Highly motivated Computer Vision and Machine Learning Researcher with a Master of Science background, specializing in advanced deep learning architectures and their real-world applications. Proven ability to conduct impactful research, optimize complex systems for performance and robustness, and contribute to peer-reviewed publications. Seeking to leverage expertise in cutting-edge R&D roles within academic or industrial research environments.
Research Assistant
Saarbrucken, Saarland, Germany
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Summary
Conducting advanced research and implementing state-of-the-art deep learning architectures and methods to drive innovation in digital product and process development.
Highlights
Researched and implemented state-of-the-art (SOTA) deep learning architectures, contributing to advancements in digital product and process optimization.
Developed novel methodologies for data analysis and model training, enhancing efficiency and accuracy of research outcomes.
Collaborated with interdisciplinary teams to integrate deep learning solutions into complex systems, demonstrating strong problem-solving skills.
Computer Vision Intern
Pune, Maharashtra, India
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Summary
Engineered a deep-learning helipad detector with Euler angle estimation and closed-loop control, validated on a physical drone for extreme-environment testing.
Highlights
Developed a deep-learning helipad detector, integrating Euler angle estimation and closed-loop control for autonomous drone landing systems.
Validated system performance on a physical drone, demonstrating robust functionality and precision in extreme environmental conditions.
Designed and implemented custom data acquisition tools, supporting comprehensive testing and refinement of the helipad detection model.
Utilized SSDMobilenet model for helipad detection and Mavlink messages via Mavsdk platform to achieve vision-based landing capabilities.
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Master of Science
Computer Science
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Bachelor of Technology
Instrumentation and Control Engineering
Grade: 9.17
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Higher Secondary School Certificate
Science
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Secondary School Certificate
General Studies
Awarded By
PickHacks '21 by Missouri University of Science and Technology
Awarded for outstanding performance in a hackathon, demonstrating innovative problem-solving and technical skills. Project: rap-god-42mnyv.
Awarded By
RowdyHacks '21 by University of Texas San Antonio
Recognized for developing the most innovative hardware solution in a competitive hackathon. Project: crashbuds.
Awarded By
HighField Hacks '21 by SouthHampton University
Received an award for exceptional project development and execution in a hackathon setting. Project: gym-buddy-rnt9yp.
Awarded By
Machacks '21 by McMaster University
Honored for creating the most impactful safety-focused solution during a hackathon. Project: drive-buddy.
Published by
SCITEPress
Summary
Analyzed transfer-learning robustness of object detectors for fish detection, achieving 0.92 mAP in-domain (YOLOv8l) and quantifying out-of-domain false positives; evaluated retraining and bias-only adaptation strategies.
C++, Python, Metal Programming.
Image Processing, Image Analysis, Image Segmentation, Computer Graphics.
Deep Learning, Machine Learning, Data Preprocessing.
Linux.
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Summary
Surveyed and implemented vision-based pipelines for industrial wastewater monitoring. Focused on anomaly detection, aeration analysis, and camera-based water-level estimation under real-world constraints.
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Summary
Developed an IoT-based smart shower system with automated water cutoff, environmental monitoring, and an emergency override function to significantly reduce water consumption.
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Summary
Developed an early-warning system for drowsy driving using machine learning algorithms to detect open and closed eyes, enhancing road safety and preventing accidents.
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Summary
Leveraged YOLOv4 architecture to train a system for detecting license plates with an optical character recognition algorithm, outputting the license plate number.