Dr. Venkata Phanikrishna B
Assistant Professor
Diu Campus
Computer Science and Engineering
Venkata Phanikrishna Balam received his doctorate in computer science and engineering from the National Institute of Technology Rourkela, India, in 2021. His master's degree (M.Tech.) was completed in Computer Science and Technology from Andhra University, Visakhapatnam, India, in 2013. He completed his graduation (B.Tech.) degree in Information Technology from Jawaharlal Nehru Technological University-Kakinada(JNTUK) at Kakinada, India, in 2010. At present, Venkata Phanikrishna is working as an Assistant Professor Grade-II in Computer Science and Engineering, Indian Institute of Information Technology, Vadodara-International Campus Diu (IIITV-ICD), DIU, India. Further, his research interests including bio-signal processing, pattern recognition, computer vision, the Internet of Things, and machine learning.
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Biosignal analysis with AI
AI-based biosignal analysis for safety-critical and medical applications, such as fatigue detection, health monitoring, and disease diagnosis.
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Remote sensing and sustainability applications using AI
AI-driven digital image analysis for remote sensing and sustainability applications, including solar panel monitoring, crop monitoring, environmental monitoring, traffic surveillance, and disaster management.
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Medical image and signal analysis
AI-powered medical image analysis (e.g., MRI, X-ray, CT, Ultrasound, PET, Histopathology) for applications such as brain tumor detection, lung disease diagnosis, and other healthcare-related tasks
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2021Ph.D.Computer Science and EngineeringNIT Rourkela
Machine Learning-Driven EEG Analysis for Early Detection and Prognostic Prediction in Parkinson’s Disease
Role: PI
Funding: IIIT Vadodara (250000)
3Years
Ongoing I am the Principal Investigator of a Faculty Initiation Grant (FIG) project titled “Machine Learning-Driven EEG Analysis for Early Detection and Prognostic Prediction in Parkinson’s Disease,” funded by IIIT Vadodara. Sanctioned Amount: ₹2.5 Lakhs | Duration: 3 Years | Status: Ongoing | Sanction Date: 24th November 2025, End date: 24th November 2028
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Automated EEG Signal Processing: A Comprehensive Investigation into Preprocessing Techniques and Sub-Band Extraction for Enhanced Brain-Computer Interface ApplicationsJournal of Neuroscience Methods (Publisher : Elsevier), 2025Journal
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Systematic Review of Single-Channel EEG-Based Drowsiness Detection Methods.IEEE Transactions on Intelligent Transportation Systems, 2024, 25Journal
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Statistical Channel Selection Method for Detecting Drowsiness Through Single-Channel EEG-Based BCI SystemIEEE Transactions on Instrumentation and Measurement, 2021, 70Journal
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Development of single-channel electroencephalography signal analysis model for real-time drowsiness detection.Physical and Engineering Sciences in Medicine(Publisher : Springer), 2021, 44Journal
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Deep Review of Machine Learning Techniques on Detection of Drowsiness Using EEG Signal.IETE Journal of Research, 2023, 69Journal
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Automated classification system for drowsiness detection using convolutional neural network and electroencephalogram.IET Intelligent Transport Systems, 2021, 15Journal
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Automatic Classification Methods for Detecting Drowsiness using Wavelet Packet Transform extracted time-domain features from Single-channel EEG Signal.Journal of Neuroscience Methods (Publisher : Elsevier), 2020, 347Journal
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Time Domain Parameters as a feature for single-channel EEG-based drowsiness detection method.2020 SCEECS, IEEE, MANIT, Bhopal, 2020Conference
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Drowsiness detection by analysis of EEG signal with the help of Machine Learning.ADCOM-2018, Advanced Computing and Communications Society (ACCS), IIIT, Bangalore, India, Sep. 21-23, 2018, 2018, 24Conference
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Dynamic Risk Stratification in ICU Sepsis: A Deep Reinforcement Learning Approach Using Synthetic Data.2025 IEEE International Conference on Recent Advances in Computing and Systems (REACS), Gwalior, India, Date of Conference: 19-20 December 2025, 2025Conference
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Analysis of EEG Signal for Drowsy Detection: A Machine Learning Approach.Soft Computing in Interdisciplinary Sciences. Studies in Computational Intelligence, 2022Book Chapter
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Advancements in electrocardiography-based detection of obstructive sleep apnea: a deep learning approach.Cutting-edge Computational Intelligence in Healthcare with Convolution and Kronecker Convolution-based Approaches, 2026Book Chapter
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Drone-Based Human Activity Classification Using Quantum Machine Learning for Smart City Security Applications: QRC-Based HAR.Securing Smart Cities With Quantum-Enhanced Deep Learning, IGI Global Scientific Publishing, 2027, 2026Book Chapter
| Organisation | Role | Since |
|---|---|---|
| Indian Society for Technical Education (ISTE) | Life Member | 2024 |
| International Association of Engineers (IAENG) | Life Member | 2024 |
| IEEE | Member | 2022 |
| Scholar | Topic | Degree | Year | Status |
|---|---|---|---|---|
| ILLA MAHESH KUMAR SWAMY (202491005) | Biomedical Signal Processing and Applications | PhD | 2024 | Ongoing |
| SAH SALONIKUMARI MANAGER (20252701001) | Intelligent and Adaptive Systems for Remote Sensing or Multi-Modal Data: Applications in Public Safety and Healthcare | PhD | 2025 | Ongoing |
| Tammineni Rama Tulasi (20252701006) | Artificial Intelligence for Safety, Security, and Sustainable Applications in Classical and/or Quantum Computing | PhD | 2026 | Ongoing |
| Mr. Surya Mahadev (2025263010) | AI in Image Analysis for Sustainability Applications in Agriculture | MTech | 2025 | Ongoing |