About Me
Hi, I’m Surya, M.Sc. Informatics student at the Technische Universität München, My interests lie in the field of Deep Learning and Computer Vision. I’ve worked on several Computer Vision projects and have hands-on experience and knowledge in various Deep Learning Architectures. I’m looking forward to implementing Deep Learning in various fields such as Medical, Self Driving vehicles, Security, etc.. Extremely interested in working on 2D/3D generative models, 2D/3D image segmentation, 2D/3D object detection and 3D Reconstruction.
Projects
- Worked on the NVDIFFRECMC(CVPR,22) architecture by NVIDIA.
- Developed a Neural BRDF model for optimizing the material part.
- Improved denoising significantly using a diffusion-based model.
- Performed Stereo Reconstruction on the KITTI Stereo 2015 dataset.
- Implemented Block Matching, Semi Global Matching for generating the disparity maps and also used SIFT, SURF and ORB for keypoint matching, triangulation and generation of point clouds.
- Developed the application using Intel Distribution of the OpenVINO Toolkit.
- This app control the movement of mouse pointer by the direction of eyes and also estimates pose of the head.
- This app takes video as input(video file or camera) and then estimates the gaze of the user’s eyes and change the mouse pointer position accordingly.
- Developed the application using Intel Distribution of the OpenVINO Toolkit.
- This app detects and counts the number of people in a particular queue and redirects them to a less congested queue.
- Worked on Intel DevCloud to implement the project on several hardwares[CPU, IGPU, VPU(NCS2),FPGA].
- Developed the application using Intel Distribution of the OpenVINO Toolkit.
- This app calculates:-
- the number of people in the frame
- time spent by those people in the frame
- the total number of people counted
and sends this data to a MQTT server.
- Performed multi-class classification for the dectection of Non-Proliferative Diabetic Retinopathy.
- Implemented Inception Network(V1-V4,ResNetV1 and ResNetV2).
- Achieved an accuracy of 93.78% on the test set.
Knee MRI Super-Resolution
- Performed Super-Resolution on Knee-Magnetic Resonance Images.
- Implemented LapSRN, SRGAN and SRCNN to perform Super-Resolution.
- Achieved an SSIM of 0.9887 on the test set.
Experience
Blickfeld
AI Work Student
December 2022 - Present
- Performed 3D Object Detection on Kitti 3D Object Detection velodyne dataset by implementing Pointpillars architecture on the OpenPCDet framework.
- Worked on end-to-end model deployment.
Tata Consultancy Services
System Engineer
August 2020 - March 2022
- Worked as a full-stack developer for Citi Bank client. Developed an API for their Best Buy partner.
- Deployed contents in Ford, Lincoln and Costco partners as a part of Pony and Costco Decommissioning projects.
Dept. of Translational Medicine and Research, SRM Medical College
Research Intern
August 2019 - August 2020
- Collected real-life Knee MRI data, cleaned the data and used image processing techniques to make the data trainable.
- Developed a novel loss function for the same which provided better results and submitted a paper on the same which got accepted at the EMBC 2020 conference.
SPARC, SRM Institute of Science and Technology
Research Intern
June 2019 - June 2019
- Worked on a Research project proposed by Indian Institute of Technology Kharagpur, collaborated with University of California, Davis.
- Developed a classifier to predict non-proliferative Diabetic Retinopathy.
- Implemented several state-of-the-art deep learning architectures for Image Classification
Alpha Cloud Labs
Research Intern
December 2018 - December 2018
- Worked on video text- recognition using Tesseract-OCR, OpenCV and Deep Learning.
Education
Technische Universität München
M. Sc. Informatics
2022 - Present
SRM Institute of Science and Technology
B. Tech Computer Science and Engineering
2016 - 2020
CGPA:- 8.78
Publications
-
MRI Super-Resolution using Laplacian Pyramid Convolutional Neural Networks with Isotropic Undecimated Wavelet Loss
Sriprabha Ramanarayanan, Balamurali Murugesan, Ananth Kalyanasundaram, Surya Prabhakaran, Keerthi Ram, Shantanu Patil, Mohanasankar Sivaprakasam
EMBC 2020 - Paper -
Detection of Pathological Myopia by Convolutional Neural Network
Ananth Kalyanasundaram, Surya Prabhakaran, J. Briskilal, D. Senthil Kumar
International Journal of Psychosocial Rehabilitation, Vol. 24, Issue 05, 2020 - Paper -
Diagnosing abnormality of foetus using Machine Learning algorithms
Abhijith Ragav, Surya Prabhakaran, Shivabhinav.S.G.
International Journal of Psychosocial Rehabilitation, Vol. 24, Issue 08, 2020.