Murat Akcakaya

Riek, N.T., Susam, B.T., Hudac, C.M., Conner, C.M., Akcakaya, M., Yun, J., White, S.W., Mazefsky, C.A., & Gable, P.A. (2024). Feedback Related Negativity Amplitude is Greatest Following Deceptive Feedback in Autistic Adolescents. J Autism Dev Disord, 54(9), 3376-3386.Springer Nature. doi: 10.1007/s10803-023-06038-y.

Eldeeb, S., & Akcakaya, M. (2022). EEG guided electrical stimulation parameters generation from texture force profiles. J Neural Eng, 19(6), 066042.IOP Publishing. doi: 10.1088/1741-2552/aca82e.

Kocanaogullari, A., Akcakaya, M., & Erdogmus, D. (2022). Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry. IEEE Trans Pattern Anal Mach Intell, 44(9), 5590-5601.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TPAMI.2021.3075915.

Liu, B., Akcakaya, M., & McDermott, T.E. (2022). Reduced Order Model of Transactive Bidding Loads. IEEE TRANSACTIONS ON SMART GRID, 13(1), 667-677.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TSG.2021.3112510.

Mak, J., Kocanaogullari, D., Huang, X., Kersey, J., Shih, M., Grattan, E.S., Skidmore, E.R., Wittenberg, G.F., Ostadabbas, S., & Akcakaya, M. (2022). Detection of Stroke-Induced Visual Neglect and Target Response Prediction Using Augmented Reality and Electroencephalography. IEEE Trans Neural Syst Rehabil Eng, 30, 1840-1850.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TNSRE.2022.3188184.

Marghi, Y.M., Kocanaogullari, A., Akcakaya, M., & Erdogmus, D. (2022). Active recursive Bayesian inference using Renyi information measures. PATTERN RECOGNITION LETTERS, 154, 90-98.Elsevier. doi: 10.1016/j.patrec.2022.01.009.

Riek, N.T., So, S., Akcakaya, M., & Yun, M. (2022). Selection of Classifiers to Enhance Efficacy of Metal/Organic Hybrid Sensor Array for VOC and Toxic Gas Identification. IEEE SENSORS JOURNAL, 22(20), 19136-19143.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/JSEN.2022.3198014.

Susam, B., Riek, N., Akcakaya, M., Xu, X., de Sa, V., Nezamfar, H., Diaz, D., Craig, K., Goodwin, M., & Huang, J. (2022). Automated Pain Assessment in Children Using Electrodermal Activity and Video Data Fusion via Machine Learning. IEEE Trans Biomed Eng, 69(1), 422-431.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TBME.2021.3096137.

Susam, B.T., Riek, N.T., Beck, K., Eldeeb, S., Hudac, C.M., Gable, P.A., Conner, C., Akcakaya, M., White, S., & Mazefsky, C. (2022). Quantitative EEG Changes in Youth With ASD Following Brief Mindfulness Meditation Exercise. IEEE Trans Neural Syst Rehabil Eng, 30, 2395-2405.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TNSRE.2022.3199151.

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. Sci Rep, 11(1), 6000.Springer Nature. doi: 10.1038/s41598-021-85362-8.

Eldeeb, S., Sybeldon, M., Susam, B., Akcakaya, M., Wozny, T., Pan, J., Richardson, R.M., Bagic, A., & Antony, A. (2021). Person-dependent seizure detection using statistical CUSUM detector: Preliminary results. EXPERT SYSTEMS WITH APPLICATIONS, 184, 115551.Elsevier. doi: 10.1016/j.eswa.2021.115551.

Elkhadrawi, M., Stevens, B.A., Wheeler, B.J., Akcakaya, M., & Wheeler, S. (2021). Machine learning classification of false-positive human immunodeficiency virus screening results. Journal of Pathology Informatics, 12(1). doi: 10.4103/jpi.jpi-7-21.

Elkhadrawi, M., Stevens, B.A., Wheeler, B.J., Akcakaya, M., & Wheeler, S. (2021). Machine Learning Classification of False-Positive Human Immunodeficiency Virus Screening Results. J Pathol Inform, 12(1), 46.Elsevier. doi: 10.4103/jpi.jpi_7_21.

Gonzalez-Navarro, P., Celik, B., Moghadamfalahi, M., Akcakaya, M., Fried-Oken, M., & Erdoğmuş, D. (2021). Feedback Related Potentials for EEG-Based Typing Systems. Front Hum Neurosci, 15, 788258.Frontiers. doi: 10.3389/fnhum.2021.788258.

Koçanaoğulları, A., Smedemark-Margulies, N., Akcakaya, M., & Erdoğmuş, D. (2021). Geometric Analysis of Uncertainty Sampling for Dense Neural Network Layer. IEEE Signal Process Lett, 28, 867-871.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.

Özdenizci, O., Eldeeb, S., Demir, A., Erdoğmuş, D., & Akçakaya, M. (2021). EEG-based texture roughness classification in active tactile exploration with invariant representation learning networks. Biomed Signal Process Control, 67, 102507.Elsevier. 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. Biosens Bioelectron, 175, 112903.Elsevier. 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 Nature. 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. Sci Rep, 10(1), 20755.Springer Nature. 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. Biomed Eng Online, 19(1), 23.Springer Nature. 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. 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 Nature. 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. 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. 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 Trans Neural Syst Rehabil Eng, 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. J Neurosci Methods, 313, 44-53.Elsevier. 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. J Neural Eng, 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. J Neurosci Methods, 320, 98-106.Elsevier. doi: 10.1016/j.jneumeth.2019.03.018.

Kocanaogullari, A., Marghi, M.Y., Akcakaya, M., & Erdogmus, D. (2019). An active recursive state estimation framework for brain-interfaced typing systems. BRAIN-COMPUTER INTERFACES, 6(4), 149-161.Taylor & Francis. 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. 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. Biomed Signal Process Control, 39, 263-270.Elsevier. 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. 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. J Neurosci Methods, 303, 169-177.Elsevier. 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. J Neural Eng, 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. J Neurosci Methods, 293, 174-182.Elsevier. 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 Trans Biomed Eng, 65(7), 1460-1467.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TBME.2017.2758643.

Koçanaoğulları, A., Akçakay, M., & Erdoğmuş, D. (2018). On Analysis of Active Querying for Recursive State Estimation. IEEE Signal Process Lett, 25(6), 743-747.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2018.2823271.

Koçanaoğulları, A., Marghi, Y.M., Akçakaya, M., & Erdoğmuş, D. (2018). Optimal Query Selection Using Multi-Armed Bandits. IEEE Signal Process Lett, 25(12), 1870-1874.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/LSP.2018.2878066.

Marghi, Y.M., Gonzalez-Navarro, P., Quivira, F., McLean, J., Girvent, B., Moghadamfalahi, M., Akcakaya, M., & Erdogmus, D. (2018). Signal models for brain interfaces based on evoked response potential in EEG. In Signal Processing and Machine Learning for Brain-Machine Interfaces. (pp. 193-218).Institution of Engineering and Technology (IET). doi: 10.1049/pbce114e_ch10.

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 Nature. 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 Trans Biomed Eng, 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). A Probabilistic Active Learning Algorithm Based on Fisher Information Ratio. IEEE Trans Pattern Anal Mach Intell, 40(8), 2023-2029.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TPAMI.2017.2743707.

Chen, Q., Müftü, S., Meral, F.C., Tuncali, K., & Akçakaya, M. (2017). Model-based optimal planning of hepatic radiofrequency ablation. Math Med Biol, 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. 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 Trans Neural Syst Rehabil Eng, 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, Fourati, H., & Iniewski, K. (Eds.). (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 Trans Neural Syst Rehabil Eng, 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 Trans Signal Process, 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. 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.Taylor & Francis. 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. 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 Trans Neural Syst Rehabil Eng, 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 Trans Signal Process, 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.Taylor & Francis. 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 Recognit Lett, 38(1), 120-131.Elsevier. 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). 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.

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

Akcakaya, M., & Nehorai, A. (2008). Performance analysis of the Ormia ochracea's coupled ears. J Acoust Soc Am, 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.

Kocanaogullari, D., Huang, X., Mak, J., Shih, M., Skidmore, E., Wittenberg, G.F., Ostadabbas, S., & Akcakaya, M. (2021). Fine-tuning and Personalization of EEG-based Neglect Detection in Stroke Patients. In Annu Int Conf IEEE Eng Med Biol Soc, 2021, (pp. 1096-1099).Institute of Electrical and Electronics Engineers (IEEE).United States. doi: 10.1109/EMBC46164.2021.9630794.

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. 1-7).Association for Computing Machinery (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).Institute of Electrical and Electronics Engineers (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), 00, (pp. 4772-4776).Institute of Electrical and Electronics Engineers (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), 00, (pp. 3082-3086).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/icassp.2019.8683308.

Demir, A., Eldeeb, S., Akçakaya, M., & Erdoğmuş, 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), 00, (pp. 1-6).Institute of Electrical and Electronics Engineers (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), 00, (pp. 1-6).Institute of Electrical and Electronics Engineers (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., Al Hassan, H.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), 00, (pp. 1-6).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/mlsp.2019.8918774.

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