Srivathsan (Sri) Badrinarayanan
AI Engineer | Data Scientist | Researcher
Master's Student - AI Engineering + Chemical Engineering
Carnegie Mellon University
About Me
I am an AI engineer specializing in machine learning and data science, with a focus on solving complex, real-world challenges in chemical engineering, life sciences, and beyond. My expertise spans deep learning, generative AI, and multimodal models, which I leverage to develop innovative AI solutions that bridge domain-specific knowledge with cutting-edge technologies.
Research Interests
My research interests center on AI4Science and Generative AI. My work spans across two main categories:
AI for Science
I explore the intersection of multimodal transformers and graph neural networks (GNNs) to predict protein properties and optimize catalyst designs, advancing both bioinformatics and materials science.
Generative AI/LLMs
I also work on enhancing generative AI capabilities, including large language models (LLMs) for applications such as automated creation of presentations and text-to-speech systems for audio-form generation.
Skills
Generative AI
Transformer models and large language models (LLMs), applied to real-world problems in science and engineering.
Deep Learning
CNNs, RNNs, GNNs for processing images, sequences, and graphs, including time-series modeling for predictive analytics
Tools & Frameworks
PyTorch, TensorFlow, Keras, HuggingFace, AWS, and scikit-learn for building and deploying machine learning models
Data Science & Analytics
Python, R, and SQL for data wrangling, visualization, and performance evaluation to inform strategic decisions