Shrivarshan K Email & Phone Number

Chennai, Tn, In

Chennai, Tamil Nadu, India

Working on a survey paper - "Small Language Models (SLMs): A Comprehensive Survey"

Bengaluru, Karnataka, India

Key member of Demand Forecasting Team, leading development of Version 3 forecast engine and process automation● Engineered V3 forecasting model using NHITS, NBEATS, RNN, and GRU architectures, designing innovative bucketing strategies for accuracy and scalability● Achieved 16% reduction in Mean Absolute Percentage Error (MAPE) by expanding hyperparameter space and optimizing validation periods per bucket, driving an estimated $0.73M in revenue impact● Enhanced operational efficiency by 65% through automated workflow integration with Azure, reducing processing time from 35 hours to 12 hours

Chennai, Tamil Nadu, India

A key member of the founding team, instrumental in idealizing the outline of Trulio.io and driving AI-focused initiatives.Trulio.io, a groundbreaking SaaS product revolutionizing search automation on top e-commerce platforms like Amazon, Flipkart, Myntra, and more.Leveraging latest cutting-edge technologies like Gemini 1.5, roBERTa for precise product recommendation based on user queries.

Canada

Contributed to projects at Transportation Lab, SALMALIS, under Prof. Suliman Gargoum, focusing on traffic safety using advanced deep learning techniques. Worked on a journal paper “Enforcing Traffic Safety: A Deep Learning Approach using YOLOv8 and DCGAN”● Processed 100 videos (20,000 frames) of Indian traffic from the AI City Challenge 2023 dataset, covering seven distinct classes● Conducted model comparison (R-CNN, SSD, YOLO); implemented YOLOv8 for motorcyclist helmet detection, achieving 0.91 F1 score● Improved F1 score by 2.5% through DCGAN-generated synthetic images and augmentation to address class imbalance● Applied Test-Time Augmentation (TTA), leading to an additional 5.5% improvement; research findings published

Chennai, Tamil Nadu, India

Worked under Dr. Swaminathan, in collaboration with Team KAATRU, led by Prof. Raghunathan Rengaswamy.● Spearheaded the acquisition of high-resolution PM2.5 data for Ambattur city at 250m spatial and 1hr temporal intervals through the deployment of cutting-edge IoT sensors.● Introduced a novel agent-based modeling approach, optimizing parameters with an Ordinary Least Squares method and achieving a remarkable MSE of 0.616.● Proficiently utilized GeoPandas for land-use data and the Google Maps API to extract traffic data for each of the 100 agents.● Elevated the modeling equation by incorporating crucial factors such as land-use and traffic data, leading to a substantial reduction in the model's MSE to an impressive 0.535.

Master'S Degree, Data Science

Bachelor'S Degree, Metallurgical And Materials Engineering

High School Diploma, Computer Science