Welcome to
Visual Computing & Robotics Lab
Welcome to
Visual Computing & Robotics Lab
Focus: Designing robust, interpretable, and real-world deployable AI systems.
Machine Learning & Deep Learning
Uncertainty-Aware Neural Networks
Large Language Models (LLMs)
Generative AI
Explainable Artificial Intelligence (XAI)
Optimization-Based Learning (Metaheuristics, GWO)
Trustworthy & Responsible AI
Focus: Secure identity systems and multimedia authenticity verification.
Person Re-Identification
Person Authentication
Face & Gait Recognition
AI-based Cattle Identification
Livestock Monitoring Systems
Visual Surveillance & Activity Monitoring
Anomaly Detection in Videos
Real-Time Security Systems
Forensic Audio & Video Analysis
DeepFake Detection
Audio-Video Integrity Verification
Focus: AI-powered precision diagnostics and computational biology.
Protein Function Prediction
Protein Secondary Structure Classification
Sequence Modeling with Attention Mechanisms
Cancer Cell Classification
Tumor Detection & Segmentation
Retinal Disease Detection
Lung Disease Classification
Uncertainty-Aware Medical AI
Attention-Augmented Segmentation Networks
Focus: Next-generation AI systems for reasoning and content synthesis.
Large Language Models
Generative AI Systems
DeepFake Detection
Explainable & Interpretable AI
Focus: AI-enabled automation and smart mobility platforms.
Line Follower Robots
Object Detection Robots
Drone Technology & Aerial Surveillance
Autonomous Vehicles
Human-Robot Interaction
Focus: Advanced visual intelligence systems for environmental and industrial applications.
Image Processing & Enhancement
Object Detection & Tracking
Real-Time Activity Detection
Remote Sensing Image Analysis
SAR + Deep Learning
Agriculture Applications (Crop Health Monitoring, Disease Detection)
Environmental Monitoring Systems
Focus: AI-driven sensing and object detection in challenging environments.
Underwater Object Detection
Sonar Sensor Signal Processing
Acoustic Image Analysis
Marine Surveillance Systems
Radar Signal Processing
Target Detection & Classification
AI for Radar-based Surveillance
Multi-Sensor Data Fusion (Radar + Vision + Sonar)
Faculty & Lab Coordinator
Dr. Gautam Kumar, Assistant Professor, Department of Computer Science and Engineering, NIT Delhi
Dr. Rishav Singh, Indian Institute of Technology Patna
Dr. Chandra Prakash, Department of Computer Engineering, SVNIT, Surat Gujarat
Dr. Sambit Bakshi, National Institute of Technology Rourkela
Dr. Rahul Raman, Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram
Dr. Deepak Ranjan Nayak, Malaviya National Institute of Technology, Jaipur
Dr. Abhinav Kumar, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India-211004