FoundERs

Dipam is a passionate learner, pursuing Master of Engineering in Robotics at the University of Maryland, College Park. He seeks excellence in any field through dedication and hard work and aims to strengthen his core skills. He has the self-motivation to learn new things and push my limits. His interests mostly include Machine Learning, Robot Operating System, Computer Vision, and Augmented Reality.

At Airgility, Dipam is involved with Deep Learning focused on Object Detection using Tensorflow API for Autonomous Takeoff & Landing of Drones. He is working on Semantic Segmentation based algorithm for Detection of Humans and Objects of Interest. His personal goal is to have complete Autonomous Flying possible using only Machine Learning.

He enjoys doing some adventurous activities like running, hiking, biking or rock climbing. He can also juggle and solve a Rubik’s cube pretty quickly.

Niket is a Robotics graduate student at the A. James Clark School of Engineering at the UMD. He has an undergraduate degree in Electronics and Telecommunication Engineering from University of Mumbai. His field of interests are Computer Vision, Autonomous Systems, Machine Learning. He joined Airgility in the summer of 2019 as an intern and works on the Computer Vision algorithms.

Ashwin Kuruttukulam is the Lead Algorithm Developer at Airgility. His undergraduate engineering degree is in Applied Electronics and Instrumentation, from the College of Engineering in Trivandrum, India. He has concluded his undergraduate work in “First Class with Distinction”. Prior to joining Airgility, he worked at the Robotics Research Center at the Indian Institute for Information Technology (IIIT), Hyderabad where he developed a fully autonomous pick and place drone system using a monocular camera and an inertial measurement unit. While at IIIT, he also developed robust face recognition algorithms using Histogram of Gradients and deep Convolutional Neural Networks (CNN). He has also worked on the Lockheed Martin AlphaPilot challenge where he developed reinforcement learning based control for autonomous quadcopter racing using CNNs. He currently a graduate student at the University of Maryland, pursuing a Masters in Robotics expecting to graduate in May 2020.

Andrew Lent is the lead manufacturing manager and flight test engineer at Airgility. Currently, he is a junior undergraduate aerospace engineering student at the University of Maryland. Andrew has been a member of the team for over a year and a half now. Prior to his current roles, he played integral parts in the composite manufacturing, wind tunnel testing, and tethered flight testing of the HorseSHU aircraft. He was also a lead engineer in the assembly and early testing of the CatDog and miniSHU vehicles. Aside from Airgility, Andrew has worked as a research assistant in the High-Speed Aerodynamics and Propulsion Laboratory where he redesigned and manufactured the test section airfoil mounting system for a Mach 6 reflected shock tunnel. He also interned at the Glenn L. Martin Wind Tunnel where he developed a novel Particle Image Velocimetry algorithm designed for large wind tunnels. Outside of his professional life, Andrew is a runner for University of Maryland’s club running team, an avid backpacker, and amateur mountaineer.