I am a passionate engineer with a dedication to cutting-edge technology and innovation. My experience spans various fields in computer science and engineering, and I thrive on challenges that push my limits and expand my knowledge. I enjoy collaborative environments and am eager to contribute to exciting projects. Throughout my career, I have developed a strong foundation in programming, problem-solving, and system design. I look forward to utilizing my skills to create impactful solutions and innovate in technology-driven roles.

Manoj Srinivasan

I am a passionate engineer with a dedication to cutting-edge technology and innovation. My experience spans various fields in computer science and engineering, and I thrive on challenges that push my limits and expand my knowledge. I enjoy collaborative environments and am eager to contribute to exciting projects. Throughout my career, I have developed a strong foundation in programming, problem-solving, and system design. I look forward to utilizing my skills to create impactful solutions and innovate in technology-driven roles.

Available to hire

I am a passionate engineer with a dedication to cutting-edge technology and innovation. My experience spans various fields in computer science and engineering, and I thrive on challenges that push my limits and expand my knowledge. I enjoy collaborative environments and am eager to contribute to exciting projects.

Throughout my career, I have developed a strong foundation in programming, problem-solving, and system design. I look forward to utilizing my skills to create impactful solutions and innovate in technology-driven roles.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Graduate Research Assistant at New York University (NYU) Video Lab
August 1, 2025 - November 18, 2025
Implemented a pipeline integrating 2D video diffusion priors with 3D Gaussian Splatting using PyTorch, HPC clusters, and Slurm, achieving a 19% LPIPS improvement in novel-view synthesis under sparse input conditions. Enhanced 3D view consistency by formulating view generation as a temporal continuity task, integrating camera-pose embeddings with diffusion-guided latent features across view points. Explored mesh registration for human poses using learned skinning methods such as SMPL to improve 3D consistency.
Graduate Engineering Intern at Intel Corporation
August 31, 2024 - August 31, 2024
Developed a computer vision framework for automated detection of IC package design violations, emulating manually performed inspection heuristics for 8 checks. Optimized computational efficiency using HuggingFace’s segmentation models and OpenCV’s morphological algorithms, reducing detection pipeline runtime by 85%. Honored with Intel’s Impact Award for delivering high-quality solutions in a short time frame.
Graduate Engineering Intern at Intel Corporation
August 1, 2024 - October 7, 2025
Developed a vision-based framework for automated detection of IC package design violations, emulating expert visual inspection heuristics for 8 key manual visual checks. Optimized computational efficiency using segmentation techniques and OpenCV’s morphological algorithms, improving parallelizability and reducing detection pipeline runtime by 85% (from over 4 hours to under 30 minutes). Honored with Intel’s Impact Award for delivering high-quality solutions in a short time frame.
Graduate Engineering Intern at Intel Corporation
August 1, 2024 - September 22, 2025
Developed a vision-based framework for automated detection of IC package design violations, emulating expert visual inspection heuristics for 8 key manual visual checks. Optimized computational efficiency using segmentation techniques and OpenCV's morphological algorithms, improving parallelization and reducing detection pipeline runtime by 85% (from over 4 hours to under 30 minutes). Honored with Intel’s Impact Award for delivering high-quality solutions in a short timeline.
Machine Learning Intern at Pre-image
December 31, 2022 - December 31, 2022
Adapted a transformer-based multi-view stereo (MVS) pipeline for dense 3D reconstruction from aerial drone imagery, improving accuracy by ~10% in sparse-view and large-scale outdoor scenes. Deployed on Azure VMs, leveraging AWS S3 for data management and PyTorch Lightning with CUDA for efficient distributed training.
Machine Learning Intern at Pre Image
December 1, 2022 - October 7, 2025
Adapted a transformer-based multi-view stereo pipeline for dense 3D geometry reconstruction from aerial imagery, optimizing performance for sparse-view and large-scale outdoor scenes. Improved feature representation using an adaptive feature pyramid network (FPN) that leverages sinusoidal embeddings conditioned on scene-specific depth bounds, increasing reconstruction accuracy by ~10% in challenging outdoor scenes. Investigated techniques such as normal regularization and geometric consistency constraints to improve reconstruction accuracy with minimal impact on computational efficiency.
Machine Learning Intern at Pre Image
December 1, 2022 - September 22, 2025
Adapted a transformer-based multi-view stereo pipeline for dense 3D geometry reconstruction from aerial (drone) imagery, optimizing performance for sparse-view and large-scale outdoor scenes. Enhanced feature representation with an adaptive feature pyramid network (FPN) leveraging sinusoidal embeddings conditioned on scene-specific depth bounds, boosting reconstruction accuracy by ~10%. Investigated normal regularization and geometric consistency constraints to improve reconstruction robustness.
Machine Learning Intern at Asilla Japan (Remote)
July 1, 2022 - October 7, 2025
Enhanced an abnormal activity detection pipeline for surveillance systems by fine-tuning the quantization mechanism used to learn a latent “normal action” dictionary and flag deviations as anomalous behavior. Reduced runtime latency by ~15%, enabling deployment on 20+ real-time CCTV feeds at Hankyu Nishinomiya Gardens Mall, Japan.
Machine Learning Intern at Asilla Japan (Remote)
July 1, 2022 - September 22, 2025
Enhanced an abnormal activity detection pipeline for surveillance systems by fine-tuning the quantization mechanism used to learn a latent 'normal action' dictionary and flag deviations as anomalous behavior.
Image Processing Intern at GalaxyEye Space
January 31, 2022 - January 31, 2022
Built a super-resolution neural network to upsample low-quality remote-sensing data in the form of SAR images, along with a generative model to predict RGB optical images from the super-resolved SAR output. Conducted experiments on Azure VMs and AWS S3 for data management and PyTorch Lightning with CUDA for efficient distributed training.
Image Processing Intern at Galaxy Eye Space
January 1, 2022 - October 7, 2025
Built a super-resolution neural network to upsample low-quality remote-sensing data in the form of Synthetic Aperture Radar (SAR) images, along with a generative model to predict RGB optical images from the super-resolved SAR output. Conducted experiments on ISRO’s data, leading to increased super-resolution quality even at scale of up to 16x.
Image Processing Intern at Galaxy Eye Space
January 1, 2022 - September 22, 2025
Built a super-resolution neural network to upsample low-quality remote-sensing data in the form of Synthetic Aperture Radar (SAR) images, along with a generative model to predict RGB optical images from the super-resolved SAR output. Conducted experiments on ISRO data, leading to increased super-resolution quality up to 16x.

Education

M.S. Computer Engineering at New York University, Tandon School of Engineering
September 1, 2023 - May 1, 2025
B.Tech - Mechanical Engineering at Indian Institute of Technology Madras
August 1, 2018 - July 1, 2023
M.Tech - Robotics; Minor: Computing, AI & ML at Indian Institute of Technology Madras
August 1, 2018 - July 1, 2023
M.S. in Computer Engineering at New York University, Tandon School of Engineering
September 1, 2023 - May 1, 2025
B.Tech - Mechanical Engineering; M.Tech - Robotics; Minors in Computing, Artificial Intelligence & Machine Learning at Indian Institute of Technology Madras (IIT M)
August 1, 2018 - July 1, 2023
M.S. in Computer Engineering at New York University, Tandon School of Engineering
September 1, 2023 - May 1, 2025
B.Tech in Mechanical Engineering; M.Tech in Robotics (IIT Madras) with minors in Computing, AI & ML at Indian Institute of Technology Madras
August 1, 2018 - July 1, 2023
M.S. Computer Engineering at New York University (NYU)
September 1, 2023 - May 1, 2025
B.E. Electrical and Computer Engineering at National Institute of Technology
August 1, 2017 - May 1, 2021

Qualifications

Machine Learning in Production
January 11, 2030 - November 18, 2025
Python for Computer Vision with OpenCV and Deep Learning
January 11, 2030 - November 18, 2025
LLM Ops
January 11, 2030 - November 18, 2025

Industry Experience

Computers & Electronics, Software & Internet, Education, Media & Entertainment, Professional Services