Faculty

Core Research Domains

• Deep Learning
• Machine Learning
• Artificial Intelligence and its Real-World Applications
• Natural Language Processing & Sentiment Analysis
• Computer Vision & Object Detection

Research Focus

Mr. Hemanth’s research focuses on applying Deep Learning and Machine Learning techniques to solve critical real-world challenges. His key works include:

• Marine Plastic Detection: YOLOv8-based deep learning model achieving 88% precision — awarded Best Paper at IEEE ACCESS 2025.
• Drug Recommendation System: An ML-based system leveraging sentiment analysis on patient reviews to enhance medication safety (published in IJSDR, Impact Factor: 9.15).
• Smart Emergency Navigation: AI-powered emergency location sharing and navigation system (Sarathi).
• Multi-Platform Price & Sentiment Analysis: AI-based assistant for price comparison and sentiment analysis (Best Buy).

Journals and Conferences

• Sarathi: A Smart Emergency Location Sharing and Navigation System. IJARSCT, Vol 6, Issue 9, March 2026. DOI: 10.48175/IJARSCT-32733
• Best Buy: An AI-Based Multi-Platform Price and Sentiment Analysis Assistant. IJARSCT, Vol 6, Issue 9, March 2026. DOI: 10.48175/IJARSCT-32715
• ML-based Drug Recommendation System. Published in IJSDR (Impact Factor: 9.15). Developed a system using sentiment analysis on patient reviews to improve medication safety.
• Deep Learning-based Marine Plastic Detection using YOLOv8 Models (Best Paper Award – IEEE ACCESS 2025). Achieved 88% precision.

Awards & Recognitions

• Best Paper Award – IEEE ACCESS 2025: Awarded for research on Deep Learning-based Marine Plastic Detection using YOLOv8 models, achieving 88% precision.

Core Technical Skills

Programming Languages

• C, C++, Java, Python

Computer Science Domains

• SQL, FLAT, Compiler Design, Machine Learning

Tools & Operating Systems

• Git, Ubuntu, Linux, Windows

Soft Skills

• Team Management, Public Speaking, Academic Mentoring