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Murat Akcakaya

Associate Professor
Personal Website Electrical and Computer Engineering

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PhD, Electrical and Systems Engineering, Washington University, 2010

MSc, Electrical and Systems Engineering, Washington University, 2010

BSc, Electrical and Electronics Engineering, Middle East Technical University, 2005

Eldeeb, S., Susam, B.T., Akcakaya, M., Conner, C.M., White, S.W., & Mazefsky, C.A. (2021). Trial by trial EEG based BCI for distress versus non distress classification in individuals with ASD. SCIENTIFIC REPORTS, 11(1), 6000.Springer Science and Business Media LLC. doi: 10.1038/s41598-021-85362-8.

Kocanaogullari, A., Akcakaya, M., & Erdogmus, D. (2021). Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/tpami.2021.3075915.

Kocanaogullari, A., Smedemark-Margulies, N., Akcakaya, M., & Erdogmus, D. (2021). Geometric Analysis of Uncertainty Sampling for Dense Neural Network Layer. IEEE Signal Processing Letters, 28, 1.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/lsp.2021.3072292.

Liu, B., Akcakaya, M., & Mcdermott, T.E. (2021). Automated Control of Transactive HVACs in Energy Distribution Systems. IEEE TRANSACTIONS ON SMART GRID, 12(3), 2462-2471.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TSG.2020.3042498.

Ozdenizci, O., Eldeeb, S., Demir, A., Erdogmus, D., & Akcakaya, M. (2021). EEG-based texture roughness classification in active tactile exploration with invariant representation learning networks. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 67, 102507.Elsevier BV. doi: 10.1016/j.bspc.2021.102507.

So, S., Khalaf, A., Yi, X., Herring, C., Zhang, Y., Simon, M.A., Akcakaya, M., Lee, S., & Yun, M. (2021). Induced bioresistance via BNP detection for machine learning-based risk assessment. BIOSENSORS & BIOELECTRONICS, 175, 112903.Elsevier BV. doi: 10.1016/j.bios.2020.112903.

Xiang, Y., Akcakaya, M., Sen, S., & Nehorai, A. (2021). Target Detection via Cognitive Radars Using Change-Point Detection, Learning, and Adaptation. CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 40(1), 233-261.Springer Science and Business Media LLC. doi: 10.1007/s00034-020-01465-z.

Eldeeb, S., Weber, D., Ting, J., Demir, A., Erdogmus, D., & Akcakaya, M. (2020). EEG-based trial-by-trial texture classification during active touch. SCIENTIFIC REPORTS, 10(1), 20755.Springer Science and Business Media LLC. doi: 10.1038/s41598-020-77439-7.

Khalaf, A., & Akcakaya, M. (2020). A probabilistic approach for calibration time reduction in hybrid EEG-fTCD brain-computer interfaces. BIOMEDICAL ENGINEERING ONLINE, 19(1), 23.Springer Science and Business Media LLC. doi: 10.1186/s12938-020-00765-4.

Khalaf, A., Nabian, M., Fan, M., Yin, Y., Wormwood, J., Siegel, E., Quigley, K.S., Barrett, L.F., Akcakaya, M., Chou, C.A., & Ostadabbas, S. (2020). Analysis of multimodal physiological signals within and between individuals to predict psychological challenge vs. threat. EXPERT SYSTEMS WITH APPLICATIONS, 140, 112890.Elsevier BV. doi: 10.1016/j.eswa.2019.112890.

Khalaf, A., Sejdic, E., & Akcakaya, M. (2020). Hybrid EEG–fTCD Brain–Computer Interfaces. In Neuroergonomics. (pp. 295-314).Springer International Publishing. doi: 10.1007/978-3-030-34784-0_15.

Liu, B., Akcakaya, M., Reiman, A.P., & McDermott, T.E. (2020). Distribution system segmented model simplification with independent dynamically changing end-use loads. ELECTRIC POWER SYSTEMS RESEARCH, 188, 106528.Elsevier BV. doi: 10.1016/j.epsr.2020.106528.

Dagois, E., Khalaf, A., Sejdic, E., & Akcakaya, M. (2019). Transfer Learning for a Multimodal Hybrid EEG-fTCD Brain–Computer Interface. IEEE Sensors Letters, 3(1), 1-4.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/lsens.2018.2879466.

Eldeeb, S., Akcakaya, M., Sybeldon, M., Foldes, S., Santarnecchi, E., Pascual-Leone, A., & Sethi, A. (2019). EEG-based functional connectivity to analyze motor recovery after stroke: A pilot study. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 49, 419-426.Elsevier BV. doi: 10.1016/j.bspc.2018.12.022.

Gonzalez-Navarro, P., Marghi, Y.M., Azari, B., Akcakaya, M., & Erdogmus, D. (2019). An Event-Driven AR-Process Model for EEG-Based BCIs With Rapid Trial Sequences. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 27(5), 798-804.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TNSRE.2019.2903840.

Khalaf, A., Sejdic, E., & Akcakaya, M. (2019). A novel motor imagery hybrid brain computer interface using EEG and functional transcranial Doppler ultrasound. JOURNAL OF NEUROSCIENCE METHODS, 313, 44-53.Elsevier BV. doi: 10.1016/j.jneumeth.2018.11.017.

Khalaf, A., Sejdic, E., & Akcakaya, M. (2019). EEG-fTCD hybrid brain computer interface using template matching and wavelet decomposition. JOURNAL OF NEURAL ENGINEERING, 16(3), 036014.IOP Publishing. doi: 10.1088/1741-2552/ab0b7f.

Khalaf, A., Sejdic, E., & Akcakaya, M. (2019). Common spatial pattern and wavelet decomposition for motor imagery EEG-fTCD brain-computer interface. JOURNAL OF NEUROSCIENCE METHODS, 320, 98-106.Elsevier BV. doi: 10.1016/j.jneumeth.2019.03.018.

Koçanaoğulları, A., M. Marghi, Y., Akçakaya, M., & Erdoğmuş, D. (2019). An active recursive state estimation framework for brain-interfaced typing systems. Brain-Computer Interfaces, 6(4), 149-161.Informa UK Limited. doi: 10.1080/2326263x.2020.1729652.

Xiang, Y., Akcakaya, M., Sen, S., Erdogmus, D., & Nehorai, A. (2019). Target tracking via recursive Bayesian state estimation in cognitive radar networks. SIGNAL PROCESSING, 155, 157-169.Elsevier BV. doi: 10.1016/j.sigpro.2018.09.035.

Haghighi, M., Moghadamfalahi, M., Akcakaya, M., & Erdogmus, D. (2018). EEG-assisted modulation of sound sources in the auditory scene. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 39, 263-270.Elsevier BV. doi: 10.1016/j.bspc.2017.08.008.

Kelsey, M., Akcakaya, M., Kleckner, I.R., Palumbo, R.V., Barrett, L.F., Quigley, K.S., & Goodwin, M.S. (2018). Applications of sparse recovery and dictionary learning to enhance analysis of ambulatory electrodermal activity data. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 40, 58-70.Elsevier BV. doi: 10.1016/j.bspc.2017.08.024.

Khalaf, A., Kersey, J., Eldeeb, S., Alankus, G., Grattan, E., Waterstram, L., Skidmore, E., & Akcakaya, M. (2018). EEG-based neglect assessment: A feasibility study. JOURNAL OF NEUROSCIENCE METHODS, 303, 169-177.Elsevier BV. doi: 10.1016/j.jneumeth.2018.03.019.

Khalaf, A., Sejdic, E., & Akcakaya, M. (2018). Towards optimal visual presentation design for hybrid EEG-fTCD brain-computer interfaces. JOURNAL OF NEURAL ENGINEERING, 15(5), 056019.IOP Publishing. doi: 10.1088/1741-2552/aad46f.

Khalaf, A., Sybeldon, M., Sejdic, E., & Akcakaya, M. (2018). A brain-computer interface based on functional transcranial doppler ultrasound using wavelet transform and support vector machines. JOURNAL OF NEUROSCIENCE METHODS, 293, 174-182.Elsevier BV. doi: 10.1016/j.jneumeth.2017.10.003.

Kleckner, I.R., Jones, R.M., Wilder-Smith, O., Wormwood, J.B., Akcakaya, M., Quigley, K.S., Lord, C., & Goodwin, M.S. (2018). Simple, Transparent, and Flexible Automated Quality Assessment Procedures for Ambulatory Electrodermal Activity Data. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 65(7), 1460-1467.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TBME.2017.2758643.

Kocanaogullari, A., Akcakaya, M., & Erdogmus, D. (2018). On Analysis of Active Querying for Recursive State Estimation. IEEE SIGNAL PROCESSING LETTERS, 25(6), 743-747.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2018.2823271.

Kocanaogullari, A., Marghi, Y.M., Akcakaya, M., & Erdogmus, D. (2018). Optima Query Selection Using Multi-Armed Bandits. IEEE SIGNAL PROCESSING LETTERS, 25(12), 1870-1874.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2018.2878066.

Onuk, A.E., Akcakaya, M., Bardhan, J., Erdogmus, D., Brooks, D.H., & Makowski, L. (2018). Dirichlet Priors for MAP Inference of Protein Conformation Abundances from SAXS. Journal of Signal Processing Systems, 90(2), 167-174.Springer Science and Business Media LLC. doi: 10.1007/s11265-016-1141-6.

Reiman, A.P., McDermott, T.E., Akcakaya, M., & Reed, G.F. (2018). Electric Power Distribution System Model Simplification Using Segment Substitution. IEEE TRANSACTIONS ON POWER SYSTEMS, 33(3), 2874-2881.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TPWRS.2017.2753100.

Rothfuss, M.A., Franconi, N.G., Star, A., Akcakaya, M., Gimbel, M.L., & Sejdic, E. (2018). Automatic Early-Onset Free Flap Failure Detection for Implantable Biomedical Devices. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 65(10), 2290-2297.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TBME.2018.2793763.

Sourati, J., Akcakaya, M., Erdogmus, D., Leen, T.K., & Dy, J.G. (2018). Probabilistic Active Learning Algorithm Based on Fisher Information Ratio. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 40(8), 2023-2029.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TPAMI.2017.2743707.

Chen, Q., Muftu, S., Meral, F.C., Tuncali, K., & Akcakaya, M. (2017). Model-based optimal planning of hepatic radiofrequency ablation. MATHEMATICAL MEDICINE AND BIOLOGY-A JOURNAL OF THE IMA, 34(3), 415-431.Oxford University Press (OUP). doi: 10.1093/imammb/dqw011.

Gonzalez-Navarro, P., Moghadamfalahi, M., Akcakaya, M., & Erdogmus, D. (2017). Spatio-temporal EEG models for brain interfaces. SIGNAL PROCESSING, 131, 333-343.Elsevier BV. doi: 10.1016/j.sigpro.2016.08.001.

Haghighi, M., Moghadamfalahi, M., Akcakaya, M., Shinn-Cunningham, B.G., & Erdogmus, D. (2017). A Graphical Model for Online Auditory Scene Modulation Using EEG Evidence for Attention. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 25(11), 1970-1977.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TNSRE.2017.2712419.

Higger, M., Akcakaya, M., Orhan, U., & Erdogmus, D. (2017). Multisensor Data Fusion. In Multisensor Data Fusion: From Algorithms and Architectural Design to Applications. (pp. 157-168).CRC Press. doi: 10.1201/b18851.

Higger, M., Quivira, F., Akcakaya, M., Moghadamfalahi, M., Nezamfar, H., Cetin, M., & Erdogmus, D. (2017). Recursive Bayesian Coding for BCIs. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 25(6), 704-714.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TNSRE.2016.2590959.

Moghadamfalahi, M., Akcakaya, M., Nezamfar, H., Sourati, J., & Erdogmus, D. (2017). An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 65(20), 5381-5392.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TSP.2017.2728500.

Onuk, E., Badger, J., Wang, Y.J., Bardhan, J., Chishti, Y., Akcakaya, M., Brooks, D.H., Erdogmus, D., Minh, D.D.L., & Makowski, L. (2017). Effects of Catalytic Action and Ligand Binding on Conformational Ensembles of Adenylate Kinase. BIOCHEMISTRY, 56(34), 4559-4567.American Chemical Society (ACS). doi: 10.1021/acs.biochem.7b00351.

Sourati, J., Akcakaya, M., Leen, T.K., Erdogmus, D., & Dy, J.G. (2017). Asymptotic Analysis of Objectives Based on Fisher Information in Active Learning. JOURNAL OF MACHINE LEARNING RESEARCH, 18.

Sybeldon, M., Schmit, L., & Akcakaya, M. (2017). Transfer Learning for SSVEP Electroencephalography Based Brain-Computer Interfaces Using Learn plus plus .NSE and Mutual Information. ENTROPY, 19(1), 41.MDPI AG. doi: 10.3390/e19010041.

Akcakaya, M., Sen, S., & Nehorai, A. (2016). A Novel Data-Driven Learning Method for Radar Target Detection in Nonstationary Environments. IEEE SIGNAL PROCESSING LETTERS, 23(5), 762-766.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2016.2553042.

Orhan, U., Nezamfar, H., Akcakaya, M., Erdogmus, D., Higger, M., Moghadamfalahi, M., Fowler, A., Roark, B., Oken, B., & Fried-Oken, M. (2016). Probabilistic simulation framework for EEG-based BCI design. Brain-Computer Interfaces, 1-15.Taylor & Francis.

Orhan, U., Nezamfar, H., Akcakaya, M., Erdogmus, D., Higger, M., Moghadamfalahi, M., Fowler, A., Roark, B., Oken, B., & Fried-Oken, M. (2016). Probabilistic Simulation Framework for EEG-Based BCI Design. Brain Comput Interfaces (Abingdon), 3(4), 171-185.Informa UK Limited. doi: 10.1080/2326263X.2016.1252621.

Sourati, J., Akcakaya, M., Dy, J.G., Leen, T.K., & Erdogmus, D. (2016). Classification Active Learning Based on Mutual Information. ENTROPY, 18(2), 51.MDPI AG. doi: 10.3390/e18020051.

Akcakaya, M., Muravchik, C., & Nehorai, A. (2015). Biologically inspired antenna array design using ormia modeling. In Biomimetic Technologies: Principles and Applications. (pp. 335-364).Woodhead Publishing.

Ataer-Cansizoglu, E., Akcakaya, M., & Erdogmus, D. (2015). Minor Surfaces are Boundaries of Mode-Based Clusters. IEEE SIGNAL PROCESSING LETTERS, 22(7), 891-895.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2014.2376192.

Higger, M., Akcakaya, M., Nezamfar, H., LaMountain, G., Orhan, U., & Erdogmus, D. (2015). A Bayesian Framework for Intent Detection and Stimulation Selection in SSVEP BCIs. IEEE SIGNAL PROCESSING LETTERS, 22(6), 743-747.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2014.2368952.

Higger, M., Akcakaya, M., Orhan, U., & Erdogmus, D. (2015). 10 Sensor Failure Robust Fusion. (p. 157).CRC Press.

Moghadamfalahi, M., Orhan, U., Akcakaya, M., Nezamfar, H., Fried-Oken, M., & Erdogmus, D. (2015). Language-Model Assisted Brain Computer Interface for Typing: A Comparison of Matrix and Rapid Serial Visual Presentation. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 23(5), 910-920.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TNSRE.2015.2411574.

Onuk, A.E., Akcakaya, M., Bardhan, J., Erdogmus, D., Brooks, D.H., & Makowski, L. (2015). Constrained Maximum Likelihood Estimation of the Abundances of Protein Conformation in a Heterogeneous Structural Ensemble from Small Angle X-ray Scattering Intensity Measurements. BIOPHYSICAL JOURNAL, 108(2), 210A.Elsevier.

Onuk, A.E., Akcakaya, M., Bardhan, J.P., Erdogmus, D., Brooks, D.H., & Makowski, L. (2015). Constrained Maximum Likelihood Estimation of Relative Abundances of Protein Conformation in a Heterogeneous Mixture From Small Angle X-Ray Scattering Intensity Measurements. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 63(20), 5383-5394.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TSP.2015.2455515.

Ahani, A., Wiegand, K., Orhan, U., Akcakaya, M., Moghadamfalahi, M., Nezamfar, H., Patel, R., & Erdogmus, D. (2014). RSVP IconMessenger: icon-based brain-interfaced alternative and augmentative communication. Brain-Computer Interfaces, 1(3-4), 192-203.Informa UK Limited. doi: 10.1080/2326263x.2014.996066.

Akcakaya, M., Peters, B., Moghadamfalahi, M., Mooney, A.R., Orhan, U., Oken, B., Erdogmus, D., & Fried-Oken, M. (2014). Noninvasive brain-computer interfaces for augmentative and alternative communication. IEEE Rev Biomed Eng, 7, 31-49.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/RBME.2013.2295097.

Ataer-Cansizoglu, E., Akcakaya, M., Orhan, U., & Erdogmus, D. (2014). Manifold learning by preserving distance orders. PATTERN RECOGNITION LETTERS, 38(1), 120-131.Elsevier BV. doi: 10.1016/j.patrec.2013.11.022.

Higger, M., Akcakaya, M., & Erdogmus, D. (2013). A Robust Fusion Algorithm for Sensor Failure. IEEE SIGNAL PROCESSING LETTERS, 20(8), 755-758.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2013.2266254.

Akcakaya, M., & Nehorai, A. (2011). MIMO Radar Sensitivity Analysis for Target Detection. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 59(7), 3241-3250.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TSP.2011.2141665.

Akcakaya, M., & Nehorai, A. (2011). Adaptive MIMO Radar Design and Detection in Compound-Gaussian Clutter. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 47(3), 2200-2207.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TAES.2011.5937292.

Akcakaya, M., Muravchik, C.H., & Nehorai, A. (2011). Biologically Inspired Coupled Antenna Array for Direction-of-Arrival Estimation. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 59(10), 4795-4808.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TSP.2011.2160056.

Akcakaya, M. (2010). Biologically Inspired Sensing and MIMO Radar Array Processing.

Akcakaya, M., & Nehorai, A. (2010). Biologically inspired coupled antenna beampattern design. BIOINSPIRATION & BIOMIMETICS, 5(4), 046003.IOP Publishing. doi: 10.1088/1748-3182/5/4/046003.

Akcakaya, M., & Nehorai, A. (2010). MIMO Radar Detection and Adaptive Design Under a Phase Synchronization Mismatch. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 58(10), 4994-5005.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TSP.2010.2054088.

Akcakaya, M., & Nehorai, A. (2008). Performance analysis of the Ormia ochracea's coupled ears. JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 124(4), 2100-2105.Acoustical Society of America (ASA). doi: 10.1121/1.2967862.

Akcakaya, M., Muravchik, C., & Nehorai, A. Biologically inspired antenna array design. Bioinspiration and Biomimetics, 5, 046003.

Koçanaoğulları, A., Akçakaya, M., Oken, B., & Erdoğmuş, D. (2020). Optimal modality selection using information transfer rate for event related potential driven brain computer interfaces. In Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments, (pp. 9-15).ACM. doi: 10.1145/3389189.3389197.

Kocanaogullari, D., Mak, J., Kersey, J., Khalaf, A., Ostadabbas, S., Wittenberg, G., Skidmore, E., & Akcakaya, M. (2020). EEG-based Neglect Detection for Stroke Patients. In Annu Int Conf IEEE Eng Med Biol Soc, 2020, (pp. 264-267).IEEE.United States. doi: 10.1109/EMBC44109.2020.9176378.

Zhu, Y., Xiang, Y., Sen, S., Dagois, E., Nehorai, A., & Akcakaya, M. (2020). Clutter Identification Based on Sparse Recovery and L1-Type Probabilistic Distance Measures. In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020-May, (pp. 4772-4776).IEEE. doi: 10.1109/icassp40776.2020.9054669.

Akcakaya, M. (2019). BAYESIAN METHODS FOR MULTIMODAL DATA FUSION, STATE ESTIMATION, AND CLASSIFICATION. In PSYCHOPHYSIOLOGY, 56, (p. S23).

Dagois, E., Khalaf, A., Sejdic, E., & Akcakaya, M. (2019). Bhattacharyya Distance-based Transfer Learning for a Hybrid EEG-FTCD Brain-computer Interface. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019-May, (pp. 3082-3086).IEEE. doi: 10.1109/icassp.2019.8683308.

Demir, A., Eldeeb, S., Akcakaya, M., & Erdogmus, D. (2019). Dynamic System Identification For Guidance Of Stimulation Parameters In Haptic Simulation Environments. In 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP), 2019-October.IEEE. doi: 10.1109/mlsp.2019.8918815.

Eldeeb, S., Ting, J., Erdogmus, D., Weber, D., & Akcakaya, M. (2019). EEG-Based Texture Classification During Active Touch. In 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP), 2019-October.IEEE. doi: 10.1109/mlsp.2019.8918777.

Goodwin, M., Kleckner, I., Akcakaya, M., Wormwood, J., Jones, R., Barrett, L.F., & Quigley, K. (2019). DEVELOPING NOVEL ANALYTICS TO OVERCOME CHALLENGES WITH AMBULATORY RECORDINGS OF ELECTRODERMAL ACTIVITY. In PSYCHOPHYSIOLOGY, 56, (p. S23).

Khalaf, A., Hassan, H.A.A., Emes, A., Akcakaya, M., & Grainger, B.M. (2019). A Machine Learning Approach for Classifying Faults in Microgrids using Wavelet Decomposition. In 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP), 2019-October.IEEE. doi: 10.1109/mlsp.2019.8918774.

Khalaf, A., Sejdic, E., & Akcakaya, M. (2019). Mutual Information for Transfer Learning in SSVEP Hybrid EEG-fTCD Brain-Computer Interfaces. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019-March, (pp. 941-944).IEEE. doi: 10.1109/ner.2019.8717018.

Marghi, Y.M., Kocanaogullari, A., Akcakaya, M., & Erdogmus, D. (2019). A History-based Stopping Criterion in Recursive Bayesian State Estimation. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019-May, (pp. 3362-3366).IEEE. doi: 10.1109/icassp.2019.8683726.

Xu, X., Craig, K.D., Diaz, D., Goodwin, M.S., Akcakaya, M., Susam, B.T., Huang, J.S., & de Sa, V.R. (2019). Automated Pain Detection in Facial Videos of Children Using Human-Assisted Transfer Learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11326 LNAI, (pp. 162-180).Springer International Publishing. doi: 10.1007/978-3-030-12738-1_12.

Xu, X., Susam, B.T., Nezamfar, H., Diaz, D., Craig, K.D., Goodwin, M.S., Akcakaya, M., Huang, J.S., & de Sa, V.R. (2019). Towards Automated Pain Detection in Children Using Facial and Electrodermal Activity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11326 LNAI, (pp. 181-189).Springer International Publishing. doi: 10.1007/978-3-030-12738-1_13.

Zhu, Y., Xiang, Y., Sen, S., Sejdic, E., Nehorai, A., & Akcakaya, M. (2019). Clutter Identification based on sparse recovery with dynamically changing dictionary sizes for cognitive radar. In Big Data: Learning, Analytics, and Applications, 10989.SPIE. doi: 10.1117/12.2520154.

Dagois, E., Akcakaya, M., Wang, H., Xiang, Y., Kelsey, M., Sen, S., & Nehorai, A. (2018). Clutter identification based on kernel density estimation and sparse recovery. In Compressive Sensing VII: From Diverse Modalities to Big Data Analytics, 10658.SPIE. doi: 10.1117/12.2309320.

Susam, B.T., Akcakaya, M., Nezamfar, H., Diaz, D., Xu, X., de Sa, V.R., Craig, K.D., Huang, J.S., & Goodwin, M.S. (2018). Automated Pain Assessment using Electrodermal Activity Data and Machine Learning. In Annu Int Conf IEEE Eng Med Biol Soc, 2018, (pp. 372-375).IEEE.United States. doi: 10.1109/EMBC.2018.8512389.

Xiang, Y., Kelsey, M., Wang, H., Sen, S., Akcakaya, M., & Nehorai, A. (2018). A Comparison of cognitive approaches for clutter-distribution identification in nonstationary environments. In 2018 IEEE Radar Conference (RadarConf18), (pp. 467-472).IEEE. doi: 10.1109/radar.2018.8378604.

Xu, X., Craig, K.D., Diaz, D., Goodwin, M.S., Akcakaya, M., Susam, B.T., Huang, J.S., & de Sa, V.R. (2018). Automated Pain Detection in Facial Videos of Children using Human-Assisted Transfer Learning. In CEUR Workshop Proc, 2142, (pp. 10-21).Germany.

Xu, X., Susam, B.T., Nezamfar, H., Diaz, D., Craig, K.D., Goodwin, M.S., Akcakaya, M., Huang, J.S., & Virginia, R.D.S. (2018). Towards Automated Pain Detection in Children using Facial and Electrodermal Activity. In CEUR Workshop Proc, 2142, (pp. 208-211).Germany.

Yazdi, G.E., Nezamfar, H., Moghadamfalahi, M., Akcakaya, M., Shafai, B., & Erdogmus, D. (2018). An Adaptive Proportional BCI-Controller for Linear Dynamic Systems. In 2018 World Automation Congress (WAC), 2018-June, (pp. 46-51).IEEE. doi: 10.23919/wac.2018.8430486.

Kelsey, M., Palumbo, R.V., Urbaneja, A., Akcakaya, M., Huang, J., Kleckner, I.R., Barrett, L.F., Quigley, K.S., Sejdic, E., & Goodwin, M.S. (2017). Artifact detection in electrodermal activity using sparse recovery. In Compressive Sensing VI: From Diverse Modalities to Big Data Analytics, 10211.SPIE. doi: 10.1117/12.2264027.

Kelsey, M., Sen, S., Xiang, Y., Nehorai, A., & Akcakaya, M. (2017). Sparse recovery for clutter identification in radar measurements. In Compressive Sensing VI: From Diverse Modalities to Big Data Analytics, 10211.SPIE. doi: 10.1117/12.2264090.

Perez-Rosero, M.S., Rezaei, B., Akcakaya, M., & Ostadabbas, S. (2017). Decoding emotional experiences through physiological signal processing. In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (pp. 881-885).IEEE. doi: 10.1109/icassp.2017.7952282.

Sybeldon, M., Schmit, L., Sejdic, E., & Akcakaya, M. (2017). Transfer learning for EEG based BCI using LEARN++.NSE and mutual information. In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (pp. 2632-2636).IEEE. doi: 10.1109/icassp.2017.7952633.

Xiang, Y., Akcakaya, M., Sen, S., Erdogmus, D., & Nehorai, A. (2017). Target tracking via recursive Bayesian state estimation in radar networks. In 2017 51st Asilomar Conference on Signals, Systems, and Computers, 2017-October, (pp. 880-884).IEEE. doi: 10.1109/acssc.2017.8335475.

Gonzalez-Navarro, P., Moghadamfalahi, M., Akcakaya, M., & Erdogmus, D. (2016). A Kronecker Product Structured EEG Covariance Estimator for a Language Model Assisted-BCI. In International Conference on Augmented Cognition, 9743, (pp. 35-45).Springer International Publishing.Springer International Publishing. doi: 10.1007/978-3-319-39955-3_4.

Haghighi, M., Moghadamfalahi, M., Nezamfar, H., Akcakaya, M., & Erdogmus, D. (2016). Toward a brain interface for tracking attended auditory sources. In 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), 2016-November, (pp. 1-5).IEEE.IEEE. doi: 10.1109/mlsp.2016.7738810.

Kelsey, M., Dallal, A., Eldeeb, S., Akcakaya, M., Kleckner, I., Gerard, C., Quigley, K.S., & Goodwin, M.S. (2016). Dictionary learning and sparse recovery for electrodermal activity analysis. In Compressive Sensing V: From Diverse Modalities to Big Data Analytics, 9857, (p. 98570G).SPIE.International Society for Optics and Photonics. doi: 10.1117/12.2227142.

Khalaf, A., Sybeldon, M., Sejdic, E., & Akcakaya, M. (2016). An EEG and fTCD based BCI for control. In 2016 50th Asilomar Conference on Signals, Systems and Computers, (pp. 1285-1289).IEEE. doi: 10.1109/acssc.2016.7869581.

Sourati, J., Kazmierczak, S.C., Akcakaya, M., Dy, J.G., Leen, T.K., & Erdogmus, D. (2016). Assessing subsets of analytes in context of detecting laboratory errors. In Annu Int Conf IEEE Eng Med Biol Soc, 2016, (pp. 5793-5796).United States. doi: 10.1109/EMBC.2016.7592044.

Sourati, J., Kazmierczak, S.C., Akcakaya, M., Dy, J.G., Leen, T.K., Erdogmus, D.Sourati, J., Kazmierczak, S.C., Akcakaya, M., Dy, J.G., Leen, T.K., Erdogmus, D., Erdogmus, D.Sourati, J., Kazmierczak, S.C., Dy, J.G., Leen, T.K., Akcakaya, M. (2016). Assessing subsets of analytes in context of detecting laboratory errors. In Conf Proc IEEE Eng Med Biol Soc, 2016, (pp. 5793-5796).IEEE.United States. doi: 10.1109/EMBC.2016.7592044.

Moghadamfalahi, M., Gonzalez-Navarro, P., Akcakaya, M., Orhan, U., & Erdogmus, D. (2015). The Effect of Limiting Trial Count in Context Aware BCIs: A Case Study with Language Model Assisted Spelling. In Foundations of Augmented Cognition: 9th International Conference, AC 2015, Held as Part of HCI International 2015, Los Angeles, CA, USA, August 2-7, 2015, Proceedings, 9183, (pp. 281-292).Springer International Publishing.Springer. doi: 10.1007/978-3-319-20816-9_27.

Moghadamfalahi, M., Gonzalez-Navarro, P., Akcakaya, M., Orhan, U., & Erdogmus, D. (2015). The effect of limiting trial count in context aware BCIs: a case study with language model assisted spelling. In International Conference on Augmented Cognition, (pp. 281-292).Springer International Publishing.

Moghadamfalahi, M., Sourati, J., Akcakaya, M., Nezamfar, H., Haghighi, M., & Erdogmus, D. (2015). Active learning for efficient querying from a human oracle with noisy response in a language-model assisted brain computer interface. In 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015-November, (pp. 1-6).IEEE.IEEE. doi: 10.1109/mlsp.2015.7324369.

Onuk, A.E., Akcakaya, M., Bardhan, J., Erdogmus, D., Brooks, D.H., & Makowski, L. (2015). Maximum a posteriori estimation of relative abundances of protein conformations. In 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015-November, (pp. 1-5).IEEE.IEEE. doi: 10.1109/mlsp.2015.7324377.

Qiyong Chen, Muftu, S., Meral, F.C., Tuncali, K., & Akcakaya, M. (2015). Pre-treatment planning for hepatic radiofrequency ablation. In 2015 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), (pp. 1-6).IEEE.IEEE. doi: 10.1109/spmb.2015.7405426.

Sourati, J., Erdogmus, D., Akcakaya, M., Kazmierczak, S.C., & Leen, T.K. (2015). A novel delta check method for detecting laboratory errors. In 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015-November, (pp. 1-6).IEEE.IEEE. doi: 10.1109/mlsp.2015.7324343.

Goodwin, M.S., Haghighi, M., Tang, Q., Akcakaya, M., Erdogmus, D., & Intille, S. (2014). Moving towards a real-time system for automatically recognizing stereotypical motor movements in individuals on the autism spectrum using wireless accelerometry. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, (pp. 861-872).ACM.ACM. doi: 10.1145/2632048.2632096.

Orhan, U., Fernandez-Canellas, D., Akcakaya, M., Brooks, D.H., & Erdogmus, D. (2014). Utilization of temporal trial dependency in ERP based BCIs. In 2014 48th Asilomar Conference on Signals, Systems and Computers, 2015-April, (pp. 26-30).IEEE.IEEE. doi: 10.1109/acssc.2014.7094389.

Haghighi, M., Akcakaya, M., Orhan, U., Erdogmus, D., Oken, B., & Fried-Oken, M. (2013). Initial assessment of artifact filtering for RSVP Keyboard™. In 2013 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), (pp. 1-5).IEEE.IEEE. doi: 10.1109/spmb.2013.6736777.

Higger, M., Akcakaya, M., Orhan, U., & Erdogmus, D. (2013). Robust Classification in RSVP Keyboard. In International Conference on Augmented Cognition, 8027 LNAI, (pp. 443-449).Springer Berlin Heidelberg.Springer Berlin Heidelberg. doi: 10.1007/978-3-642-39454-6_47.

Moghadamfalahi, M., Orhan, U., Akcakaya, M., & Erdogmus, D. (2013). Bayesian Priors for Classifier Design in RSVP Keyboard.

Orhan, U., Akcakaya, M., Erdogmus, D., Roark, B., Moghadamfalahi, M., & Fried-Oken, M. (2013). Comparison of Adaptive Symbol Presentation Methods for RSVP Keyboard.

Akcakaya, M., & Nehorai, A. (2011). MIMO radar sensitivity analysis for target detection. In 2011 IEEE RadarCon (RADAR), (pp. 633-638).IEEE. doi: 10.1109/radar.2011.5960614.

Akcakaya, M., Muravchik, C.H., & Nehorai, A. (2011). Performance analysis of biologically inspired coupled circular antenna array. In 2011 IEEE International Symposium on Antennas and Propagation (APSURSI), (pp. 1530-1533).IEEE.IEEE. doi: 10.1109/aps.2011.5996588.

Akcakaya, M., & Nehorai, A. (2010). Biologically inspired coupled beampattern design. In 2010 International Waveform Diversity and Design Conference, (pp. 48-52).IEEE. doi: 10.1109/wdd.2010.5592352.

Akcakaya, M., & Nehorai, A. (2010). MIMO radar detection and adaptive design in compound-Gaussian clutter. In 2010 IEEE Radar Conference, (pp. 236-241).IEEE.IEEE. doi: 10.1109/radar.2010.5494620.

Akcakaya, M., & Nehorai, A. (2010). MIMO radar detection under phase synchronization errors. In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, (pp. 2578-2581).IEEE. doi: 10.1109/icassp.2010.5496278.

Akçakaya, M., & Nehorai, A. (2010). Biologically inspired coupled beampattern design. In Waveform Diversity and Design Conference (WDD), 2010 International, (pp. 000048-000052).IEEE.

Akcakaya, M., Muravchik, C.H., & Nehorai, A. (2010). Biologically inspired coupled antenna array for direction of arrival estimation. In 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, (pp. 1961-1965).IEEE. doi: 10.1109/acssc.2010.5757883.

Akcakaya, M., Hurtado, M., & Nehorai, A. (2008). MIMO radar detection of targets in compound-Gaussian clutter. In 2008 42nd Asilomar Conference on Signals, Systems and Computers, (pp. 208-212).IEEE.IEEE. doi: 10.1109/acssc.2008.5074393.

Mittwede, S.K., & Bozkurt, E. (2001). Preface. In INTERNATIONAL GEOLOGY REVIEW, 43(7), (p. 577).IEEE. doi: 10.1109/mlsp.2015.7324169.

Research interests

EEG-based Brain Computer Interfaces
Machine learning
Radar Signal Processing
Statistical signal processing