Hi! I am an AI engineer and junior researcher specializing in artificial intelligence, robotics, and signal processing. I have recently completed my Bachelor of Science in Robotics and Artificial Intelligence at AMET University, Chennai.

Guided by distinguished mentors such as Dr. Thawseeak Yingthawornsuk, Dr. Malathy Batumalay, and Dr. Duraimutharasan, my research covers advanced deep learning applications for tsunami prediction, mental health diagnosis using EEG and ECG signal analysis, and extremism detection via large language models.

I have authored over a dozen research papers, including award-winning studies on psychological stress detection, tsunami forecasting, and depression detection. My current focus includes developing lightweight AI models for edge deployment in biomedical signal processing, along with secure communication solutions for defense applications.

Motivated by a commitment to social impact and the United Nations Sustainable Development Goals (UN SDGs), I strive to create AI-driven innovations that address healthcare, security, and disaster management challenges, with a strong emphasis on ethical, practical, and scalable technology solutions.

I believe collaboration and cutting-edge research are vital to solving today’s global challenges and responsibly advancing technology.

🔥 News

• 2026.01: 🎉🎉 Paper accepted at iEECON 2026: Secure Acoustic Communication with Frequency-Hopping and Steganography for Underwater and Terrestrial Environments
• 2026.01: 🎉🎉 Paper accepted at iEECON 2026: Multi-Class Classification of Low-Frequency Hum in Electromagnetic Interference Using Hybrid Deep Learning Models
• 2026.01: 🎉🎉 Paper accepted at iEECON 2026: Deep Learning-Based Classification of Cardiac Arrhythmia in ECG Samples
• 2025.05: 🎉🎉 Paper accepted by Journal of Applied Data Sciences (Q2): Study of Machine Learning Techniques for Predicting Panic Attacks with EEG and Personalized Binaural Beat Frequencies
• 2025.02: 🎉🎉 Paper accepted by Journal of Applied Data Sciences (Q2): A Study of Unified Framework for Extremism Classification, Ideology Detection, Propaganda Analysis, and Flagged Data Detection Using Transformers.
• 2024.12: 🎉🎉 Paper accepted by iEECON 2025: A Study of Deep Learning Models for Identifying and Estimating Psychological Stress and Disorders Using Electroencephalogram Signals.
• 2024.12: 🎉🎉 Paper accepted by iEECON 2025: Intelligent Flagged Content Detection with Transformer-Based Models for Secure Online Environments.
• 2024.08:   🎉🎉 Paper accepted by GCMM 2024: Precision Tsunami Prognostication: A Machine Learning Expedition for Predictive Accuracy.
• 2024.03:   🎉🎉 Paper accepted by ICLIST 2024: Deep Learning-Based Predictive Modeling for Male Depression Detection.
• 2024.02:   🎉🎉 Paper accepted by IEECON 2024: Data Analytics and Machine Learning Approach for Tsunami Prediction from Satellite and Hydrographic Data.
• 2024.01:   🎉🎉 Paper accepted by JETIR: A Web-Based Doctor Appointment System.

🔧 Work Going On

• June 2024: Developed mental health solutions leveraging physical sensors and EEG data using advanced machine learning and deep learning techniques. Delivered 2 research papers under supervision of Dr Thawseeak Yingthorsuk and Ir.Dr. Malathy Batumalay.
• July 2024: Advanced detection models for extremism, propaganda, radicalization, and flagged content using large language models (LLMs). Published 1 research paper, supervised by Dr Thawseeak Yingthorsuk and Ir.Dr. Malathy Batumalay.
• December 2024: Enhanced flagged data monitoring system with robust multilingual support to improve content security and moderation.
• May 2024 – March 2025: Working on cutting-edge ECG and EEG signal analysis for cardiovascular and neurological disorder detection by integrating lightweight, edge-deployable AI models.
• April 2025: Integrated VetraSync, a secure, low-latency sound data transfer protocol, to enhance real-time communication capabilities.
• May 2025: Developed and optimized baby cry detection models for real-time audio analysis applications.
• June 2025 - Present: Developing SXEcho Lite, a lightweight data-over-sound communication system enabling secure, low-bandwidth transmission through audible and ultrasonic frequencies using adaptive modulation and advanced error correction.
• February 2026 - Present: Developing Admissibility Verification, a framework for evaluating the stability of deep neural network representations under structured perturbations, introducing a novel admissibility formula for detecting silent representation collapse through geometric similarity analysis.

  📝 Publications

• JETIR A Web-Based Doctor Appointment System, Journal of Emerging Technology and Innovative Research.
• IEEE Data Analytics and Machine Learning Approach for Tsunami Prediction from Satellite and Hydrographic Data, International Electrical Engineering Congress (IEECON) 2024, Pattaya, Thailand.
• ICLIST Deep Learning-Based Predictive Modeling for Male Depression Detection, International Journal of Educational Communications and Technology IJECT. Presented at the ICLIST 2024 7th International Conference on Learning Innovation in Science and Technology, Chonburi, Thailand, March 21-23, 2024.
• GCMM Precision Tsunami Prognostication: A Machine Learning Expedition for Predictive Accuracy, 18th Global Congress on Manufacturing and Management (GCMM 2024), Bangkok, Thailand, December 4-7, 2024.
• JOIT Deep Learning-Based Predictive Modeling for Male Depression Detection, Journal of Information Technology, February 2025.
• IEEE Intelligent Flagged Content Detection with Transformer-Based Models for Secure Online Environments, International Electrical Engineering Congress (IEECON), Hua Hin, Thailand, March 5-7, 2025.
• IEEE A Study of Deep Learning Models for Identifying and Estimating Psychological Stress and Disorders Using Electroencephalogram Signals, International Electrical Engineering Congress (IEECON), Hua Hin, Thailand, March 5-7, 2025.
• IEEE Poland Section Deep Learning Model Performance on Critical Arrhythmia Detection Using CNN and WaveNet, Submitted.
• JADS A Study of Unified Framework for Extremism Classification, Ideology Detection, Propaganda Analysis, and Flagged Data Detection Using Transformers, Journal of Applied Data Sciences (Q2), Accepted.
• JADS Study of Machine Learning Techniques for Predicting Panic Attacks with EEG and Personalized Binaural Beat Frequencies, Journal of Applied Data Sciences (Q2), Accepted.
• IEEE Access The Study of Lightweight and Advanced Deep Learning Models for Accurate Classification of Cardiovascular ECG Rhythms, Submitted.
• BBEMS-2025 Deep Learning-Based Classification of Premature Ventricular Contractions and Supraventricular Tachycardia Using ECG Signals, Bangkok, Thailand, Published.
• Secure Acoustic Communication with Frequency-Hopping and Steganography for Underwater and Terrestrial Environments, Submitted to IEEE Thailand Section, 2026
• Multi-Class Classification of Low-Frequency Hum in Electromagnetic Interference Using Hybrid Deep Learning Models, Submitted to IEEE Thailand Section, 2026
• Deep Learning-Based Classification of CardiacArrhythmia in ECG Samples, Submitted to IEEE Thailand Section, 2026

🎖 Honors and Awards

• 2026.02, Presidential Acknowledgement, France Received a formal letter from the Office of the President of France acknowledging my academic work and conveying encouragement for the continuation of my research and professional initiatives. Issued by the office of Emmanuel Macron.
• 2025.07, AGMA Young Maritime Leadership Award – Awarded at the AMET Global Maritime Awards 2025 for AI innovations in signal systems. Jury included Prof. Dr. Gabriel Raicu (Rector, Constanta Maritime University, Romania) and Prof. Stephen Hurd (Director, Centre for Seafaring and Maritime Operations, UK).
• 2025.05, Featured Innovator – Dina Thanthi (Tamil Daily Newspaper, 1 Crore Readers), recognized for developing a lightweight, highly accurate heart diagnostic software.
• 2025.04, Letter of Appreciation, INTI International University, for pioneering ultra-lightweight AI models for real-time ECG analysis.
• 2025.03, Best Paper Award at IEECON 2025, Hua Hin, Thailand, for “A Study of Deep Learning Models for Identifying and Estimating Psychological Stress and Disorders Using Electroencephalogram Signals.”
• 2024.12, Best Paper Award at GCMM 2024, Bangkok, Thailand, for “Precision Tsunami Prognostication: A Machine Learning Expedition for Predictive Accuracy.”
• 2024.03, Best Paper Award at ICLIST 2024, Chonburi, Thailand, for pioneering research on Deep Learning-Based Predictive Modeling for Male Depression Detection.
• 2023.03, Contributor, ICFDTSD 2023 Conference, recognized for significant insights into sustainable development.
• 2023.03, Guest Speaker, Cyber Conference 2023 hosted by the Tamil Nadu Police Department, where I presented on cybersecurity advancements and practices.

📝 Letters of Recommendation

• 2025.03, Prof. Dr. Waraluk Pansuwan (Dean, SOAD, King Mongkut’s University of Technology Thonburi, Thailand) – Recommendation for pioneering work on novel hybrid deep learning architectures for automatic cardiac arrhythmia classification, including a lightweight model capable of detecting over 20 cardiac conditions optimized for low-resource devices.
• 2024.12, Prof. Ir. Dr. Malathy Batumalay (INTI International University, Malaysia ) – Letter of Recommendation highlighting my excellence in AI-driven healthcare innovations and collaborative research impact.
• 2024.05, Prof. Dr. Duraimutharasan (Dean, AMET University, India) – Recommendation recognizing my diverse technical skillset, commitment to the United Nations Sustainable Development Goals (UN SDGs) and describing me as an invaluable asset to the academic and research community.
• 2023.09, Prof. Dr. Thawseeak Yingthawornsuk (King Mongkut’s University of Technology Thonburi, Thailand) – Letter of Recommendation for significant contributions in machine learning, deep learning and data analytics applied to tsunami prediction, mental health diagnostics and other AI-driven research.

📖 Educations

• 2022.08 - 2025.07, Bachelor of Science (GPA: 3.53/4.00, US Equivalent), Major in Robotics and Artificial Intelligence; Minors in Mathematics, Physics, Electrical. AMET (Academy of Maritime Education and Training) University, Chennai, Tamil Nadu, India. Coursework Project: Developed “Rishiverse,” an AI-driven chatbot for aviation queries using deep learning and NLP, LLM-Based Intelligent Detection of Flagged Content for Secure and Safe Online Environments

💬 Invited Talks

• 2023.03, Cyber Conference 2023, Tamil Nadu Police Department, Government of Tamil Nadu — Presented on advancements and best practices in cybersecurity.
• 2025.07, Guest Speaker, EDII – Government of Tamil Nadu — Spoke on “The Brain Behind the eV”, sharing insights on AI-driven advancements in electric vehicle technology and sustainable innovation.

💻 Work Experience

• 2025.06 - Present, CIO, Altruisty Innovation Pvt Ltd.
• 2022.03 - Present, Director, Trekcodes (8-employee venture - AI Startup), Chennai, India.
• 2020.01 - Present, Technical Specialist, Gandhi World Foundation (NGO), Chennai, India.

💻 Internships

• 2025.01 - 2025.06, Junior Research Fellow, King Mongkut’s University of Technology Thonburi, Bangkok City, Thailand, Supervised
• 2024.08 - 2024.10, Artificial Intelligence Engineer Intern, Industrial & Commercial Waste Disposal Pte Ltd, Singapore.
• 2024.07 - 2024.08, Web Developer Intern, QuantPro Global Pvt Ltd, Bangalore, India.
• 2023.12 - 2024.06, Volunteer Web Developer & Research Intern, CLAW Global, Dehradun, India.
• 2023.06 - 2023.09, Research Intern, King Mongkut’s University of Technology Thonburi, Bangkok City, Thailand, Supervised by Dr Thawseeak Yingthorsuk.