Soumya Basu

Courses

Graduate Courses

• Fall 2018

  • Advanced Probability: Coupling in Markov Chains(Prof. Francois Baccelli)

• Spring 2018

  • Special Topics in Unsupervised Learning (Prof. Alex Dimakis)

• Spring 2017

  • Theory of Probbaility II(Prof. Gordon Zitkovic)

• Fall 2016

  • Theory of Probbaility(Prof. Gordon Zitkovic)

• Spring 2016

  • Theory of Computation(Prof. David Zuckerman)

  • Machine Learning with Large Data Set(Prof. Alex Dimakis and Prof. Constantine Caramanis)

    • Course Project: (with Vatsal Shah and Pranav Madadi)

      • Kaggle Santander Challenge: Predicting User Satisfaction

      • Kaggle Amazon Emplyoee Access Challenge: Predicting Resource Access Permission

• Fall 2015

  • Advanced Porbability in Learning, Inference and Networks (Prof. Sanjay Shakkottai)

    • Course Project: Power of Choices: Performance under Error and Compression (with Vatsal Shah)

  • Distributed Computing-I (Prof. Lorenzo Alvisi)

    • Course Project: System Implementation (with Arjun Anand)

      • Three Phase Commit: Atomic Commit Protocol

      • Paxos: Protocol for Consensus in Asynchronous System

      • Bayou: Eventually Consistent Consensus

• Spring 2015

  • Information Theory (Prof. Alex Dimakis)

  • Communication Networks: Analysis and Design (Prof. Gustavo de Veciana)

  • Advanced Algorithm (Prof. Evdokia Nikolova)

    • Course Project: Discrepancy Theory in Approximation Algorithms (with Rajat Sen)

• Fall 2014

  • Large Scale Optimization (Prof. Sujay Sanghavi)

  • Probability and Stochastic Processes-I (Prof. Sanjay Shakkottai)

  • Markov Chains and Mixing Time (Prof. Joe Neeman)

    • Course Project: A Review of the Mixing Time of Exponential Random Graphs

Undergraduate Courses

• Machine Learning

• Advanced Graph Theory

• Algorithms & Datastructure

• MIMO Communication

• Wireless Communication

• Digital Communication Networks

• Linear Algebra

• Probability and Statisticss

• Adaptive Systems & Signal Processing

• Digital Signal Processing