The researcher earned his B.S., M.S. and Ph.D. from the Department of Computer Engineering at Yildiz Technical University, Istanbul, in 2004, 2007 and 2013, respectively.
During his master’s studies, he became interested in image processing. As a result of his MS thesis, he participated in the Biltronik National Project Competition and took second prize in 2008, winning a $10,000 award. He continued studying image processing during work on his Ph.D. as well, and developed a novel background subtraction method. He also applied artificial intelligence methods to interdisciplinary projects such as fluid mechanics in mechanical engineering during his doctoral studies. He has developed many significant correlation equations and neural network solutions in these areas.
After receiving his Ph.D., he joined the Stochastic Robotics Lab as a post-doc researcher. During this period, he focused on developing localization, mapping, exploration and communication methods for multi robot platforms in both 2-d and 3-d environments using a laser scanner and RGBD cameras. He published numerous papers with his team members in the areas of exploration, navigation, robot control and mapping. He has attended international RoboCup competitions every year with his university’s robot team, which won first prize in 2016 and second prize in 2012, 2013 and 2014 in the Virtual Robot Rescue League.
In the summer of 2015, he spent three months at the Department of Biomedical Engineering, University of North Carolina at Chapel Hill. He also gained extensive experience in biomedical image processing during this period.
In May 2016, he moved to Paris for a new academic position. He had been working as a post-doc researcher at CAOR, Centre de Robotique, Mathématiques et Systèmes MINES ParisTech. During this period he focused on light field cameras and their robotic implementation such as 3D reconstruction and SLAM.
From February 2019 to March 2021, he was a member of LITIS Research Lab in University of Rouen Normandy. He worked on Graph Neural Networks where the main logic behind it is to create data driven approach onto the chemical molecule based inputs which can be represented by graph.
Currently, he is working as a R&I researcher at interdigital in Rennes. He is focusing on data compression for non-Euclidean domain data by ML approaches.
He has a strong mathematical background and programming skills and excellent skills in all C derivatives, Java, Matlab, Python and low level programming such as Assembly. He has used C/C++ programming language for 18 years. He has substantial experience in Robot Operating System (ROS), microcontrollers and OpenCV. Since he has taken part in many robot projects, he has much experience in parallel programming, network programming, Machine Learning and Deep Learning. He has a solid background in both heuristic and mathematical optimization as well.
During his master’s studies, he became interested in image processing. As a result of his MS thesis, he participated in the Biltronik National Project Competition and took second prize in 2008, winning a $10,000 award. He continued studying image processing during work on his Ph.D. as well, and developed a novel background subtraction method. He also applied artificial intelligence methods to interdisciplinary projects such as fluid mechanics in mechanical engineering during his doctoral studies. He has developed many significant correlation equations and neural network solutions in these areas.
After receiving his Ph.D., he joined the Stochastic Robotics Lab as a post-doc researcher. During this period, he focused on developing localization, mapping, exploration and communication methods for multi robot platforms in both 2-d and 3-d environments using a laser scanner and RGBD cameras. He published numerous papers with his team members in the areas of exploration, navigation, robot control and mapping. He has attended international RoboCup competitions every year with his university’s robot team, which won first prize in 2016 and second prize in 2012, 2013 and 2014 in the Virtual Robot Rescue League.
In the summer of 2015, he spent three months at the Department of Biomedical Engineering, University of North Carolina at Chapel Hill. He also gained extensive experience in biomedical image processing during this period.
In May 2016, he moved to Paris for a new academic position. He had been working as a post-doc researcher at CAOR, Centre de Robotique, Mathématiques et Systèmes MINES ParisTech. During this period he focused on light field cameras and their robotic implementation such as 3D reconstruction and SLAM.
From February 2019 to March 2021, he was a member of LITIS Research Lab in University of Rouen Normandy. He worked on Graph Neural Networks where the main logic behind it is to create data driven approach onto the chemical molecule based inputs which can be represented by graph.
Currently, he is working as a R&I researcher at interdigital in Rennes. He is focusing on data compression for non-Euclidean domain data by ML approaches.
He has a strong mathematical background and programming skills and excellent skills in all C derivatives, Java, Matlab, Python and low level programming such as Assembly. He has used C/C++ programming language for 18 years. He has substantial experience in Robot Operating System (ROS), microcontrollers and OpenCV. Since he has taken part in many robot projects, he has much experience in parallel programming, network programming, Machine Learning and Deep Learning. He has a solid background in both heuristic and mathematical optimization as well.
Contact Information: muhammetbalcilar [at] gmail [dot] com scholar.google.fr/citations?user=LRyde44AAAAJ&hl=en https://github.com/balcilar https://medium.com/@balcilar https://twitter.com/balcilar_m |