Position: Researcher
Category: Data Science
English level: upper
Years of experience: 4

For the last five years, I've been a member of the Multi Robot System research group at Czech Technical University in Prague.
As a bachelor at Ukrainian Catholic University, I was the only exchange student who took part in MBZIRC 2020 (a prestige robotics competition with a 5 million USD prize pool and significant competitors from the world of research: ETH, Cornell, Beijing, etc.). My success in this competition leads us to take 2nd place in First Competition (intercepting an aerial target and destroying multi-targets using a multi-agent approach) and first place in the Grand Challenge, securing a 250k USD prize. Our work has been published at top robotics conferences ICRA 2021 and Field Robotics Journal, and Robotics and Autonomous systems journal.
During my master's at  Czech Technical University, with the CTU-CRAS team, I participated in the DARPA Subtterainian challenge, which brought together top robotics groups and companies.
I also lead the computer vision subteam for aerial robotics in simulation and real-world deployment at DARPA Subt, placing us second in the simulation with a 500k USD prize. I also co-authored a publication describing the system and problem of deploying a Deep Learning model on an embedded aerial system, published in Field Robotics journal. 
For the last year, I've been working on multi-agent systems for human (drone) swarm interaction - a combination of robotics and game theory. 
Also, my current work is developing exploration for visual-inertial odometry  (VIO) UAVs.
I've enhanced my ability to learn and lead throughout the years, as these two things always go together.
I've had a chance to work with top researchers in my field, lead talented students, and learn from them, even if I was the team lead.
- Five years of frontier robotics research
- linux/bash/zsh - deploying code on various embedded systems
- indoor/outdoor navigation systems
- indoor/outdoor exploration for rotor aerial vehicles
- state estimation for unmanned aerial/ground vehicles
- signal processing - adapting measurements for visual servoing
- sensor fusion - combining different sensors - for example, Depth camera with the thermal camera for accurate fire detection, human position estimation from a 2d camera, and depth map (using a Kalman Filter for fusing the two estimates)
- C++ - 5 years of deploying code on aerial systems, optimizing code for working together with UAV control, state estimation - high load and reliability code
- ROS - deep experience with the system, am part of the open-source ROS system for UAV simulation/deployment - made entirely on ROS
- Swarms - I've also worked on swarm research for aerial platforms in recent years. One of the examples - combined a swarm of 5 drones with human control using pose estimation and gesture detection - showcases MRS drone system capability.
- OpenCV - since aerial platforms tend to have limited GPU/CPU capability (due to heavy control system), I've used classical computer vision methods for different tasks - 2d image position to 3d world position - fire detection - window detection.
- MachineLearning - a big part of my work included training and testing various ML models and then upgrading them for using on embedded systems - using optimization technics as OpenVino, for parallel processing five cameras onboard a UAV to detect artifacts in caves/metros/mines.
- Academic writing - authored an ICRA 2021 (and an extended version) paper and co-authored another two.