About Me

Hi, I'm Ansh! I'm from Chicago, IL. I'm currently an incoming undergraduate at the University of Illinois Urbana-Champaign studying Computer Science. I just finished interning at Smartlinx, a workforce management solutions company, where my main project was to build a virtual clock system enabling a cross-building clock-in service for over 500K users, enhancing employee convenience and reducing building constraints.

I love working on projects that I am passionate about on the side. Most recently, I got my article published in the Journal of Student Research titled, "Using a Predictive Model to Reduce Emissions/Energy Costs with Virtual Power Plants in North India," where I developed a Machine Learning model with 98.89% accuracy in predicting emissions/cost, demonstrating the potential of Virtual Power Plants to reduce pollution in developing countries.

I love exploring new technologies and am currently fascinated by Virtual Power Plants, applications of Machine Learning in fintech, and Caleb Williams' Super Bowl run with the Bears (I'm still delusional). I am a huge NFL football fan. You'll find me glued to the nearest TV, computer, or phone streaming multiple games at once. It's the best way to root for my favorite players who are all coincidentally on my team now and hang out with friends. Can't wait for UIUC games!

I love writing articles on Medium.com about Machine Learning and AI. It's an outlet to provide others who might not have a technical background with info about how our future innovations run behind the scenes. But even more than that, it's an opportunity for aspiring engineers, including myself, to strengthen their foundational knowledge and build off of that.

I love talking about tech, products, stocks, and more. Feel free to connect with me over LinkedIn! Links to the left!

Experience

Smartlinx | June 2024 - August 2024

SWE Intern - Built a virtual clock system for over 500K users, enhancing convenience and reducing building constraints

Independent Research | June 2023 - September 2023

Researcher - Developed ML model with 98.89% accuracy in predicting gains in emissions/cost to reduce pollution in developing countries

Northwestern University | June-August 2022 & June-August 2023

Research Intern - Improved ML control system accuracy to over 99% for a Fermilab particle accelerator to enhance safety measures

University of Illinois Urbana-Champaign | February 2023 - June 2023

IOT Camp Instructor - Created and taught a 7-day Algorithms course covering essential computer science topics to high school students

SurePayroll | June 2021 - July 2021

SDE Intern - Developed a payroll info entry web page for 5000 accountants and collaborated with teams to enhance product quality

Projects

Using a Predictive Model to Reduce Emissions/Energy Costs with Virtual Power Plants in North India

June 2023 - September 2023

This project aims to reduce emissions and energy costs in India by optimizing power plant output using Mixed Integer Linear Programming. The approach creates Unit Commitment (UC) and Economic Dispatch (ED) schedules to determine which plants should operate and at what levels. By recalibrating energy usage based on real-time data, such as demand and weather, UC/ED helps stabilize the grid while minimizing energy consumption.

Technologies Used: Python, Gurobi, BEOPT Tool, Excel

View on GitHub View Publication

Next project is going to be a Fantasy Football Player Score Predictor so you can accurately choose which player to start at what position using real life data instead of "a hunch."

Fantasy Football Score Predictor (Full PPR)

My Team

  • Quarterback: Jordan Love
  • Running Back: Breece Hall
  • Running Back: De'Von Achane
  • Wide Receiver: Marvin Harrison Jr
  • Wide Receiver: DK Metcalf
  • Tight End: Trey McBride
  • Flex: James Conner
  • Defense: Bengals
  • Kicker: Tyler Bass

Team Image