About

Hello World! My name is Mayank Jhamtani. My research interests lie broadly in the domain of Reinforcement Learning; Systems and Networks; Communication Systems and Coding Theory. I am currently in the final year of my Undergrad at BITS Pilani, Goa, pursuing a dual major in Mathematics and Electronics Engineering. You can find my detailed CV here

Education

M.Sc Mathematics(Hons) and B.E. Electrical and Electronics(Hons)

2015 - 2020
BITS Pilani, Goa.

Select Coursework - Object Oriented Programming, Statistical Inference, Discrete Mathematics Graphs Theory, Data Communication Networks, Signals and Systems, Control Systems, Reinforcement Learning [ = Online Course]

Experiences

Undergraduate Thesis

August, 2019 - Present
Indian Institute of Science, Bangalore

I am presently working on adaptive packet level FEC schemes for real-time applications, under the guidance of professor P V Kumar. I am responsible for implementing the high throughput encoding and decoding algorithms in C++, and integrating the code with an open-source application to benchmark the performance.

Summer Research Intern

May - July, 2018
Indian Institute of Science, Bangalore

I worked under the guidance of professor Parimal Parag in the Distributed Systems research group at ECE Department, IISc. The work involved using Coding Theory to analyze latency trade-offs in distributed storage frameworks, with a particular emphasis on Fountain Codes.

Instructor, Introduction to Programming

August - December, 2017
Centre for Technical Education, BITS Goa

As part of a college wide initiative, taught programming basics to more than 100 first year undergrads. The responsibilities involved designing lectures, assigning relevant reading material, conducting labs and exams to assess the learning outcomes. Repository. Certificate.

Data Analytics Intern

May - July, 2017
Adani Power, Nagpur

The work involved developing a prediction mechanism for electricity prices in the Indian Energy Exchange. The complete pipeline involved scraping online data, filtering noise, and making the final prediction system using Convolutional Nueral nets. Various architectures were tested on multiple metrics. Code. Report. Presentation.

Projects

Connect4 - RL Engines - Currently working on implementing various Reinforcement Learning based algorithms to play the board game Connect4
Network Simulation - Packet level network simulation done for indoor employee and resource monitoring system. Extended the NS3 Framework, which is a discrete event network simulator written in C++.
Universal Approximation Theorem for Neural Nets - Implemented a visual proof of the Universal Approximation Theorem, done in Matlab with interactive graphical illustrations

Awards

Mathworks Live Script Challenge

July, 2018

Won the third price in the international student competition organised by Mathworks. Code.

Skills & Proficiency

C++

Python

Java

Matlab