Dr. Ince received his PhD degree in Electrical and Electronics Engineering from Cukurova University, Turkey in 2005. His PhD thesis was awarded with an international PhD scholarship by National Scientific Research Council of Turkey (TUBITAK) and during this period he worked a visiting scholar at the University of Technology Graz, Austria and at the University of Minnesota. He obtained dual Post-Doc training in the fields of biosignal processing and computational neuroscience at the Brain Sciences Center, VA Medical Center, Minneapolis and Neuroscience Department at the University of Minnesota. Before joining the Department of Biomedical Engineering in 2013, Dr. Ince was a Research Assistant Professor in the Electrical and Computer Engineering Department at the University of Minnesota.
Biomedical Signal Processing (BIOE 4342/6342)
Awards and Honors:
My research interests span a variety of basic and translational research in the rapidly growing area of neural engineering and biomedical signal processing. Areas of special interest are clinical neuroengineering, neural signal processing for brain machine interfaces, machine learning for neuromarker discovery and biomedical instrumentation for healthcare and assisted living. My lab will strive for research that contributes not only to algorithm development but to the discovery of new methods for diagnosis and therapy that can be applied in clinical practice as well. In this scheme, my lab work closely with researchers from diverse fields such as cardiology, psychiatry, neuroscience, neurosurgery and neurology.
Fikri Goksu, Nuri F.Ince, Ahmed H.Tewfik, “Greedy solutions for the construction of sparse spatial and spatio-spectral filters in brain-computer interface applications”, Neurocomputing, Januray 2013.
Ibrahim Onaran, Nuri F. Ince, A. Enis Cetin, “Sparse spatial filter via a novel objective function minimization with smooth L1 regularization”, Biomedical Signal Processing and Control , October 2012.
Aviva Abosch, David Lanctin, Ibrahim Onaran, Lynn Eberly, and Nuri F. Ince, “Long-term Recordings of Local Field Potentials from Implanted Deep Brain Stimulation Electrodes”, Neurosurgery, 2012.
Ibrahim Onaran, Nuri F. Ince , Enis Cetin, “Classification of Multichannel ECoG Related to Individual Finger Movements with Redundant Spatial Projections”, IEEE Engineering in Medicine and Biology Conf. (EMBC'11), Boston USA, Aug. 2011.
Sami Arica, Nuri F. Ince, Abdi Bozkurt, Ahmet Birand, Ahmed H. Tewfik, Prediction of pharmacologically induced baroreflex sensitivity from local time and frequency domain indices of R-R interval and systolic blood pressure signals obtained during deep breathing, Computers in Biology and Medicine Volume 41 Issue 7, July, 2011.
Nuri F. Ince, Gupta R, Arica S, Tewfik AH, Ashe J, Pellizzer G., “High accuracy decoding of movement target direction in non-human primates based on common spatial patterns of local field potentials.” PLoS ONE. 2010.
Charidimos Tzagarakis, Nuri F. Ince, Arthur Leuthold, and Giuseppe Pellizzer, "Beta-band activity during motor planning reflects response uncertainty", Journal of Neuroscience, 2010, Vol. 30 (34).
Nuri F. Ince, Akshay Gupte, Thomas Wichmann, James Ashe, Thomas Henry, Margaret Bebler, Lynn Eberly, and Aviva Abosch, “Selection of Optimal Programming Contacts Based on Local Field Potential Recordings from Subthalamic Nucleus in Patients with Parkinson’s Disease”, Neurosurgery, August 2010 - Volume 67 - Issue 2 - p 390–397.
Nuri F. Ince, Giuseppe Pellizzer, Ahmed H. Tewfik, Katie Nelson, Arthur Leuthold, Kate McClannahan, Massoud Stephane, “Classification of Schizophrenia with Spectro-Temporo-Spatial MEG Patterns in Working Memory”, Clinical Neurophysiology, Elsevier, Volume 120, Issue 6, June 2009, Pages 1123-1134.
Nuri F. Ince, Fikri Goksu, Ahmed Tewfik, “ECoG Based Brain Computer Interface with Subset Selection”, Invited chapter, Communications in Computer and Information Science (CCIS) Book Series Springer, Biomedical Engineering Systems and Technologies,Vol25, 2008.
Nuri F. Ince, Sami Arica, Ahmed Tewfik, "Classification of Single Trial Motor Imagery EEG recordings with Subject Adapted Non-Dyadic Arbitrary Time-Frequency Tilings", J. Neural Eng. 3 (2006) 235-244.