I am a 2nd-year Ph.D. student in Computer Science at the University of Vermont advised by Joe Near. I’m also a research scientist at OpenMined. 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 have lived and studied in 3 continents, completed my undergrad in Cameroon, Master’s in Turkey and currently in the US. 

Interested in collaborating? If you have a cool idea and would like to discuss it, don’t hesitate to email me

Ivoline Ngong

PhD Candidate, UVM ivolinengong@gmail.com