Abhay Kshirsagar

Mumbai · Maharashtra · India · (+91) 9321201230 · ask19ms172@iiserkol.ac.in

I'm 4th year Integrated MS Student in Biological Sciences and Computational Data Sciences at IISER Kolkata. I'm interested in studying Biological Systems and Phenomenas using Machine Learning and Computational techniques. You can find my CV here .


Research Internship

  1. Learned about Molecular Dynamics Simulations for Biological Systems
  2. Learned and worked on some Deep Learning Frameworks for studying conformational landscape of protein like Time Lagged AutoEncoders (Noe. at. al. ) and AutoEncoders (Mondal et. al. )
  3. Worked on NSP1 protein of SARS-CoV-2, specifically its CTD which behaves like an IDR. We studied its conformational ensemble using an enhanced sampling method REMD and MD. We employed Expectation Maximized Molecular Dynamics to gain insights on its conformational landscape.
November 2021 - Present

NLP Researcher

  1. Worked on the core Data Science and NLP Engineering Team at wavel.ai.
  2. Learned how to create train and evaluate models and create pipelines for Text-To-Speech
  3. Learned about various state of the art TTS models for multilingual TTS and Voice Cloning Some of the models I Implemented were based on following architectures
Jun 2022 - Aug 2022

Summer Research Project Intern


Completed a two month research Internship under Dr.Jayasri Das Sarma (Dept. Biological Sciences) where I studied the effects of SARS-CoV-2 on humans with Murine-CoV as a model. Also gained insights on the lab methods for studying animal models for human diseases.

June 2020 - August 2020


Solar Power Prediction

SHELL.ai hackathon
My Submission to the Shell AI Hackathon for predicting Global Solar Irradiance and Cloud Coverage. Implemented Long Short Term Memory Networks on previous Data to Forecast Target Variables. My Team were selected to be finalist among Top 30 Teams. The Approach and the Certificate is provided in the Repository Below

 Project Link  Certificate

Wind Farm Layout Optimization program

SHELL.ai hackathon
My Submission to the Shell AI Hackathon for finding Optimum Wind Turbine Layout for maximum Annual Energy Production. In the Project I used a Stochastic Algorithm called Particle Swarm Optimization Algorithm (PSO)

 Project Link

Flappy Bird AI

Made an self Supervised AI that Plays the famous game Flappy Bird. The Program is build using NEAT Algorithm provided by the neat library.

 Project Link


Personal Team Project
A cli application built using Python for interacting with our Institutes Course Content Website on Welearn. The program uses Moodle Web Service API for downloading course content and making Google Calendar reminders for Assignment or Test Submissions.

 Project Link


Indian Institute of Science Education and Research Kolkata

Intergrated MSc
Majoring Biological Sciences and Minor in Computational Data Sciences

GPA: 8.73

August 2019 ~ present


Programming Languages & Tools
  • Android Development - Flutter and Dart
  • Web Development - Node and React (Limited Proficiency), LAMMP Stack
  • ML FrameWork - Tensorflow, PyTorch, PyTorch Geometric (Limited Proficiency)
  • Python libraries - Numpy, ScikitLearn, Pandas
  • Molecular Dynamics - GROMACS, VMD
  • Scientific Computing - MATLAB, Simulinks, OCTAVE (Limited Proficiency)
  • Database - SQL, NoSQL (Limited PRo)


Neural Networks and Deep Learning

Course taught by Andrew Ng from DeepLearning.ai. The Course gives an introduction to Basic Neural Networks and goes over Regression and Classification Examples using Python and its libraries like Numpy.


Machine Learning

Course taught by Andrew Ng from Stanford University. The Course goes over various Supervised (Regression, SVM, Kernels, NN) and Unsupervised Learning Algorithms (Clustering, Dimensionality Reduction, etc). It also dwells deep into best Practices and builds these foundations using plenty examples with MATLAB / OCTAVE.


Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

Course taught by Andrew Ng from DeepLearning.ai. The Course goes over standard Neural Network techniques and dives into how to improve the performance of the Deep Neural Network Blackbox. The Course uses many Examples to understand the improvements each modifications bring using ML FrameWorks such as Tensorflow.


Convolutional Neural Networks

Course taught by Andrew Ng from DeepLearning.ai. The Course goes over CNN and how it revolutionized the field of Computer Vision. The course shows how to build CNN and Residual Networks to build projects such as Style-Transfer, Image and Video Detection, Image Semantic Segmentation using ML Framworks like Tensorflow.