I'm a final-year undergraduate student at Indian Institute of Technology, Jodhpur (India) pursuing Bachelor’s in Mechanical Engineering with Specialisation in Data Science.

I have been captivated by the intersection of technology and engineering throughout my academic career. I believe the solution to today's complicated problems lies in harnessing the power of data and using it to encourage innovation. I have a strong foundation in problem-solving and analytical thinking, thanks to my undergraduate journey which has allowed me to delve even further into the world of algorithms, data science, and predictive modelling.

As I approach the end of my undergraduate journey, I am excited about the endless possibilities that lie ahead. I hope to contribute to innovative projects that make a positive impact on society while continuously learning and pushing the boundaries of what is possible.

My current areas of interest include:
  • Machine Learning
  • Deep Learning
  • Large Language Models
  • Reinforcement Learning
  • NLP
During my time as a student, I got opportunities to expand my knowledge and gain practical experience. Such opportunities included my role as a Data Science and Machine Learning intern. This experience allowed me to work on real-world projects, collaborating with a team to analyse and extract insights from large datasets. It was during these internships that I discovered my passion for using Machine Learning and Deep Learning techniques to uncover patterns and make data-driven predictions.

I was awarded the MITACS Globalink Research Internship by MITACS Canada. I was chosen amongst students from 16 countries to undertake a summer internship at University of Calgary, Canada.


Coursework:

These are the courses I have taken in my academic education, at workshops, internships, and extracurricular coursework in addition to self-study.

  1. Advanced Machine Learning
  2. Data Structures and Algorithms
  3. Introduction to Computer Science
  4. Introduction to Generative AI
  5. Introduction to Deep Learning
  6. Statistical Inference and Simulation Techniques
  7. Introduction to Machine Learning
  8. Introduction to Data Science
  1. Software Engineering
  2. Operating Systems
  3. Database Management Systems
  4. Calculus and Linear Algebra
  5. Software Architecture & Technology of Large-Scale Systems
  6. Scientific Computations
  7. Time Series Analysis
  8. Optimisations