I am a Masters Student in the field of Deep Learning at the Technical University of Munich and have been working in the field for the past 4 years.
Work Experience
Currently, I am also working with a Medical Imaging Company, Imfusion Gmbh - Munich, in the capacity of a Computer Vision Engineer, applying Deep learning on Medical Images and Computer Vision datasets.
My work mainly focusses on Semantic Segmentation and 3D to 2D registration. Tensorflow/Keras was the framework of choice.
Previously I had worked at Edge Networks, Bangalore, India in the capacity of an NLP Engineer where my work primarily focussed on applying Deep learning on tasks such as named entity recognition and sentence classification using LSTMs. Pytorch was the framework of choice.
Projects
At TUM, I am mostly working on Deep Reinforcement Learning applied to various domains such as Robotics, Protein Extraction etc. My work done here is primarily done in Pytorch.
I have also developed various projects such as a Movie recommendation engine, data simulation developer and Probabilistic programming in pytorch.
I have implemented the Transformer Network, that only works with attention modules, in Pytorch and used it for sentiment classification
All my projects are enlisted in my github profile.
Accomplishments
I have coauthored a paper titled 3D Registration using Deep Learning, which as been accepted at MICCAI 2018.
Interests
I am mostly interested in working on Deep Learning applications as well as general machine learning applications and data visualization. My current research interests lie with Deep Reinforcement Learning and Bayesian Optimization.
