These days,

I recently returned from traveling, and these days, I’ve been expanding my skills through personal projects.

So far, I’ve completed two major projects: Brain Tumor Classification using a CNN Model for MRI Image Analysis and Detecting Sarcasm with AI: Building an LSTM Model for News Headlines. Currently, I’m working on two advanced ML projects that are pushing my skills to the next level:

1. Designing and developing a custom LLM for automated data analysis, a chatbot that performs statistical analysis, generates visualizations, and handles Excel datasets, while incorporating memory functionality to retain context from past interactions.

2. Building an ASR (Automatic Speech Recognition) system for Kirtan, a "Shazam-like" tool that generates text-based outputs from audio inputs, leveraging generative AI techniques.

These projects are particularly exciting because they represent a shift from single-outcome models (e.g., predictive or classification tasks) to more complex, generative systems. Both involve combining multiple layers of machine learning models into larger, interconnected systems—essentially creating neural networks of ML models. This approach challenges me to integrate individual models I’ve built into cohesive, multi-functional systems, marking a significant step forward in my technical growth.

Also, expanding on my interest for economic development, also working on a new case study. My previous case study—the Djibouti project for my economic development class—was entirely research-driven, grounded in data and analysis. But behind every data point are real people, real stories, and complexities that numbers alone can’t fully capture. Having just returned from Punjab, I wanted to take a different approach with this new case study—one that blends academic research with firsthand experience. This time, I’m not just analyzing data; I’m drawing from what I saw, the economic realities I witnessed, and the perspectives of those still living in Punjab, navigating its transformation in real-time. By bringing these elements together, I hope to create something deeper and more meaningful—one that bridges research with lived experience. But my vision goes beyond just a case study or machine learning applications. One day, I want to take these ideas—and many others—and turn them into action, whether in global warming & climate solutions, or broader economic challenges. And not alone, of course. The greatest privilege wouldn’t just be making an impact, but doing it alongside a team just as determined to change the world.