I am a PhD candidate in Information Science at Cornell Tech in New York City. I am interested in large scale data mining applied to healthcare, cyber security & video analytics. During summer 2016, I interned at Dropbox with Abuse Prevention team. Before PhD, I completed Master of Engineering in Computer Science from Cornell.
I like to ask simple questions and build practical systems capable of producing significant impact by answering those questions.
How can we analyze visual data?
Answer: Deep Video Analytics
How can we share visual data?
Answer: Visual Data Network
How can doctors use patient datasets?
Answer: Computational Healthcare
I am currently developing Deep Video Analytics an open source visual data analytics platform. The platform uses deep learning based indexing, detection and recognition models for visual search. Using Deep Video Analytics users can quickly load, annotate, index, images & videos. They can detect and recognize objects (such as faces) and seamlessly import and share processed datasets using Visual Data Network. Deep Video Analytics is developed using Django, Postgres, Tensor Flow & Docker to enable flexible deployment.
Today numerous high quality datasets are shared by researchers. However due to incompatible formats, using these datasets requires significant effort. Deep Video Analytics provides a standardized way of analyzing visual data. As a result it opens up possibility of sharing structured visual data (Video, Images with associated annotations, detections and indexes) I am building a lightweight Visual Data Network which allows effortless sharing of data. Visual Data Network aims to become Git / GitHub of visual data.
Today medical researchers can acquire de-identified data on millions of patients. Yet currently there is no system that allows them to quickly explore & use this data while ensuring compliance with privacy requirements. Computational Healthcare platform indexes and aggregates data from millions of patient visits, enabling physicians and researchers to conduct high-impact medical research.
Computational Healthcare is developed in collaboration with Radiology, Anesthesiology & Neurology departments at Weill Cornell Medical College. It is open source and available for use by researchers.
I have worked on several projects such as community detection & topic models for Twitter, prediction of protocols for radiology imaging orders. As an undergraduate student I published research on prediction of physical properties of molecules from their structure.
Copyright Akshay Bhat, 2017. All rights reserved.