I am a Research Fellow at Australian National University (ANU), currently hosted by Dr. Hanna Kurniwati. Before joining ANU, I completed my Ph.D. from The University of Queensland (UQ) on September, 2019, under the supervision of Prof. Mandyam V. Srinivasan. My research interests are in computer vision, machine learning, and deep learning. I am particularly interested in the areas of collision avoidance strategies, Robust Decision-making and Learning, and Object detection. Before starting my PhD, I was working as a lecturer at the American International University-Bangladesh (AIUB) - in the department of Computer Science. I also worked as a software engineer at Infra Blue Technology (IBT Games).
- Deep Learning
- Machine Learning
- Robust Decision-making and Learning
- Bio-inspired collision avoidance strategies
- Karmaker, D., Schiffner, I., Wilson, M. and Srinivasan, M.V., 2018, December. Image Denoising with Weighted Orientation-Matched Filters (WORM). In 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO) (pp. 1022-1027). IEEE.
- Karmaker, D., Schiffner, I., Wilson, M. and Srinivasan, M.V., 2018, November. The bird gets caught by the WORM: tracking multiple deformable objects in noisy environments using Weight ORdered logic Maps. In International Symposium on Visual Computing (pp. 332-343). Springer, Cham.
- Molloy, T.L., Garden, G.S., Perez, T., Schiffner, I., Karmaker, D. and Srinivasan, M.V., 2018. An inverse differential game approach to modelling bird mid-air collision avoidance behaviours. IFAC-PapersOnLine, 51(15), pp.754-759.
- Karmaker, D., Schiffner, I., Strydom, R. and Srinivasan, M.V., 2016, November. WHoG: A weighted HoG-based scheme for the detection of birds and identification of their poses in natural environments. In 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV) (pp. 1-7). IEEE.
- Rahman, M.A.U., Miah, M.S.U., Fahad, M.A. and Karmaker, D., 2014, December. SHIMPG: Simple human interaction with machine using Physical Gesture. In 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV) (pp. 301-305). IEEE.