Venkata Sai Krishna Bodda

Enthusiastic Robotics Engineering student at WPI and Researcher at Medical Fusion Lab. Crafting the algorithms that teach machines to perceive, navigate, and interact with the world autonomously.

Looking to colloborate on cutting edge robotics-project🤖? geek out over automotives🏎, discover epic treking spots🧗 , or challenge me to a swim 🏊? let's connect 🙂


Venkata Sai Krishna Bodda

About Me

Robotics engineer currently working at Amazon Robotics as a Robotic Solution Design Engineer, where I build simulation, automation, and map-validation systems for warehouse robotics deployments. My work spans Python, Unity3D, AWS, Revit API, Dynamo, Docker, and Open3D to model large-scale robotic workflows, validate 500+ warehouse maps, and improve deployment speed and reliability across facility networks.

I completed my Master's in Robotics Engineering at WPI in April 2025, where I worked as a researcher at Medical Fusion Lab developing a Franka-based robotic system for multi-view OCT imaging of transplant kidneys. Across Amazon Robotics, WPI, and earlier software engineering work at Wipro, I have focused on turning robotics, perception, and machine learning ideas into production-ready systems with measurable impact.


Venkata Sai Krishna Bodda

Robotic Solution Design Engineer - Amazon Robotics

Built and scaled simulation, automation, and map-validation systems to improve robotic deployment speed and reliability across Amazon warehouse networks.

Amazon Robotics

Warehouse Robotics Simulation

Built a Python and Unity3D simulation platform that converted warehouse JSON map exports into accurate 3D digital twins, validating OBDA workflows across 10+ facility layouts and simulating 10k+ package arrivals per hour to identify routing bottlenecks.

Amazon Robotics

Cloud Deployment and Reliability

Deployed the simulation service on AWS EC2 with S3-backed pipelines and added automated testing with PyTest and GitHub Actions, enabling scalable scenario execution and dependable releases as the team grew.

Amazon Robotics

Layout Automation at Scale

Built a Revit API and Dynamo automation pipeline, containerized headless Revit with Docker and Windows containers, and enabled 20+ designers to trigger layout updates via web workflows, cutting manual processing time by 80%.

Amazon Robotics

Map Validation and Incident Prevention

Developed Open3D voxel-based clash detection for 100M+ point-cloud datasets and integrated automated checks into deployment workflows, validating 500+ maps and helping prevent invalid navigation layouts and repeat Sev-2 incidents.

Research Assistant - Fusion Lab

developing multiview OCT imaging of kidney pre transplantation with autofocus, under Prof. Haichong Zhang

Medical Imaging

Medical Imaging

Using Optical Coherence Tomography with franka robot to scan kidney transplant.

Medical Imaging

Image Segmentation

Trained a U-Net model to detect kidney capsule and fat from OCT probe RGB feed for adaptive scan acquisition.

Medical Imaging

Path Planning

Planned Trajectory around organ for efficient scanning

Medical Imaging

OCT post-Processing

Converted OCT B-scans into Depthmaps and Volumes

Project Engineer - Wipro

Developed a deep learning pipeline for prostate cancer detection from MRI

Medical Imaging

Prostrate Cancer Detection

Developed a 3D Convolutional Neural Network (CNN) to accurately detect prostate cancer from MRI scans, enabling automated analysis of volumetric medical images.

Medical Imaging

Data Augmentation

Augmented 3D MRI data using Slicer3D simulations, applying techniques such as rotation, clipping, and synthetic data generation to enhance model robustness.

Medical Imaging

Model Optimization and pruning

Optimized the deep learning model using pruning and quantization techniques to reduce model size and improve inference speed without sacrificing accuracy.

Medical Imaging

Model Evaluation & Integration

Conducted model evaluation on a clinical dataset using requirements-driven development and rigorous validation and testing methodologies, ensuring 98% sensitivity and seamless integration into the diagnostic workflow.

Active Sensing End Effector for Robotic Ultrasound

Devised an endeffector for robotic ultrasound system, automating probe orientation perpendicular to patient surface using depth cameras.

Simulating Pick and Place Operations with an ABB Robot

Simulated a pick-and-place operation for the ABB IRB 1200 robot, designing station logic for attacher and detacher mechanisms and defining precise robotic paths to automate the process, demonstrating advanced skills in robotic programming and process optimization.

Embodied Agent - Indoor Robot Navigation

Comparison of traditional planners such as RRT, A* with end to end learning approaches for indoor Embodied navigation.

Neural Radiance Fields

Optimized NeRF model to reconstruct 3D scenes with a 5 × 10−4 pixel loss by refining positional encoding and MLP architecture.Rendered novel 3D views from radiance fields, improving accuracy through data engineering and enhancing visual fidelity.

Odometry Using Deep learning

LSTM-based deep learning model for Visual-Inertial Odometry using image datasets and IMU data, achieving a localization error of 0.0237m on the Euroc_MAV dataset.

Deep learning for reconstructing car's environment from camera feed

Processed Tesla camera feed using MiDaS for depth and YOLOv8 for segmentation, identifying cars, lanes, and pedestrians in 3D space. Reconstructed 3D environments by calculating object positions from depth and placing assets in Blender, simulating Tesla’s dashboard.

Quadcopter control system for aerial refuelling

Designed a feed-forward control algorithm for a quadcopter in MATLAB, attaining alignment with ±1.45 cm error for midair refueling. Developed a dynamic model for a quadcopter along with simulating mass discharge enabling accurate representation of the quadcopter.

Panorama Stitching using Deep Learning

Developed a deep learning model using HomographyNet to predict homography between image pairs, Executed image morphing and stitching processes using predicted homographies.

Dynamics and Controls of a Pick-and-Place Robot

Developed dynamic model of open manipulator x robot using solid works, enabling precise control within 1mm error. Designed controller for manipulator utilizing Computed Torque Controller to follow a trajectory generated by quintic polynomial profiles. Integrated camera based object detection with 95% accuracy and inverse kinematics to to pick and place object at a desired place.

Surface from motion

Executed Structure from Motion by capturing images, matching features, performing bundle adjustment, and estimating 3D points.

ART-SLAM

ROS2-Python Implementation of accurate realtime simultaneous localization and mapping

Skills

Python
C++
Localization, Mapping
Computer Vision
Deep Learning
Motion Planning
ROS 2
Pytorch
CUDA
Dynamics and Controls
Open3d
Opencv
numpy
MoveIT
MATLAB
Gazebo

Get in touch

Ready to dive in? Drop your info and let's make something awesome happen!


Portfolio

Venkata Sai Krishna Bodda

Enthusiastic Robotics Engineering student at WPI and Researcher at Medical Fusion Lab. Crafting the algorithms that teach machines to perceive, navigate, and interact with the world autonomously.

Looking to colloborate on cutting edge robotics-project🤖? geek out over automotives🏎, discover epic treking spots🧗 , or challenge me to a swim 🏊? let's connect 🙂


Venkata Sai Krishna Bodda

About Me

Robotics Engineering graduate student at WPI, Researcher at Medical Fusion Lab, developing robotic system using franka robot for automated multiview OCT Imaging of transplant kidney with autofocus. Specalizing in Deep Learning, Localization, Mapping, Computer Vision and advanced robot control systems, driving future of intelligent automation in Medical Imaging.

With 2 years of experience as a Software Engineer at Wipro, I engineered advanced machine learning and perception algorithms to accurately detect prostate cancer in 3D MRI scans, driving impactful innovations in medical imaging.


Venkata Sai Krishna Bodda

Research Assistant - Fusion Lab

developing multiview OCT imaging of kidney pre transplantation with autofocus, under Prof. Haichong Zhang

Medical Imaging

Medical Imaging

Using Optical Coherence Tomography with franka robot to scan kidney transplant.

Medical Imaging

Image Segmentation

Trained a U-Net model to detect kidney capsule and fat from OCT probe RGB feed for adaptive scan acquisition.

Medical Imaging

Path Planning

Planned Trajectory around organ for efficient scanning

Medical Imaging

OCT post-Processing

Converted OCT B-scans into Depthmaps and Volumes

Project Engineer - Wipro

Developed a deep learning pipeline for prostate cancer detection from MRI

Medical Imaging

Prostrate Cancer Detection

Developed a 3D Convolutional Neural Network (CNN) to accurately detect prostate cancer from MRI scans, enabling automated analysis of volumetric medical images.

Medical Imaging

Data Augmentation

Augmented 3D MRI data using Slicer3D simulations, applying techniques such as rotation, clipping, and synthetic data generation to enhance model robustness.

Medical Imaging

Model Optimization and pruning

Optimized the deep learning model using pruning and quantization techniques to reduce model size and improve inference speed without sacrificing accuracy.

Medical Imaging

Model Evaluation & Integration

Conducted model evaluation on a clinical dataset using requirements-driven development and rigorous validation and testing methodologies, ensuring 98% sensitivity and seamless integration into the diagnostic workflow.

Active Sensing End Effector for Robotic Ultrasound

Devised an endeffector for robotic ultrasound system, automating probe orientation perpendicular to patient surface using depth cameras.

Simulating Pick and Place Operations with an ABB Robot

Simulated a pick-and-place operation for the ABB IRB 1200 robot, designing station logic for attacher and detacher mechanisms and defining precise robotic paths to automate the process, demonstrating advanced skills in robotic programming and process optimization.

Embodied Agent - Indoor Robot Navigation

Comparison of traditional planners such as RRT, A* with end to end learning approaches for indoor Embodied navigation.

Neural Radiance Fields

Optimized NeRF model to reconstruct 3D scenes with a 5 × 10−4 pixel loss by refining positional encoding and MLP architecture.Rendered novel 3D views from radiance fields, improving accuracy through data engineering and enhancing visual fidelity.

Odometry Using Deep learning

LSTM-based deep learning model for Visual-Inertial Odometry using image datasets and IMU data, achieving a localization error of 0.0237m on the Euroc_MAV dataset.

Deep learning for reconstructing car's environment from camera feed

Processed Tesla camera feed using MiDaS for depth and YOLOv8 for segmentation, identifying cars, lanes, and pedestrians in 3D space. Reconstructed 3D environments by calculating object positions from depth and placing assets in Blender, simulating Tesla’s dashboard.

Quadcopter control system for aerial refuelling

Designed a feed-forward control algorithm for a quadcopter in MATLAB, attaining alignment with ±1.45 cm error for midair refueling. Developed a dynamic model for a quadcopter along with simulating mass discharge enabling accurate representation of the quadcopter.

Panorama Stitching using Deep Learning

Developed a deep learning model using HomographyNet to predict homography between image pairs, Executed image morphing and stitching processes using predicted homographies.

Dynamics and Controls of a Pick-and-Place Robot

Developed dynamic model of open manipulator x robot using solid works, enabling precise control within 1mm error. Designed controller for manipulator utilizing Computed Torque Controller to follow a trajectory generated by quintic polynomial profiles. Integrated camera based object detection with 95% accuracy and inverse kinematics to to pick and place object at a desired place.

Surface from motion

Executed Structure from Motion by capturing images, matching features, performing bundle adjustment, and estimating 3D points.

ART-SLAM

ROS2-Python Implementation of accurate realtime simultaneous localization and mapping

Skills

Python
C++
Localization, Mapping
Computer Vision
Deep Learning
Motion Planning
ROS 2
Pytorch
CUDA
Dynamics and Controls
Open3d
Opencv
numpy
MoveIT
MATLAB
Gazebo

Get in touch

Ready to dive in? Drop your info and let's make something awesome happen!