Nikhil Shekhawat

I'm a graduate research student at SRM Institute of Science and Technology in Chennai, where I lead a small team that mostly works on Autonomous Underwater Vehicles. As a SDE Intern at State Bank of India I've worked on financial forecasting and resource allocation strategies. I did my Bachelors in Computer Science at SRMIST, where I was advised by Dr Angayarkanni S. I've received the Top performer Award for batch 2021-25.

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My research interests span the fields of computer vision, deep learning, and NLP, with a strong focus on data-efficient learning strategies such as semi-supervised, unsupervised, and self-supervised approaches. I am particularly interested in designing intelligent systems and agents that can autonomously perceive, explore, and interact with their environments by using raw data and self-driven learning signals.

IEEE    

• Received Top Performer Award for Batch of 2021-25, SRMIST
• Won the Tenacity Award at TAC Challenge, an international subsea drone competition at Norway
  
• Technical Project Lead at SRMAUV, overseeing industry-level tasks such as subsea docking, pipeline inspection, and valve intervention
  
• Student research collaborator at The Directorate of Entrepreneurship and Innovation at SRMIST, for AI-Driven Debris Cleaning System, backed by DRDO and NIOT, with funding support of INR 9,00,000 from The SRM Innovation, Incubation, and Entrepreneurship Centre.
  

Developed a smart MAC protocol for underwater sensor networks using TDMA and multichannel strategies, boosting data flow and reducing collisions. Combined PSO, ACO, fuzzy logic, and GWO to improve routing, energy use, and communication efficiency in crowded, layered network environments.

Built an AI-driven traffic monitoring system using YOLOv8s for real-time helmet and license plate detection, achieving 93.7% accuracy. Combined CNNs and EasyOCR to maintain high performance in challenging conditions, with a mAP50 of 95.8% and robust recognition across varied environments.

Designed and tested banking tools to enhance functionality and user experience. Applied statistical analysis to build predictive models, enabling better financial forecasting and resource planning. Delivered data-driven insights to guide management decisions and improve overall operational efficiency.

Processed and prepared employee feedback for sentiment analysis using NLP techniques. Identified key sentiment trends and recurring concerns, delivering insights to boost satisfaction. Created detailed reports and visualizations with actionable recommendations for improving workplace engagement.