HEY,
I'M SRINIVAS!
Data Scientist | AI Researcher | Data Blogger | Speaker
Exploring Data-Driven Solutions Through Research and Collaboration
Journey So Far
My journey in data science and artificial intelligence began with a Bachelor of Technology in Information Technology from SSN College of Engineering, which laid a robust foundation for my future endeavors.
Early Research Experience
In 2019, I gained early research experience as a research intern at IIITDM Kanchipuram (Indian Institute of Information Technology, Design and Manufacturing). During that time, I authored two papers—one on face recognition in the NIR domain and another on CSFR—that contributed significantly to my growth in data science and helped shape my career path.
Industry Experience
As a Senior Data Engineer at LTIMindtree, I was an integral part of the Data Centre of Excellence. Over a three-year tenure, I worked at the bleeding edge of data innovation with Snowflake—playing a crucial role in building models that helped optimize cloud compute and storage costs for several companies. In addition to driving cost-efficiency, I also focused on developing ethical AI solutions. I devised and implemented modules to detect and mitigate bias across the machine learning pipeline, enhancing model fairness and reliability. My expertise in Snowflake was further showcased through multiple internal talks on Snowpark and Snowflake, as well as several blogs published on the company site.
Graduate Studies & Advanced Research
Building on this industry experience, I am currently pursuing my Master’s in Data Science at Rutgers University. In the Spring of 2024, I served as a research assistant in the Rutgers Public Informatics department. There, I helped organize RAISE 2024—a public informatics data science competition—and co-authored a research paper exploring how news media narratives can propagate fear around artificial intelligence using advanced NLP, ML, and LLM techniques.
Current Research Initiatives
Since Fall 2024, I have been working as a research assistant in the Rutgers Department of Chemical and Biochemical Engineering on several NSF-funded projects. My current research leverages deep learning and LLM-based approaches to tackle challenges such as document similarity and complex panel assignment problems.
Advocacy and Lectures
Beyond my technical and research pursuits, I have a deep passion for sharing knowledge. I enjoy giving talks and have delivered multiple presentations at SSN College of Engineering on topics like the age of AI and preserving speaker characteristics in multilingual translation. These experiences continue to inspire my commitment to advancing data science and ethical AI.
Projects
Latest Research
This study investigates how news media shapes public perceptions of artificial intelligence by analyzing 70,000 headlines using NLP, machine learning, and large language models. The findings reveal that many headlines use fear-inducing language, often portraying AI as dangerous, which can skew public opinion and impact policy. The study concludes with recommendations for educational and policy reforms to support human identity and dignity.
Cross-Spectral Face Recognition (CSFR) tackles the challenge of matching face images from the VIS and NIR spectra, crucial for day–night surveillance.
This paper introduces a lightweight CNN that outperforms denser networks on benchmark datasets—achieving 97.12% to 99.85% accuracy with only 102 thousand parameters.
This paper addresses the limitations of visible spectrum face recognition caused by environmental lighting by leveraging near-infrared (NIR) imaging. It introduces an end-to-end light CNN architecture specifically designed for NIR face recognition, achieving impressive accuracies on challenging public datasets such as CASIA NIR VIS 2.0 (98.16%), Oulu CASIA (99.26%), PolyU (97.90%), CBSR (98.22%), and HITSZ (99.72%).