abd2141 at columbia dot edu
I am a Ph.D student in the department of Statistics at Columbia University where I am jointly being advised by David Blei and John Paisley. My work at Columbia is about combining probabilistic graphical modeling and deep learning to design better sequence models. I develop these models within the framework of variational inference which enables efficient and scalable learning. My hope is that my research can be applied to many real world applications particularly to natural language understanding.
Prior to joining Columbia I worked as a Junior Professional Associate at the World Bank. I did my undergraduate training in France where I attended Lycee Henri IV and Telecom ParisTech--France's Grandes Ecoles system. I hold a Diplome d'Ingenieur from Telecom ParisTech and spent the third year of Telecom ParisTech's curriculum at Cornell University where I earned a Master in Statistics.
May 2018: I am excited to be interning at Facebook AI Research this summer.
May 2018: Our paper "Augment and Reduce: Stochastic Inference for Large Categorical Distributions" is at ICML.
May 2018: Our paper "Noisin: Unbiased Regularization for Recurrent Neural Networks" has been accepted at ICML.
Feb 2018: I will be part of the Women Techmakers 2018 Summit panel at Google, New York.
Feb 2018: I will be giving a spotlight talk at the NYAS ML Symposium.
Tufts University CS Colloquium, Medford, MA, April 2018
Harvard University NLP Group Meeting, Cambridge, MA, April 2018
Stanford University NLP Seminar, Stanford, CA, April 2018
New York Academy of Science ML Symposium, NY, March 2018
Machine Learning and Friends Seminar, UMass, Amherst, MA, February 2018
Black in AI Workshop, Long Beach, CA, December 2017
MSR AI, Microsoft Research, Redmond, WA, August 2017
SSLI Lab, University of Washington, Seattle, WA, August 2017
DeepLoria, Loria Laboratory, Nancy, France, April 2017
AI With The Best, Online, April 2017
OpenAI, San Francisco, CA, January 2017
IBM TJ Watson Research, Yorktown Heights, NY, December 2016
Microsoft Research, Redmond, WA, August 2016