Shyamsundar Prabhakar Indra Email and Phone Number
Welcome! I recently completed my year-long internship as an AI / ML Engineer at Renesas Electronics America Ltd., where I focused on developing lightweight ML models for Renesas Edge Devices and crafting an in-house Python software for automatic ML deployment on user data. I completed my Robotics masters program from the James Clark School of Engineering at the University of Maryland (UMD), College Park, in May 2024.My professional background includes tackling challenging Computer Vision issues in domains such as Autonomous Driving and navigating Robotic Systems. I've successfully integrated diverse Robotics stacks to seamlessly collaborate. Additionally, I have hands-on experience with Virtual Reality systems and have contributed to software development within that space. My area of interest / research focus lie in the realm of 3D Computer Vision applications, especially in 3D Scene Reconstruction and Single/Multi-view Images to 3D problems. I’m particularly interested in the AR/VR applications of 3D Vision techniques.Acknowledged for my adept and rapid learning, I consistently pursue chances to elevate my skill set and expand my breadth of knowledge. My colleagues value my empathetic demeanor and passion for acquiring new insights. Outside of my academic endeavors, I have organized tutoring sessions aimed at supporting fellow peers on their academic paths and coursework.Apart from delving into the mathematical intricacies of problem-solving, you might find me sweating it out in badminton for 3 hours straight or indulging in the enjoyment and critical analysis of compelling movies. I am excited about the convergence of technology and creativity, and I look forward to contributing my skills to innovative projects.
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Machine Learning EngineerKpcs SystemsHyattsville, Md, Us
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Machine Learning Engineer InternRenesas Electronics Jun 2023 - May 2024Maryland, United StatesSummary : Specialized in MLOps & developing software for automated AI deployment on Renesas edge devices• Built a Python edge AI deployment software platform with end-to-end ML pipelines catered to 1D & 2D data from Renesas edge devices’ sensors, enhancing deployment speed by 46% and reducing manual work by about 70%, saving over 100 man-hrs/month.• Reduced the size of PyTorch Fully Connected Neural Networks by 42% through the implementation of Low-Rank Adaptation (LoRA), making models more efficient for edge deployment.• Integrated ONNX Runtime in the platform, improving model inference speed by 30% & reducing training time by 12%.• Developed and deployed a Support Vector Machine (SVM) model for voice authentication on a Renesas edge device, using a 500 samples in-house dataset collected manually, achieving 96% accuracy on 100 unseen people from the wild.• Dockerized the software platform, enabling consistent and scalable deployment across various developers and edge devices. -
Graduate Computer Vision Researcher - Vision & Learning LabUniversity Of Maryland Feb 2023 - Jun 2023United StatesSummary : Conducted cutting-edge research on generative AI models for text-to-3D facial animation• Performed comprehensive literature review on 3DGANs, GAN Inversion, & CLIP models for a novel text-to-3D animation generation methodology in the domain of 3D facial animations.• Solved an intermediate problem of text based 3DGAN image editing by creating a model integrating EG3D with GAN Inversion for text-based manipulation of latent space using CLIP, trained using the EmotiW (facial emotions) dataset.• Evaluated the intermediate approach using PSNR and SSIM scores to ensure similarity to the originally generated image and CLIP scores to ensure editing success in accordance with the textual input. -
Graduate Teaching Assistant - Department Of Mechanical EngineeringUniversity Of Maryland Jan 2023 - Jun 2023United StatesGraduate Teaching Assistant for ENME272: Computer Aided Design
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Robotics Research InternRobert Bosch Centre For Cyber-Physical Systems @ Iisc Jan 2022 - Aug 2022Bengaluru, Karnataka, IndiaSummary : 3D obstacle detection and lower level controller for WIPRO sponsored L3 autonomous vehicle (AV)• Developed LiDAR-based 3D object detection model for WIPRO sponsored L3 AV, achieving mAP values of 73% (cars) & 72% (pedestrians) on KITTI3D dataset, by training on Waymo Open dataset & self-curated Carla dataset of 10000 synthetic samples. • Engineered Control Barrier Functions (CBFs) based lower level controller python software package, which along with the 3D object detection, gave around 92% successful collision avoidance over 50 simulated scenarios in Carla. • Verified the controller by ROS deployment on a Copernicus UGV, resulting in a published conference paper on the same. -
Computer Vision Research InternInternational Institute Of Information Technology Bangalore Jan 2021 - Aug 2021Bengaluru, Karnataka, IndiaSummary : ROS Perception stack and prototype development for autonomous farm robot• Curated & annotated around 2000 plant images using Azure Image Labeling tool for YOLO model training using transfer learning.• Achieved 94.6% accuracy on a publicly available leaf dataset, by training a YOLO leaf detection model for leaf counting, hence enhancing a farm robot’s crop health monitoring capabilities.• Led a team of 5 junior interns and accelerated completion of farm robot prototype development and ROS perception stack deployment with the leaf detection model on the same, within 22 days. -
Undergraduate ResearcherBirla Institute Of Technology And Science, Pilani Jan 2020 - Jul 2020Pilani, Rajasthan, India• Successfully defended thesis on Deep Learning applications in Computer Vision for level-3 autonomous vehicle.• Created a pedestrian detection + tracking pipeline in a multi-camera setup for an L2 AV, with open source models.• Engineered a Bi-LSTM based model to take tracking data as input and predict the path of pedestrians 2 seconds into the future. -
Web Developement InternCsir - Central Leather Research Institute May 2018 - Jul 2018Chennai, Tamil Nadu, India• Served as a Summer Intern, leading the full-stack development of a dynamic web application. Handled back-end development using Java and JSP, while crafting an intuitive front-end with HTML and CSS.• Designed and implemented a user-friendly web interface for seamless input, storage, management, and retrieval of all project data for the institute from a MySQL database.
Shyamsundar Prabhakar Indra Education Details
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4.00/4.00
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Cbse Aissce - 97% -
Sree Narayana Mission Senior Secondary School, ChennaiCbse Aisse - 10.00/10.00
Frequently Asked Questions about Shyamsundar Prabhakar Indra
What company does Shyamsundar Prabhakar Indra work for?
Shyamsundar Prabhakar Indra works for Kpcs Systems
What is Shyamsundar Prabhakar Indra's role at the current company?
Shyamsundar Prabhakar Indra's current role is Machine Learning Engineer.
What schools did Shyamsundar Prabhakar Indra attend?
Shyamsundar Prabhakar Indra attended University Of Maryland, Birla Institute Of Technology And Science, Pilani, Kendriya Vidyalaya, Sree Narayana Mission Senior Secondary School, Chennai.
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