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Ujwal2910


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Greetings to all πŸ‘‹, I'm Ujwal Tewari.


I have been working in Reinforcement learning, control optimization-based techniques and multi-agent systems. In addition to this, I work in the real world deployment of AI-based models for automated control decision processes using both RL and evolutionary strategies in cases where human intervention would otherwise be difficult.

I have also been working as an AI Ambassador at Intel Corporation, a classroom mentor for the Deep Reinforcement Learning nanodegree at Udacity and a tech blogger at Medium in Analytics Vidhya.

Have worked in ML and Research as Applied Scientists for more than 4 years with good track record of ML papers in reputed conferences. Expertise in model development to deployment lifecycle My Interests are:

Machine Learning, Reinforcement Learning, Knowledge Graphs, Natural Language Processing and Computer Vision

Here is a bit about my interests and how to get in touch:

  • πŸ’¬ I am learning about Model deployment and integration cycles.
  • 🌱 I’m currently working on Multi-agent Reinforcement Learning, Dialog systems and Optimization based problems.
  • πŸ’¬ Ask me about NLP, Deep Neural Networks, GAN, Probabilistic Models and let's Collaborate to knock new ideas to code.
  • πŸ“« How to reach me: [email protected]

Ujwal Tewari Github Stats


Ujwal Tewari's Projects

deep-rl-keras icon deep-rl-keras

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

deeptraffic icon deeptraffic

DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.

dejavu icon dejavu

Audio fingerprinting and recognition in Python

dopamine icon dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

energyplus icon energyplus

EnergyPlusβ„’ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water use in buildings.

face_generation icon face_generation

In this project, we are going to define two adversarial networks, a generator and a discriminator, and train them until we can generate realistic faces.

firedup icon firedup

Clone of OpenAI's Spinning Up in PyTorch

flow icon flow

Computational framework for reinforcement learning in traffic control

gentrl icon gentrl

Generative Tensorial Reinforcement Learning (GENTRL) model

gym icon gym

A toolkit for developing and comparing reinforcement learning algorithms.

hanabi_sparta icon hanabi_sparta

Research code implementing the search AI agent for Hanabi, as well as a web server so people can play against it

handwritingrecognition-cnn icon handwritingrecognition-cnn

This CNN-based model for recognition of hand written digits attains a validation accuracy of 99.2% after training for 12 epochs. Its trained on the MNIST dataset on Kaggle.

horizon icon horizon

A platform for Applied Reinforcement Learning (Applied RL)

huskarl icon huskarl

Deep Reinforcement Learning Framework + Algorithms

imdb_in_keras icon imdb_in_keras

From a given dataset finding whether a review is positive or negative using keras.

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