Scholar
Sparsh Garg
Google Scholar ID: uP6sOhoAAAAJ
Carnegie Mellon University
Citations & Impact
Citations
33
H-index
2
i10-index
1
Publications
3
Co-authors
8
list available
Resume
Academic Achievements
- Published paper 'Depth Any Camera (DAC): A Framework for Zero-Shot Metric Depth Estimation Across Diverse Camera Types', accepted to CVPR 2025; Projects include: Depth Any Camera, SplatSim, Vine Stereo, Liquid Segmentation and Viscosity Estimation, EMG Prosthetic Arm.
Research Experience
- Worked as a Research Intern at Bosch Center for Artificial Intelligence (BCAI), co-developing a state-of-the-art model for monocular metric depth estimation from arbitrary cameras. Gained professional experience at ExxonMobil in Bangalore and CynLr (Cybernetics Laboratory), where I played a key role in building a stereo vision system from the ground up, spanning both hardware and software development.
Education
- Pursued Master’s degree at Carnegie Mellon University, specializing in computer vision and robotics. Worked at the Robotics Institute’s Kantor Lab under the guidance of Dr. George A. Kantor, advancing automation technologies for agriculture and physical sciences, with an emphasis on perception and manipulation pipelines for real-world applications. Earned undergraduate degree from Punjab Engineering College, India.
Background
- Currently working as a Machine Learning Engineer in the Perception team at Lucid Motors, focusing on advancing autonomous driving technologies within the ADAS domain. My work centers around developing robust perception systems that enable safer and more intelligent vehicles. My interests lie at the intersection of computer vision, deep learning, and robotics, with a focus on building reliable perception systems that can drive the next generation of intelligent vehicles.
Miscellany
- Contact: sparsh913@gmail.com; Office: CIC Robotics Institute (near Lab 2)
