Sai Ramana Kiran

I am a Senior Algorithms Engineer at Quidient , developing algorithms for 3D reconstruction at the intersection of Computer Graphics, Computer Vision, and Deep Learning. Prior to this I worked on 3D computer vision using edge devices for tiny aerial robots at PeAR Lab, WPI along with my master's advisor Prof Nitin Sanket.

From 2018 to 2022, I worked at Quantitative Brokers as a senior C++ software developer. I designed latency sensitive trading systems and algorithms for fast algorithmic execution.

I got my BS/MS in Aerospace Engineering from IIT Madras, where I worked in Prof Ranjith Mohan's lab on Aerial and Ground Robot Collaborative Navigation systems

I learn by teaching and as part of that effort I jot down my thoughts on concepts I learn. You can find this in my obsidian second brain.

CV  /  Email  /  GitHub  /  Google Scholar  /  LinkedIn  /  Obsidian Notes

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Senior Algorithms Engineer - CV/CG/ML
Quidient
May 2024 - Present
Computer Vision and Deep Learning Intern
Torc Robotics
Aug 2023 - Dec 2023
Perception and Localization Intern
Nokia Bell Labs
Summer 2023
Spring 2024
M.Sc Robotics
WPI
2022-2024
Senior C++ Developer
Quantitative Brokers
Jul 2018 - July 2022
B.Tech/M.Tech Aerospace Engineering
IITM
2013-2018

Research

I'm interested in math, computer vision, machine learning, optimization, graphics and their applications to robotics.

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EdgeFlowNet: 100FPS@1W Optical Flow For Tiny Mobile Robots


Sai Ramana Kiran, Rishabh Singh, Manoj Velmurgan, Nitin Sanket

We present an approach to achieve 100FPS optical flow inference speeds and demonstrate on real world robot autonomy experiments. (Currently under preparation for RA-L)

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Aerial-Ground Robotic system for Terrain estimation and Navigation


Sai Ramana Kiran, Ashutosh Kumar, Ranjith Mohan
ICC, 2019
IEEE Paper / Aerial vehicle stack / Ground vehicle Stack

We show autonomous aerial vehicle and ground vehicle collaborate while performing task of unknown rough terrain estimation and navigation.




Projects

These include coursework, side projects and unpublished research work.

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Enhancing Multi view structured Bird’s-Eye-View Traffic Scene Understanding from Onboard Images


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Enhanced the original STSU’s transformer architecture to use multi-view onboard images using enhanced positional encoding to construct better lane lines

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Stereo Visual Inertial Odometry


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Implemented Multi-State Constraint Kalman Filter based Visual Inertial Odometry

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Point Cloud Semantic Mapping


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A pipeline to combine the data from LiDAR and Camera to obtain semantic painted point cloud.

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Neural Radience Fields (NeRF)


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Implemented a full pipeline of NeRF

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Structure from Motion (SfM)


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Simultaneously reconstructed 3D scene (Mapping) and extracted camera pose (Localization) from given camera correspondences using (Non)Linear triangulation, (Non)Linear PnP and Bundle Adjustment (BA) pipeline

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AutoCalib: Zhang's Calibration module


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Implemented Zhang’s camera calibration by nonlinear optimization of intrinsics and extrinsics

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Face Swap


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Faceswap pipeline using Delaunay triangulation and Thin plate splines based warping and poisson blending in a video

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AutoPano: Stitching assorted images


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Created a panorama by stitching images using homography estimated from traditional (ANMS, RANSAC feature points) and Deep learning (Supervised and Unsupervised HomographyNet) methods


Design and source code from Jon Barron's website fork of Leonid Keselman