Dr Yasemin Bekiroglu PhD

Dr Yasemin Bekiroglu

Department of Mechanical Engineering
Research Fellow in Robotics

Contact details

Email
y.bekiroglu@bham.ac.uk
Address
School of Mechanical Engineering
University of Birmingham
Edgbaston
Birmingham
B15 2TT

Yasemin completed her PhD in the Computer Vision and Active Perception Lab (CVAP), in theSchool of Computer Science and Communication, at the Royal Institute of Technology (KTH), in Stockholm, Sweden, in November 2012. Her supervisor was Prof. Danica Kragic. She was involved in the EU project CogX. She was a postdoctoral researcher at CVAP until Feb 2016 and involved in the EU project RoboHow and eSMCs. Currently Yasemin works as a postdoctoral researcher in Dr. Rustam Stolkin's research group and her work is funded by the EU project Romans.

Yasemin's research interests include robotics, computer vision and machine learning. More specifically, she interested in learning-based approaches for robot grasping and manipulation using multisensory data.

Qualifications

  •  Ph.D., November 2012, Computer Science, Royal Institute of Technology KTH, Sweden
  • M.S., 2008, Applied Artificial Intelligence, Dalarna University, Sweden
  • M.S., 2007, Computer Engineering, Karadeniz Technical University, Turkey
  • B.S., 2005, Computer Engineering, Karadeniz Technical University, Turkey 2004-2005, Computer Science, Erasmus Student, Roskilde University, Denmark

Biography

Yasemin Bekiroglu received the M.Sc. degree in computer engineering from Karadeniz Technical University, Trabzon, Turkey, and the M.Sc. degree in applied artificial intelligence from Dalarna University,
Dalarna, Sweden. She completed her PhD studies in the Computer Vision and Active Perception Lab (CVAP), in the School of Computer Science and Communication, at the Royal Institute of Technology (KTH), in Stockholm, Sweden, in 2012. Currently, she is a Research Fellow at the University of Birmingham. Her research interests include robotics, computer vision and machine learning. More specifically, she is interested in learning-based approaches for robotic grasping and manipulation using multisensory data.

Publications

  • Pokorny, F T, Billard, A, Kragic, D (2016), Hierarchical Fingertip Space: A Unified Framework for Grasp Planning and In-Hand Grasp Adaptation, IEEE Transactions on Robotics.
  • Journal Article - Bekiroglu, Y, Laaksonen, J, Jørgensen, JA, Kyrki, V, Kragic, D (2011), Assessing grasp
    stability based on learning and haptic data. IEEE Transactions on Robotics, Vol.27,
    No.3, 616–629.
  • Caccamo, S, Bekiroglu, Y, Ek, C H, Kragic, D (2016), Active Exploration Using Gaussian Random Fields and Gaussian Process Implicit Surfaces, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
  • Krug, R, Lilienthal, A J, Kragic, D, Ek, CH, (2016) Probabilistic Consolidation of Grasp Experience, IEEE International Conference on Robotics and Automation (ICRA).
  • Bjorkman, M, Bekiroglu, Y, Hogman, V, Kragic, D (2013), Enhancing Visual Perception of Shape through Tactile Glances. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013, IROS CoTeSys Cognitive Robotics Best Paper Award Finalist.
  • Bekiroglu, Y, Song, D, Wang, L, Kragic, D (2013), A Probabilistic Framework for Task-Oriented Grasp Stability Assessment. IEEE International Conference on Robotics and Automation (ICRA), Best Manipulation Paper Award.

Selected publications are below, for a complete list, please see my personal page: www.yaseminbekiroglu.com