I am a 2nd-year Ph.D. student in Computer Science at the University of Vermont and a research scientist at OpenMined. I am very fortunate to be advised by Joe Near. My research interests broadly revolve around data privacy and all aspects of machine learning; theory, algorithms, and applications.
Currently, I’m focusing on private data analytics and privacy-preserving machine learning including differential privacy, federated learning, and secure multiparty computation.
In the past, I’ve published papers in fairness workshops at Neurips , contributed to Microsoft Research VowpalWabbit opensource project and to OpenMined’s PySyft library where we build Privacy Enhancing Technologies (PETs) that will hopefully lower the barrier of entry to privacy.
Fun fact: I’m a true citizen of the world! I’ve hopped across three continents for my education – the journey started with my undergrad in Cameroon, my Master’s degree brought me to Turkey, and now I’m crushing it in the land of the stars and stripes, the good ol’ USA!. Talk about racking up those frequent flyer miles!
Interested in collaborating? If you have a cool idea and would like to discuss it, don’t hesitate to email me.
PhD Candidate, UVM email@example.com