Yash Savani

I worked on improving RL methods to fine-tune flow-based models.

I performed research in the AutoML / NAS and Fairness in ML domains. We wrote five papers based on this work.

I designed and implemented scalable deep learning architectures including LSTM forecasting models, AutoML / NAS regression and classification models, GAN data augmentation models, and VAE anomaly detection models among others.

I worked on improving contemporary statistical learning and applied graph theory models for natural language applications. The machine intelligence algorithms I developed help decipher global news data.

I worked on developing the front end experience for a collaborative graph visualization tool using React.js, Redux, and Webpack. I also added basic NLP functionality to the filter and search technologies.

I worked with an international team to develop an intelligent drone platform that applied advanced flight technologies, SLAM, and deep learning for improved flight stability and awareness.

In Andrew Ng’s AI lab I worked on the system infrastructure and CUDA code for a hybrid CNN and LSTM architecture designed to instantly detect and semantically segment images and videos with multiple stimuli.

In Sebastian Thrun’s AI lab I improved the performance of machine learning algorithms for smart home applications by adding thermal image descriptors into a robotics pipeline.

I assisted in the management of servers and the design of a Hadoop infrastructure for the data centers of telecommunication companies in Thailand.

I developed a medical iPad application for use in the orthopedic section of hospitals.