan Ford, and worked as a postdoc with Vitaly Shmatikov at Cornell Tech before joining our lab. Having specialized in protecting communication privacy and data retrieval, Kirill now strives to build real-world solutions for privacy-preserving analysis and sharing of genomic data. During his leisure time, he enjoys going to theatre plays, learning bachata, and dining in outer boroughs.

Sydney is a Postdoctoral Research Associate in the lab. She was previously an NIH/NLM T15 Biomedical Informatics Fellow at Columbia University. She completed her PhD at Tufts University where she studied how obesity-dependent changes in the breast tumor microenviornment promote tumor growth and metastasis.

Xiaoting is a Postdoctoral Research Associate in the lab. She completed her PhD at Columbia University where she worked with Prof. Harmen Bussemaker on genetic variant effects on transcription factor regulation. She enjoys playing tennis and baking in her free time.

Alison Sutherland is a Postdoctoral Research Associate in the lab. She received her PhD in Human Evolutionary Genetics from the University of Cambridge, advised by Profs. Maanasa Raghavan and Eske Willerslev. Her research will focus on biological encryption and the permeation of genetic material in soil. Outside of the office Alison enjoys playing hockey and softball, nurturing an ever-growing collection of plants, and volunteering in science outreach with youth.

Jacob is a PhD student at the Computer Science department of Columbia University. He graduated from UVA with a BS in Math and CS. He loves swimming and analyzing swimming technique with CS. He also enjoys ragtime / stride piano.

Carlos is a Pharmacology PhD student in Columbia University and jointly mentored by Chao Lu at Columbia Genetics. He obtained my BS in Genomic Sciences (Bioinformatics) at the National Autonomous University of Mexico (UNAM). His research interests lay in developing computational methods to understand how mutations and disease alter genome topology and epigenetic patterns. Outside the lab you can find him at the gym, listening to kpop or finding new coffee shops in NYC.

Abby is a PhD student in Biomedical Informatics at Columbia University. She graduated from UVA with a BA in math and a double minor in biology and data science. In her free time she enjoys running, hiking, and listening to podcasts.

Rashid is PhD student in Computer Science at Columbia. He obtained his BS in Computer Science from Stanford University. He is interested in 3D genome, repeat DNA and its regulatory role in the genome. He is an avid cook in the kitchen, and writes spoken word poetry in his free time.

Florent is a PhD student in Biomedical Informatics at Columbia University. He graduated from PSL University with a MSc in CS and from Paris-Saclay University with a MSc in Applied Math for AI. In his free time, he loves running, biking, and swimming.

Yebin Kim is a visiting scholar in the G2 lab. She is pursuing her Ph.D. degree in Bioinformatics at Indiana University Bloomington. During her academic journey, she aspires to bridge the gap between traditional medical practices and personalized medicine. Her research interest encompasses developing computational tools that aim to predict an individual’s disease causes or prognosis, thus paving the way for more tailored and effective medical interventions.