Education

A concise collection of my relevant academic courses throughout my undergraduate and masters.

Table of Contents

🎓 University of Southern California (USC)

I graduated with an MS in Computer Engineering, concentrating on Machine Learning.

  1. EE-660 Machine Learing II: Mathematical Foundations and Methods
    • Concentration Inequalities, VC-dimension, Stochastic Gradient Methods, Algorithmic Stability, PAC-Bayes Inequalities, Generative Models, Model Interpretability, Domain Adaptation, Multi-Task Learning …
  2. CSCI-662 Advanced Natural Language Processing
    • NLP Tools, Syntax, Semantics, Information Extraction, Generation (Machine Translation, Summarization, Dialogue, Creative Generation) …
  3. EE/CSCI-451 Parallel and Distributed Computation
    • Matrix Multiplications, Multi-threading, GPUs, Cloud, MapReduce …
  4. EE-559 Machine Learning I: Supervised Methods
    • Distribution-free and Probabilistic Methods for Supervised Classification and Regression, Learning Algorithms Optimization, Feature-Space Transformations, Parametric/Nonparametric Methods, Bayes Theory, Artificial Neural Networks …
  5. EE-503 Probability for Electrical and Computer Engineers
  6. EE-510 Linear Algebra for Engineering
  7. EE-450 Introduction to Computer Networks

🎓 Indian Institute of Technology (IIT) Delhi

I graduated with a Bachelor of Technology in Electrical Engineering, with a specialization minor degree in Cognitive and Intelligent Systems.

  1. ELL-890 Computational Neuroscience
  2. ELL-793 Computer Vision
  3. ELL-788 Computational Perception and Cognition
  4. ELL-729 Stochastic Control and Reinforcement Learning
  5. ELL-715 Digital Image Processing
  6. ELL-457 Optimization for Machine Learning
  7. ELL-409 Machine Intelligence and Learning
  8. COL-106 Data Structures and Algorithms