Robotics and AI Engineering student with hands-on experience in embedded systems, hardware integration, medical robotics, and precision measurement systems. Building intelligent solutions for medical and industrial automation.
Robotics and AI Engineering student specializing in autonomous systems, computer vision, and SLAM algorithms. Experienced in building complete navigation pipelines from sensor fusion to control implementation. Strong foundation in geometric computer vision, deep learning, and embedded systems with proven ability to develop end-to-end robotic solutions.
Navigation, SLAM, Sensor Fusion, Control Implementation
Geometric Vision, Deep Learning, Visual SLAM, Perception
ESP32, STM32, Arduino, Real-time Systems, Hardware Integration
System Design, Simulation, Field Testing, Full Stack Robotics
Funnel-based autonomous docking architecture for precision UAV landing and charging. Vision-based guidance, multi-stage controller, and robust mechanical alignment for ISRO URSC Challenge.
Developing funnel-based autonomous docking architecture for precision UAV landing and charging (ongoing). Designed passive mechanical alignment using center-of-mass stabilization for robust docking. Implementing belly-mounted E-pads with pogo-pin charging interface for reliable electrical connection. Creating vision-based guidance using ArUco markers targeting sub-5cm docking accuracy. Integrating multi-stage controller: GPS navigation, vision approach, and contact alignment. Testing in outdoor environments with wind conditions up to 5 m/s. Selected among top 177 teams from 2,000+ nationwide applicants for ISRO URSC 2025 Challenge.
Developed a robust Visual SLAM pipeline for real-time localization and mapping in unknown environments. Integrated ORB feature extraction, loop closure, and bundle adjustment for accurate trajectory estimation.
Designed and implemented a Visual SLAM system using ORB features, PnP, and bundle adjustment. Achieved real-time performance on embedded hardware. Demonstrated robust loop closure and map optimization in dynamic and low-texture environments. Used for autonomous navigation in indoor and outdoor robotics projects.
Browser extension for instant PDF section extraction, search, and copy. Works offline, supports local and online PDFs, auto-summary, multi-select, and edit-before-copy. No dependencies or external requests.
Technical: Parses raw PDF byte streams, decodes FlateDecode, ToUnicode CMap, and text operators. Supports local file:// PDFs via File API picker. Auto-summary scores sections by keyword and position, generates 5-bullet summary. Text reflow for clean copy. Fully self-contained, no server or sign-up.
Non-GPS localization system for indoor environments using UWB and LIDAR fusion. NLOS detection and correction with machine learning.
Built honeypot using NLP for attacker command analysis and threat classification. Developed Ethereum smart contracts for immutable security logging. Created threat scoring achieving 85% accuracy with real-time monitoring.
Autonomous UAV navigation with IMU, GPS, and camera fusion. AI-based path execution in ROS/Gazebo for complex scenarios.
Developing funnel-based autonomous docking architecture for precision UAV landing and charging (ongoing). Designed passive mechanical alignment using center-of-mass stabilization for robust docking. Implementing belly-mounted E-pads with pogo-pin charging interface for reliable electrical connection. Creating vision-based guidance using ArUco markers targeting sub-5cm docking accuracy. Integrating multi-stage controller: GPS navigation, vision approach, and contact alignment. Testing in outdoor environments with wind conditions up to 5 m/s. Selected among top 177 teams from 2,000+ nationwide applicants for ISRO URSC 2025 Challenge.
Mobile robot for sound source localization using audio signal processing. Integrated sound cues with obstacle avoidance and validated in ROS/Gazebo simulations.
Developed a mobile robot for sound source localization using audio signal processing. Integrated sound cues with obstacle avoidance and validated in ROS/Gazebo simulations.
Wearable system with IMU sensors and smart insoles for patient movement analysis. Sensor fusion and computer vision for posture/motion analysis and real-time feedback for clinicians.
Developed gait analysis fusing computer vision with IMU sensors at 30fps. Created ML model classifying gait abnormalities with 88% accuracy.
Platform for detecting image, video, and audio deepfakes using CNNs, 3D CNNs, and Wav2Vec. REST APIs and experiment tracking included.
Developed a platform for detecting image, video, and audio deepfakes using CNNs, 3D CNNs, and Wav2Vec. Included REST APIs and experiment tracking, achieving 89% detection accuracy.
Smart SSH honeypot with NLP-based command analysis and blockchain-backed log integrity. Live dashboard and threat-scoring algorithm for real-time attack monitoring.
Designed a smart SSH honeypot with NLP-based command analysis and blockchain-backed log integrity. Developed a live dashboard and threat-scoring algorithm for real-time attack monitoring.
Automated vehicle counting and slot monitoring with IoT sensors.
Developed an IoT system with IR sensors, servo control, and LCD display for real-time parking management. Automated vehicle counting and slot status logic.
CGPA: 8.67/10.0
Focus: Robotics, AI, Embedded Systems, Medical Robotics, Hardware Engineering
Stream: Mathematics, Physics, Chemistry
2025 - Present | Managing technical logistics, participant coordination, and event execution
2025 - Present | Leading technical initiatives and digital transformation projects
2025 - Present | Organizing outreach programs and industry-focused activities
2025 - Present | Contributing to robotics research and competition preparation
2025 - Present | Chief Administrative Officer
Based in Nitte, Karnataka. Open to opportunities in robotics, AI, embedded systems, and medical device development. Let's connect and discuss how we can work together on innovative projects!