About

Introduction

I am Mandar Deshpande from Nagpur, India. Currently a graduate student at UCLA Electrical and Computer Engineering Dept with a focus on signal processing and machine learning. I graduated from VNIT Nagpur in 2017 where I studied Electrical and Electronics Engineering.

My research interests are in deep learning for vision/nlp and reinforcement learning.

Past work/Research

• Google Summer of Code 2019 -
  • TensorFlow Mentor : Mentored Ryan Lee in the development of curiosity module for TF-Agents along with Oscar Ramirez. Ryan implemented Random Network Distillation (RND), a state-of-the-art bonus-based exploration reinforcement learning algorithm

• Machine Learning Engineer at Citi : Solved NLP and CV use cases usig deep learning and traditional vision techniques for images. Utilized NLP for parsing financial documents and extarcting relevant information.

• Google Summer of Code 2018 -
  • Scilab Mentor: Mentored Soumitra Agrawal (student) in the development of machine learning toolbox for Scilab, to extend my GSoC 2017’s work on jupyter integration for remote script execution
  • Gensim Mentor: Co-mentor to Aneesh Joshi on the neural networks for similarity learning research for Gensim, a topic modelling and nlp toolkit (under Numfocus)

• Google Summer of Code 2017: Worked with Scilab to develop a modular ml toolbox, which allowed remote execution of python model traning over network and inference on local machineProject page

• Developed a deep understanding of PyTorch by implementing models from scratch. Got selected as an International Fellow for fast.ai’s Cutting Edge Deep Learning for Coder Part 2 v2

• Researched PixelCNN based pixel wise image completion models in collboration with IVPL Lab, Northwestern University. Utilized Tensorflow and keras to develop residual networks.

Learning moto

Only persistence fuels my learning engines and the dream to become a ml engineer one day!

Contact me

All your suggestion and help will be useful, so don’t hold back! :D

mandar061095@gmail.com
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