Srijith Umakanth has 3+ years of Industry experience in Technology Research and Development field working for Transportation and Logistics market place. He is a self-initiated, results-oriented Robotics Engineer with excellent academic standing along with professional experience in the field of Control Systems, Robotics, Autonomous Mobile Robots (AMR), Pathplanning, Hardware in the Loop (HiL) testing, CAD/CAM, FEA packages, Machine Design, Computer Vision and Deep Learning. He graduated from University of Illinois at Chicago, USA with a degree in Mechanical Engineering focusing on Control and Perception Systems. He is currently working with Arcbest Technologies, USA as a Robotics Engineer developing Autonomous Mobile Robots for deployment inside a large warehouse to automate and optimize logistics operations. He has expertise in automation, path planning, trajectory tracking and safety for AMR applications. He also has experience working with perception systems like depth cameras, 2D/3D LiDAR’s and GPU based inference edge platforms like Nvidia AGX Xavier. He has also worked in training and deploying real time deep learning models on AMR’s for applications like obstacle avoidance and object tracking.
Natarajan Vaidyanathan is a PhD candidate in University of Waterloo working on computational models of motor control. His primary research is based on building biologically relevant mechanisms to understand how our brains control arms in dynamic and noisy environments. Navigation, vision, flying, adaptation and learning are some of the problems that he is particularly interested in. With a background in mechanical engineering and experience in deep learning and neuroscience, Natarajan helps out in bringing a multidisciplinary approach.
PRAKYATH KANTHARAJU (PK): Currently 3rd year Ph.D. student at the University of Illinois at Chicago. His research interests include Human-Robot interaction, Machine learning, and Biomedical signal processing. He is working towards using biomedical signals and kinematics in the decision-making process for exoskeleton applications using machine learning. He has successfully completed projects in wearable signals like ECG, IMU, EMG, and foot pressure sensors. He has also developed real-time controllers for walking, squatting, and running using ankle and hip exoskeleton. He has received an M.S degree from the University of Illinois at Chicago in 2019 and a B.E degree from Visvesvaraya Technological University in 2017.