VK
Vinothkumar Kolluru
Also known as: Vinothkumar Kolluru
Fractal Analytics Artificial Intelligence Company, Stevens Institute of Technology, Mitsubishi Power, Ltd. (Japan)
Research areas: Computer Science · Computer Vision and Pattern Recognition · Internet of Things and AI · Network Security and Intrusion Detection · Advanced Neural Network Applications
0009-0006-1713-5720
Employment
-
Fractal Analytics Artificial Intelligence Company Senior Data Scientist2021 - Present
- 2018 - 2019
- 2017 - 2018
-
Stevens Institute of Technology Research Assistant
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (50)
- AI-enabled multi-class visual fault diagnosis for large-scale solar photovoltaic systems supporting energy transition and net-zero operations Save
- AI enabled geospatial intelligence for the energy transition: A comparative CNN study on CCUS, geothermal siting, and NetZero strategies Save
- Reinforcement learning guided active crop localization with CNN detectors and an interactive decision dashboard for precision agriculture Save
- AI—Prediction of Neisseria gonorrhoeae Resistance at the Point of Care from Genomic and Epidemiologic Data Save
- Response surface modeling of sodium hypochlorite-based manganese oxidation in drinking water Save
- AI-Based Brain Diseases Monitoring Device Save
- A Design of Hybrid Model and Bayesian Neural Networks for Smart Grid Stability Prediction Save
- AI-Driven Mobile Healthcare: Societal Impact, Workforce Adaptation, and Enhanced Predictive Modeling for Diabetes Risk Assessment Save
- Comprehensive Analysis of Mobile Phone Specifications: Trends, Clustering, and Market Insights Save
- Deep Learning-Based Vulnerability Detection for Web Application Security: A Dual-Stage Hamiltonian Neural Network Approach for SQLi and XSS Attacks Save
- Enhancing Real-Time Security Monitoring: A Hybrid Machine Learning Approach to Cyber Threat Detection Save
- Explainable Machine Learning Models for Phishing Website Detection: Enhancing Transparency and Accuracy in Cybersecurity Save
- Hybrid Approach of TabNet and Transformer-XGBoost for Predicting Traffic Flow in Smart Cities Save
- Hybrid Deep Learning for Multimodal Fake Profile Detection Using CNN-Transformer and Temporal Convolutional Networks Save
- Hybrid PCA-Based Machine Learning Models for Predictive Analytics in Urban Health Monitoring Systems Save
- Leveraging Software-defined Wireless Networks for Intelligent Resource Management in 5G and Beyond Wireless Networks Save
- Machine Learning for Fake Profile Users Detection in Social Network Systems: A Review and Implementation Phase Save
- OpIDS-DL: Optimizing Intrusion Detection in IoT Networks: A Deep Learning Approach with Regularization and Dropout for Enhanced Cybersecurity Save
- Optimizing Solar Radiation Forecasting for Renewable Energy Systems: A Comparative Analysis of Machine Learning and Feature Engineering Techniques Save
- Predictive Analytics in AI Marketing: Transforming Consumer Engagement Save