Hi! I'm Shivam, a recent graduate from BITS Pilani, Goa, with an M.Sc. in Mathematics and a B.E. in Electronics & Communication. I am into machine learning, deep learning, and programming.
I am currently an Associate Data Scientist at QuantumStreet AI, where I build machine learning solutions for financial data. Previously, I worked at Wadhwani AI, where I focused on Deep Feature Synthesis and its applications. I also gained experience as an SDE intern at Amazon and as a research collaborator at NTU Singapore. Through these roles, I have developed strong skills in Machine Learning and Programming.
I am passionate about learning and constantly seeking new challenges. My interests lie in Theoretical Deep Learning, Classical Machine Learning, and Applied Machine Learning for scientific research. If you're working on something interesting, please reach out to me. I'm always eager to collaborate and contribute, whether it's on theoretical/conceptual work or practical implementation. I'm enthusiastic about learning from new experiences and projects.
Currently, I'm learning about LLMs and trying to implement a few things. I'm also planning to pick up RL once I get time.
A Machine Learning Framework for Classroom EEG Recording Classification: Unveiling Learning-Style Patterns
Rajamanickam Yuvaraj, Shivam Chadha, et al.
Algorithms (MDPI)
A Chaos-Causality Approach to Principled Pruning of Dense Neural Networks
Rajan Sahu, Shivam Chadha, Nithin Nagaraj, Archana Mathur, Snehanshu Saha
Chaos Theory and Applications (CHTA)
A Machine Learning Framework for Classroom EEG Recording Classification: Unveiling Learning-Style Patterns
Rajamanickam Yuvaraj, Shivam Chadha, et al.
Algorithms (MDPI)
A Chaos-Causality Approach to Principled Pruning of Dense Neural Networks
Rajan Sahu, Shivam Chadha, Nithin Nagaraj, Archana Mathur, Snehanshu Saha
Chaos Theory and Applications (CHTA)
[R] is for Reproduction
Here's my CV.