Gaurav Vikhe
ML EngineerCPO | Robotics Consultant
Combat Robotics
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
CPO | Robotics Consultant
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Worcester Polytechnic Institute
Master of Science - MS, Mechatronics, Robotics, and Automation Engineering
January 1, 2017 – January 1, 2019
Vishwakarma Institute Of Technology
Bachelor's degree, Instrumentation and Control Engineering
January 1, 2011 – January 1, 2015
Combat Robotics
Chief Product Officer
January 1, 2024 – Present
Pune · On-site
Acceleration Robotics
Chief Product Officer
November 1, 2022 – Present
Technoyantra
Senior Robotics Engineer
January 1, 2022 – October 1, 2022
Pune, Maharashtra, India
TRC Robotics (nee Telepresence Robotics Corp).)
Robotics Engineer
September 1, 2020 – October 1, 2021
Drivemind LLC
Software Engineering Intern
January 1, 2019 – April 1, 2019
Sparta, New Jersey
University of Massachusetts Medical School
Research Assistant
September 1, 2018 – December 1, 2018
LIVEWIRE India
Application Engineer
January 1, 2016 – May 1, 2017
Pune Area, India
CADD Centre Training Services Pvt Ltd.
Application Engineer
June 1, 2015 – December 1, 2015
Pune Area, India
Haptic Control for a swarm of mobile robots
January 1, 2018 – Present
- Force Feedback from a Geomagic Touch device is used to augment user control of a swarm of robots. - Movement of the device’s end effector in each axis used to control the speed, formation and heading of the swarm. - Force Feedback scheme to be implemented using a Mamdani Fuzzy Logic Controller. The force feedback is directly proportional to the displacement of the haptic device in each of the axis
Ackermann steering control for aggresive regions of the state space
January 1, 2018 – April 1, 2018
· Model predictive control used to explore the aggressive regions of the state space. Building up from simple controllers like PID and Nakano controllers to nonlinear model predictive control · Wrote a wrapper around VREP’s python API as an interface between ROS and the VREP simulation environment. · Linear Model Predictive Control used to track trajectories.
Tele-Robotic Intelligent Nursing Assistant (TRINA) via Motion-capture
October 1, 2017 – December 1, 2017
-Capturing human hand motion data from both Kinect and Vicon Mocap -Fusing sensor data to model a paradigmatic hand using the principal components on performing PCA -Mapping human grasp to Righthand Robotics' Reflex SF
Robot-Robot Handover via Reinforcement Learning
September 1, 2017 – Present
-Trained a DQN-based RL agent to learn a collaborative behavior strategy between two robots when neither can perform the task alone. -Wrote a wrapper around V-REP's Python API and simulated the handover task in V-REP using a custom-built OpenAI-like environment. -Extending the work and attempting a publication under the guidance of Dr. Carlos Morato (Principal Scientist, Microsoft).
Example based sensor prediction for gesture driven robot in Gazebo
August 1, 2017 – October 1, 2017
- Used example based sensor prediction(ESP) to train for gesture learning on an Arduino 101 - These gestures were then encoded into basic movements for a bot in the ROS gazebo environment
Image Deblurring using deterministic filters and a novel CODA algorithm(MATLAB)
May 1, 2016 – July 1, 2016
- Compared the performance of the deterministic filter and bayesian estimation on image deblurring - Implemented an algorithm which combines bayesian estimation and deterministic filter in a conjunctive manner Work is primarily based on "Analyzing Image Deblurring Through Three Paradigms"
Image Classification using Ant Colony Optimization and Genetic Algorithm
April 1, 2016 – May 1, 2016
Used ACO and GA for optimizing K-means and Fischer's LDA respectively in the context of image classification on the Corel Image features dataset
MATLAB based evaluation of a hybrid hydraulic vehicle with a novel transfer case
December 1, 2015 – February 1, 2016
- Performance evaluation of a hybrid hydraulic vehicle with a transfer case for AWD. - The model of the vehicle was developed using Simulink, SimPowerSystems, and SimDriveline
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in cutting-edge robotics and AI research, indicating a proactive and innovative mindset. The variety of projects, from haptic control to reinforcement learning for robot-robot handover, suggests adaptability and a willingness to explore diverse technical areas. The experience in both academic research and industry roles (including CPO positions) indicates a blend of theoretical knowledge and practical application, which could contribute positively to a dynamic team culture. However, the lack of explicit team-based project descriptions or collaboration details makes a deeper cultural fit assessment challenging.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and a hands-on approach to complex engineering challenges. The experience as a Chief Product Officer suggests leadership potential and an understanding of product development, which could be beneficial for operational fit. However, without specific psychometric or English test results, a detailed assessment of communication clarity, work attitude, stress handling, and team collaboration is not possible.