About me
Glad that you could join me here! My inspiration for working in the field of Machine learning and AI stems from the belief in conducive symbiosis between humans and machines. Humans do have some predictive blindspots and shortcomings and machines can fill in the gap which will for sure propel the human civilization forward.
Currently, I am a grad student in Data Science at Indiana University, Bloomington. I have previously applied the concepts of AI in multiple domains which you can find in my project section. Also, I like to write down my thoughts and I am a part-time blogger. You can find the link to my blogs here and Medium blogs.
Blog Posts and Publications
- Published paper on a novel data-driven method for analysis of Evacuated U-tube Solar collector Link to publication.
- Contributed guides and tutorials to FinRL on Hyperparameter tuning , XARL and data streaming
- Explanations of Reinforcement learning algorithms like Policy gradient, DDPG, SAC and Trust region methods stories list
- Introduction to Deep Reinforcement learning in finance Part I and Part II
- Wrote other articles like Apple's CSAM detection, AI threats, Simulation argument. You can find more in my blogs
Projects
- Financial Reinforcement learning using Google trends data research project with Professor Damien Ernst, Unviersity of Liege
- Financial Reinforcement learning explainability link
- Financial hyperparameter tuning using Optuna, Ray tune, W&B and population based algorithms
- Financial data streaming using Alpaca Project link
- Research publication on Evacuated U-tune Solar Collector, Github and paper link
- Computer Vision Papers Summary, link
- Anomaly Detection in a Baldwin Pump, project link
- Politeness Modelling using transformer models, Github link
- Naive Bayes Model implementation from scratch project link
- Verge Website automated scraper using Selenium project link
- Twitter Scraper using Tweepy, Github link