# Sriram Priyadharshan

> SLAM Engineer @ Bonsai Robotics | MS in Robotics | Robot perception, navigation, learning and control.

Location: San Jose, California, United States
Profile: https://flows.cv/srirampriyadharshan

My journey in robotics is fueled by a deep-seated enthusiasm for innovating at the intersection of hardware robustness and software intelligence. I am constantly driven by the challenge of creating systems that are not only efficient and intelligent but also intuitive and groundbreaking. I am excited to explore new opportunities and collaborations in the field of robotics and AI.

## Work Experience
### SLAM Engineer @ Bonsai Robotics
Jan 2024 – Present | San Jose, CA
Developing perception, SLAM, computer vision, deep learning, and sensor calibration solutions for autonomous off-road agricultural machinery operating in perceptually challenging and GPS-denied environments.

### Research Engineer @ University of Michigan Robotics Department
Jan 2023 – Jan 2024 | University of Michigan, Ann Arbor
FLUENT Robotics Lab:
- Worked on enhancing Human-robot collaborative transportation tasks such as lifting and transporting objects with users, improving human experience with robots in the workspace.
- Built the autonomy software stack for a mobile manipulator, enabling complex tasks around humans, ensuring safety and stability. Contributed to system integration and designed pipelines to characterize hardware and software performance.
- Devoloped a navigation stack for a mobile manipulator in ROS2 with RGB-D feature based SLAM and MPPI (Optimal trajectory control for mobile base), enabling the robot to navigate autonomously in a dynamic indoor setting.
- Integrated multi-modal perception capabilities with computationally limited hardware, leveraging pre-trained models for visual-language manipulation and pose estimation improving user experience in collaborative tasks.

### Teaching Assistant @ University of Michigan Robotics Department
Jan 2023 – Jan 2024 | Ann Arbor, Michigan, United States
Teaching assistant for EECS 504 Computer vision course at University of Michigan Ann arbor
Responsibilities included:
- Grading student homework assignments and projects.
- Conducting office hours discussing coursework and assignments.

### Research Assistant Intern @ University of Michigan Robotics Department
Jan 2023 – Jan 2024 | Ann Arbor, University of Michigan
BIRDS (Biologically Inspired Robotics and Dynamical Systems) Lab :
- Deployed a perception software stack using C++ and ROS for a Hexapedal picking robot, using a Intel realsense L515 sensor to detect, track and create a map of targets, while simultaneously performing localization.
- Programmed a computer vision pipeline for target detection and instance segmentation, utilized an early fusion model to integrate with a 3D LIDAR graph SLAM system seamlessly, enabling real-time state estimation and semantic mapping.

### Graduate Research Assistant @ University of Michigan Robotics Department
Jan 2023 – Jan 2023 | United States
Distributed Aerospace Systems and Control Laboratory :
- Presented a practical analysis of an Adaptive Safety-Critical control system that ensures real-time safety and stability on digital platforms with discrete-time updates, comparing it to traditional periodic controllers.
- Designed Self-triggered Exponential-CBF controller in MATLAB that uses Quadratic Program (QP) optimization applied in Zero-Order Hold manner with a notion of Safe period for Higher order systems, resulting in safety and stability in safety-critical applications, overcoming the limitations of periodic controllers.

### Research Intern @ Syrma Technologies Pvt Ltd
Jan 2021 – Jan 2021 | India
- Designed a concept for a 6-DOF arm-robot ultrasonic welding system for high-volume production yield in a semi-automation RFID-tag production line.
- Programmed a simulation of a arm-robot performing welding action using GAZEBO and ROS. 
- Implemented teach and repeat way-point navigation to demonstrate the action required to perform on the assembly line
- Tested the efficiency of the system by comparing the yield from a manual operation process and the robots automated process for a certain time period, Discovered a potential increase in
the production yield up to 98.8%.


## Education
### Master's degree in Robotics
University of Michigan

### Bachelor's degree in Electrical, Electronics and Communications Engineering
SRM IST Chennai


## Contact & Social
- LinkedIn: https://linkedin.com/in/srirampriyadharshan
- Portfolio: https://srirampr22.github.io/portfolio/index.html
- GitHub: https://github.com/srirampr22
- Portfolio: https://www.youtube.com/@SriramPriyadharshan

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Source: https://flows.cv/srirampriyadharshan
JSON Resume: https://flows.cv/srirampriyadharshan/resume.json
Last updated: 2026-04-10