AI · Machine Learning · Deep Learning · Research · Teaching · Innovation
Ph.D Academician · 9+ Years Teaching · 2 Years Industry · 24+ Publications · MVGR
I am a Ph.D-qualified academician and researcher blending 9+ years of teaching excellence with 2 years of industry experience in AI, Machine Learning, and Deep Learning. My focus lies in building adaptive, explainable AI systems that bridge cutting-edge research with real-world healthcare applications.
Serving as Distinguished Assistant Professor at MVGR College of Engineering, Vizianagaram, I have mentored 500+ students and published 24+ peer-reviewed research papers in reputed international journals and conferences.
Leading academic delivery in AI, ML, Deep Learning and Cybersecurity. Conducting lab instruction & practical sessions. Mentoring UG/PG students through research projects. Publishing peer-reviewed papers in reputed journals. Active in institutional committees, quality improvement initiatives (NBA/NAAC).
Jawaharlal Nehru Technological University Kakinada — University College of Engineering Vizianagaram. Delivered undergraduate engineering courses in Computer Science.
Conducted security assessments, vulnerability analysis, and penetration testing for enterprise clients. Provided strategic information security advisory services.
Developed and maintained web applications for clients. Front-end and back-end development, database integration, and deployment.
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ML and deep learning models for disease detection, ECG classification, Parkinson detection, depression prediction, and intelligent clinical decision support.
Image classification, object detection, skin disease identification, and biomedical image analysis using CNNs and vision transformers.
ECG, EEG, and physiological signal processing using deep learning for real-time health monitoring and intelligent diagnosis systems.
Developing transparent ML models using SHAP, Grad-CAM, LIME, and counterfactual explanations for trustworthy AI in critical decision environments.
Integrating cryptographic protocols and cybersecurity with AI/ML for privacy-preserving, adversarially robust, and trustworthy intelligent systems.
Federated learning architectures, edge intelligence, and distributed AI frameworks with differential privacy and secure aggregation protocols.
>> 20+ peer-reviewed publications · International journals & conferences
A Blockchain-Based Solution for Employee Performance Management using smart contracts and decentralized ledger technology.
Offline Multilingual AI Tutor Using Local RAG and Voice Interaction for rural and low-connectivity environments.
Multi-Agent AI System for Automated Requirement Gathering and Project Coordination using LLM-based agents.
Web-Based AI Task Planning System with Microservice Architecture and Roadmap Visualization using reinforcement learning.
Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environments with adaptive scheduling.
Comprehensive Digital Signature Framework for Network Security using asymmetric cryptography and PKI infrastructure.
Classification of Cardiac Arrhythmia Patients Using Hybrid Machine Learning Features validated on PhysioNet MIT-BIH dataset.
Prediction of Depression and Suicide Ideation Using Machine Learning-Based Self-Efficacy Analysis on social media text.
Analysing COVID-19 Cases by Eliminating False Negatives and False Positives Using Visual Exploratory Data Analysis.
Skin Disease Prediction and Classification Using Deep Learning Techniques with Grad-CAM interpretability on HAM10000.
Parkinson’s Disease Diagnosis Using Voice Recordings and Ensemble Machine Learning Techniques achieving 96.3% accuracy.
Performance Evaluation of Machine Learning Algorithms for Credit Card Fraud Detection on highly imbalanced financial datasets.
Plagiarism Detection Using Natural Language Processing (NLP) with BERT contextual embeddings and semantic similarity.
Impact Analysis of Social Media on Human Behaviour Using Machine Learning and sentiment analysis techniques.
Machine Learning-Based Detection of Genetic Variants in Cancer and Inherited Disorders using genomic data analysis.
Deep Learning Approaches for Drug Repurposing using graph neural networks and biomedical knowledge graphs.
Election Prediction Using Social Media Data Analytics and Machine Learning with real-time sentiment monitoring.
Detecting Spam Zombies through Monitoring of Outgoing Messages using network traffic analysis and anomaly detection.
Managing social media presence, department outreach programs, and external communication for the CSE department.
Coordinating placement activities, industry liaisons, mock interviews, and career development programs.
Overseeing final year project allocations, student-industry collaboration, project evaluations and mentoring.
Managing alumni relations, organizing alumni meets, building a strong alumni network for mentoring current students.
Active contributor to professional engineering community through IEI membership and national events.
Telugu (Native) · English (Proficient). Delivering academic content and research publications in both languages.
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