Alizishaan Khatri

I am a technology professional with an academic research and industry background in Natural Language Processing, Deep Learning, Machine Learning, Differential Privacy and Software Development.

I currently work as a Machine Learning Engineer on the research team of Pivotus Ventures, a Fintech innovation lab. My responsibilities include (but are not limited to) reproducing results from research papers, conceptualizing and building Proof-Of-Concept AI solutions to business problems and conducting blue-sky research. Major accomplishments in the current role include building an abusive content flagging system using deep convolutional networks that bettered the state-of-the-art.

I have graduated from SUNY-University at Buffalo with a Masters Degree in Computer Science. My thesis investigated the use of differential privacy to tackle overfitting in deep neural networks.

In the past, I have worked as a Data Science Intern to build a neural network based regression / classification system and a 'model-as-configuration' based deployment system for neural networks. Over the summer of 2016, I interned at a platform-based solar energy company in Oakland,CA. My role was primarily DevOps with additional responsibilities extending into the domains of Site Reliability and Build & Release engineering.

I have completed academic coursework in the areas of Machine Learning, Differential Privacy, Multi-lingual Information Processing and Retrieval, Pattern Recognition, Deep Learning, Differential Privacy, Computer Vision and Networks. I have worked as a student researcher to develop a customized search engine for Arabic Script data.

During my time off, I enjoy travelling, mountaineering, landscape photography, skiing and philately.