Books:

Zollanvari, A., Machine Learning with Python: Theory and Implementation, Springer, available September 14, [link], (2023).

Peer Reviewed Journals:

2023

Yazdi, S. S. H., Shafiei, S., Kapanov, A., Shakhin, Y., Namadmalan, A., Zollanvari, A., & Bagheri, M., A Wireless Charging System Based on a DR-IPT to Power a UAV From Distribution Poles. IEEE Transactions on Industry Applications, (2023).

Mukhamediya, A., Fazli, S., & Zollanvari, A., On the Effect of Log-Mel Spectrogram Parameter Tuning for Deep Learning-based Speech Emotion Recognition. IEEE Access, (2023).

Nurmanova, V., Akhmetov, Y., Bagheri, M., Zollanvari, A., & Phung, T., A confidence level estimation technique for reliable Data-Driven FRA interpretation in air-core winding faults. International Journal of Electrical Power & Energy Systems, 148, 108942, (2023).

Alimbayev, A., Zhakhina, G., Gusmanov, A., Sakko, Y., Yerdessov, S., Arupzhanov, I., & Gaipov, A., Predicting 1-year mortality of patients with diabetes mellitus in Kazakhstan based on administrative health data using machine learning. Scientific Reports, 13(1), 8412, (2023).

2022

Dolzhikova, I., Abibullaev, B., Sameni, R., & Zollanvari, A., Subject-Independent Classification of Motor Imagery Tasks in EEG Using Multisubject Ensemble CNN. IEEE Access, 10, 81355-81363, (2022).

Abibullaev, B., Kunanbayev, K., & Zollanvari, A., Subject-Independent Classification of P300 Event-Related Potentials Using a Small Number of Training Subjects. IEEE Transactions on Human-Machine Systems, 52(5), 843-854, (2022).

Akhmetov, Y., Nurmanova, V., Bagheri, M., Zollanvari, A., & Gharehpetian, G. B., A bootstrapping solution for effective interpretation of transformer winding frequency response. IEEE Transactions on Instrumentation and Measurement, 71, 1-11, (2022).

2021

Serikbay, A., Bagheri, M., Zollanvari, A., Phung, B. T., Accurate Surface Condition Classification of High Voltage Insulators based on Deep Convolutional Neural Networks, Accepted for publication at IEEE Transactions on Dielectrics and Electrical Insulation, (2021).

Nurmanova, V., Akhmetov, Y., Bagheri, M., Zollanvari, A., Phung, BT., Gharehpetian, G., Confidence Level Estimation for Advanced Decision-making in Transformer Short-circuit Fault Diagnosis, Accepted for publication at IEEE Transactions on Industry Applications, (2021).

Zollanvari, A., Abibullaev. B., Bias Correction for Linear Discriminant Analysis, Pattern Recognition Letters, 151, 41-47, (2021).

Abibullaev. B., Zollanvari, A., A Systematic Deep Learning Model Selection for P300-Based Brain Computer Interface, IEEE Transactions on Systems, Man, Cybernetics: Systems, doi: 10.1109/TSMC.2021.3051136, (2021).

2020

Zollanvari, A., Kunanbayev, K., Bitaghsir, S. A., Bagheri, M.,  Transformer Fault Prognosis Using Deep Recurrent Neural Network Over Vibration Signals, In Press, IEEE Transactions on Instrumentation & Measurement, (2020).

Nurmanova, V., Akhmetov, Y., Bagheri, M., Zollanvari, A., Gharehpetian, G. B., A New Diagnostic Technique for Reliable Decision-making on Transformer FRA Data in Inter-turn Short-circuit Condition, In Press, IEEE Transactions on Industrial Informatics, (2020).

Abibullaev, A., Dolzhikova, I., Zollanvari, A., A Brute-force CNN Model Selection for Accurate Classification of Sensorimotor Rhythms in BCIs, IEEE Access, 8, 101014-101023, (2020).

2019

Zollanvari, A., Dougherty, E., Optimal Bayesian Classification with Vector Autoregressive Data Dependency, IEEE Transactions on Signal Processing, 67, 3073-3086, (2019).

Abibullaev, B., Zollanvari, A., Saduanov, B., Alizadeh, T., Design and Optimization of a BCI-Driven Telepresence Robot Through Programming by Demonstration, IEEE Access, 7, 11625-111636, (2019).

Nurmanova, V., Bagheri, M., Zollanvari, A., Alikhmet, K. Akhmetov, G., Gharehpetian, A., A New Transformer FRA Measurement Technique to Reach Smart Interpretation for Inter-disk Faults, IEEE Transactions on Power Delivery, 34, 1508-1519, (2019).

Zollanvari, A., James, A. P., Sameni, R., A Theoretical Analysis of the Peaking Phenomenon in Classification, In Press, Journal of Classification, (2019), doi: 10.1007/s00357-019-09327-3.

B. Abibullaev, Zollanvari, A., Learning Discriminative Spatiospectral Features of ERPs for Accurate Brain-Computer Interfaces, IEEE Journal of Biomedical and Health Informatics, 23, 2009-2020, (2019).

Zollanvari, A., Abdirash, M., Dadlani, A., Abibullaev, B., Asymptotically Bias-Corrected Regularized Linear Discriminant Analysis for Cost-Sensitive Binary Classification, IEEE Signal Processing letters, 26, 1300-1304, (2019).

2018

Bagheri, M., Zollanvari, A., Nezhivenko, S., Transformer Fault Condition Prognosis Using Vibration Signals over Cloud Environment, IEEE Access, 6, 9862-9874, (2018).

Bagheri, M., Nezhivenko, S., Salay Naderi, M., Zollanvari, A., A New Vibration Analysis Approach for Transformer Fault Prognosis Over Cloud Environment, International Journal of Electrical Power and Energy Systems, 100, 104-116, (2018).

2017

Zollanvari, A., Non-Optimality of the Maximum-Dependence Tree in Classification, IEEE Signal Processing Letters, 24, 71-75, (2017).

Zollanvari, A., Alterovitz, G., SNP by SNP by Environment Interaction Network of Alcoholism, BMC Systems Biology, 11 (3), (2017).

Hassani Saadi, H., Sameni, R., Zollanvari, A., Interpretive Time-Frequency Analysis of Genomic Sequences, BMC Bioinformatics, 18 (4), (2017).

Zollanvari, A., Kizilirmak, R. C., Kho, Y. H., Hernández-Torrano, D., Predicting Students’ GPA and Developing Intervention Strategies Based on Self-Regulatory Learning Behaviors, IEEE Access, 5,23792-23802, (2017).

Mathew, J., Zollanvari, A., James, A., Edge-Aware Spatial Denoising Filtering Based on a Psychological Model of Stimulus Similarity, IEEE Access, 6, 3433-3447, (2017).

B Abibullaev, J An, SH Lee, JI Moon. Design and Evaluation of Action Observation and Motor Imagery based BCIs using NIRS. Measurement, vol. 98, pp. 250-261, Elsevier, (2017).

2016

Bakir, D., James, A., Zollanvari, A., An Efficient Method to Estimate the Optimum Regularization Parameter in RLDA, Bioinformatics, 32, 3461-3468, (2016).

Zollanvari, A., Dougherty, E.,Incorporating Prior Knowledge Induced from Stochastic Differential Equations in Classification of Stochastic Observations, EURASIP Journal on Bioinformatics and Systems Biology, 20, (2016).

N.A. Bhagat, A. Venkatakrishnan, B. Abibullaev, E.J. Artz, N. Yozbatiran, A. Blank, J. French, C. Karmonik, R.G.Grossman, M.K O’Malley, G. Francisco, J.L. Contreras-Vidal. Design and optimization of an EEG-based brain machine interface (BMI) to an upper-limb exoskeleton for stroke survivors. , vol. 10, March, (2016).

2015

Zollanvari, A., High-Dimensional Statistical Learning, Roots, Justifications, and Potential Machineries, Cancer Informatics, 5, 109-121, (2015).

Zollanvari, A., Dougherty, E.,Generalized ConsistentError Estimator of Linear Discriminant Analysis, IEEE Transactions on Signal Processing, 60:2804-2814, (2015).

J.G. Cruz-Garza, Z.R. Hernandez, T. Tse, E. Caducoy, B. Abibullaev, J.L. Contreras-Vidal. A novel experimental and analytical approach to the multimodal neural decoding of intent during social interaction in freely-behaving human infants; JoVE (Journal of Visualized Experiments), doi:10.3791/53406, October, (2015).

C.H. Park, J.H Seo, D. Kim, B. Abibullaev, H. Kwon, Y.H. Lee, M.Y. Kim, K. Kim, J.S. Kim, E.Y. Joo, S.B. Hong, (2015, Feb). Source Imaging in Partial Epilepsy in Comparison with Presurgical Evaluation and Magnetoencephalography. Journal of Clinical Neurology, 11:e12, February 17, (2015).

2014

Braga-Neto, U., Zollanvari, A., Dougherty, E.,Cross-Validation Under Separate Sampling: Strong Bias and How to Correct It, Bioinformatics, 30 (23): 3349-3355, (2014).

Villa, A., Zollanvari, A., Alterovitz, G., Cagetti, M. G. Strohmenger, L., Abati, S.,Prevalence of Halitosis in Children Considering Oral Hygiene, Gender and Age, International Journal of Dental Hygiene, 12: 208-212, (2014).

Zollanvari, A., Dougherty, E.,Moments and Root-Mean-Square Error of the Bayesian MMSE Estimator of Classification Error in the Gaussian Model, Pattern Recognition, 47: 2178-2192, (2014).

B. Abibullaev, J An, S.H. Jin, and J.I. Moon. Classification of brain hemodynamic signals arising from visual action observation tasks for brain-computer interfaces: An fNIRS study, Measurement, Elsevier, (2014).

2013

Zollanvari, A., Hua, J., & Dougherty E., Analytical Study of Performance of Linear Discriminant Analysis in Stochastic Settings, Pattern Recognition, 46 (11): 3017-3029, (2013).

Zollanvari, A. & Genton, M. G., On Kolmogorov AsymptoticsofEstimatorsof theMisclassificationError Rate in Linear Discriminant. Analysis, Sankhya A, The Indian Journal of Statistics, 75 (2): 300-326, (2013).

Warner, J., Zollanvari, A., Ding, Q., Zhang, P., Snyder, G., & Alterovitz, G., Temporal Phenome Analysis of a Large Electronic Health Record Cohort Enables Identification of Hospital-acquired Complications, Journal of American Medical Informatics Association, doi:10.1136/amiajnl-2013-001861, (2013).

Esfahani, M. S., Knight J., Zollanvari, A., Yoon, B., & Dougherty E., Classifier Design Given an Uncertainty Class of Feature Distributions via Regularized Maximum Likelihood and the Incorporation of Biological Pathway Knowledge in Steady-state Phenotype Classification, Pattern Recognition, 46 (10): 2783-2797, (2013).

B. Abibullaev, J An, S.H. Lee, S.H. Jin, and J.I. Moon. Minimizing inter-subject variability in FNIRS based brain computer interfaces via multiple-kernel support vector learning. Medical Engineering Physics, Elsevier, (2013).

2012

Quo, C. Kaddi, Phan, J. C., Zollanvari, A., Xu, M., Wang, M. & Alterovitz, G., Reverse Engineering Bio-molecular Systems Using -Omic Data: Challenges, Progress, and Opportunities, Brief. Bioinformatics, 13 (4): 430-445, (2012).

Zollanvari, A., Braga-Neto, U., & Dougherty E., Exact Representation of the Second-order Moments for Resubstitution and Leave-one-out Error Estimation for Linear Discriminant Analysis in the Univariate Heteroskedastic Gaussian Model, Pattern Recognition, 45 (2): 908-917, (2012).

B. Abibullaev and J. An. Classification of frontal cortex hemodynamic response during cognitive tasks using wavelet transforms and machine learning algorithms. Medical Engineering Physics, 34(10):1394–410, Elsevier, (2012).

2011

Zollanvari, A., Braga-Neto, U., & Dougherty E., Analytic Study of Performance of Error Estimators for Linear Discriminant Analysis, IEEE Transactions on Signal Processing, 59 (9):4238-4255, (2011).

Dougherty E., Zollanvari, A., & Braga-Neto, U., The Illusion of Distribution-Free Classification in High-Throughput Biology, Current Genomics, 12 (5), 333-341, (2011).

B. Abibullaev and J. An. Decision support algorithm for diagnosis of ADHD disorder using electroencephalograms. Journal of Medical Systems, 36(4):2675–2688, Springer, (2011).

B. Abibullaev, J. An, and J.I. Moon. Neural network classification of brain hemodynamic responses from four mental tasks. International Journal of Optomechatronics, 5(4):340–359, Taylor & Francis, (2011).

B. Abibullaev and H.D. Seo. A new QRS detection method using wavelets and artificial neural networks. Journal of Medical Systems, 35(4):683–691, Springer, (2011).

2010

Zollanvari, A., Braga-Neto, U., & Dougherty E., Joint Sampling Distribution Between Actual and Estimated Classification Errors for Linear Discriminant Analysis, IEEE Transactions on Information Theory, 56 (2): 784-804, (2010).

Zollanvari, A., Masnadi-Shirazi, M. A., A Class of Comprehensive Constraints for Design of PCWLSE Laguerre and FIR Filters: A Boost in Performance, Signal Processing, 90 (4), 1118-1130, (2010).

B. Abibullaev, M.S. Kim, and H.D. Seo. Epileptic spike detection using continuous wavelet transforms and artificial neural networks. , 8(1):33–48, 2010. International journal of wavelets, multiresolution and information processing, Worldscientific, (2010).

B. Abibullaev, M.S. Kim, and H.D. Seo. Seizure detection in temporal lobe epileptic EEGs using the best basis wavelet functions. Journal of Medical Systems, 34(4):755–765, Springer, (2010).

2009

34. Zollanvari, A., Cunningham, M., Braga-Neto, U., & Dougherty E., Analysis and Modeling of Time-Course Gene-Expression Profiles from Nanomaterial-Exposed Primary Human Epidermal Keratinocytes. BMC Bioinformatics, 10, (2009).

35. Zollanvari, A., Braga-Neto, U., & Dougherty E., On the Sampling Distribution of Resubstitution and Leave-One-Out Error Estimators for Linear Classifiers. Pattern Recognition, 42 (11): 2705-2723, (2009).

2008

Masnadi-Shirazi, M. A.  & Zollanvari, A., Complex Digital Laguerre Filter Design with Weighted Least Square Error Subject to Magnitude and Phase Constraints, Signal Processing, 10 (4), 796-810, (2008).

Conferences:

2023

Abilgazym, A., Zollanvari, A., & Bagheri, M., High-Voltage Insulator Surface Pollution Classification Using Insulator Type-Specific CNNs. In 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (pp. 1-6). IEEE, (2023).

2022

Akhmetov, Y., Nurmanova, V., Bagheri, M., Zollanvari, A., & Phung, T., Overhead Line Insulator Type Classification Using YOLOv3 Architectures, 2022 International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA) (pp. 36-40), IEEE, (2022).

Reihanian, S., & Zollanvari, A., Optimal Bayesian Regression for Serially Dependent Training Observations, 2022 30th European Signal Processing Conference (EUSIPCO) (pp. 1522-1525). IEEE, (2022).

Serikbay, A., Bagheri, M., Zollanvari, A., & Saukhimov, A. A., CNN-based Classification of Contaminated High Voltage Insulator Surface, 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (pp. 1-5), (2022).

Dolzhikova, I., Abibullaev, B., Zollanvari, A., An Ensemble of Convolutional Neural Networks for Zero-Calibration ERP-Based BCIs, Presented at 10th International Winter Conference on Brain-Computer Interface (BCI), 1-4, (2022).

2021

Dolzhikova, I., Abibullaev. B., Sameni, R., Zollanvari, A., An Ensemble CNN for Subject-Independent Classification of Motor Imagery-based EEG, Presented at IEEE Engineering in Medicine and Biology Conference (EMBC), (2021).

Kainolda, Y., Abibullaev. B., Sameni, R., Zollanvari, A., Is Riemannian Geometry Better than Euclidean in Averaging Covariance Matrices for CSP-based Subject-Independent Classification of Motor Imagery?, Presented at IEEE Engineering in Medicine and Biology Conference (EMBC), (2021).

Kunanbayev. K., Temirbek. I., Zollanvari, A., Complex Encoding, in the proceedings of 2021 International Joint Conference Neural Networks (IJCNN), (2021).

Kunanbayev. K., Abibullaev. B., Zollanvari, A., Data Augmentation for P300-based Brain-Computer Interfaces Using Generative Adversarial Networks, in the proceedings of the 9th International Winter Conference on Brian-Computer Interface, (2021).

Kunanbayev. K., Azhigulov, D., Abibullaev. B., Zollanvari, A., Deep Transfer Learning for Subject-Independent ERP-based BCIs, in the proceedings of the 9th International Winter Conference on Brian-Computer Interface, (2021).

Zhagyparova, K., Zhagypar, R., Zollanvari, A., Akhtar, M. T., Supervised Learning-based Sound Source Distance Estimation Using Multivariate Features, IEEE Region 10 Symposium (TENSYMP), (2021).

Nurmanova, V., Akhmetov, Y., Bagheri, M., Zollanvari, A., Gharehpetian, G., Phung, BT., A New Transformer Winding RLC Model to Study the Effect of the Disk Space Variation on FRA Signature, 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), (2021).

Baktiyar, A., Baizhan, D., Bagheri, M., Zollanvari, A., Murzabulatov, A., Serikbay, A., Remote Monitoring of Outdoor High Voltage Insulator using Deep Learning-based Image Processing, 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), (2021).

Serikbay, A., Bagheri, M., Zollanvari, A., High Voltage Insulators Condition Analysis using Convolutional Neural Network, 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), (2021).

2020

Nurmanova, V., Akhmetov, Y., Bagheri, M., Zollanvari, A., Gharehpetian, G. B., Phung, T., A New Transformer FRA Test Setup for Advanced Interpretation and Winding Short-circuit Prediction, IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Spain, 2020.

A. Oleinikov, B. Abibullaev, M. Folgheraiter, On the Classification of Electromyography Signals to Control a Four Degree-Of-Freedom Prosthetic Device, in 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

B. Saduanov, D. Tokmurzina, K. Kunanbayev and B. Abibullaev, Design and Optimization of a Real-Time Asynchronous BCI Control Strategy for Robotic Manipulator Assistance, in 2020 8th International Winter Conference on Brain-Computer Interface (BCI).

2019

Abibullaev, B., Orazayev, Y., Zollanvari, A., Novel Spatiospectral Features of ERPs Enhances Brain-Computer Interfaces, in Proceedings of the 7th IEEE International Winter Conference on Brain-Computer Interface, Korea, (2019).

A. Tuleuov and B. Abibullaev, Deep Learning Models for Subject-Independent ERP-based Brain-Computer Interfaces, in the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), March 20-23, 2019, San Francisco, CA, USA.

B. Abibullaev, Y. Orazayev, and A. Zollanvari, Novel Spatiospectral Features of ERPs Enhances Brain-Computer Interfaces , in Brain-Computer Interface (BCI), 2019 7th International Conference on.1em plus 0.5em minus 0.4em IEEE, 2019, GangWon, South Korea.

2018

Zollanvari, A., Dougherty, E. R., Optimal Bayesian Classification When the Training Observations are Serially Dependent, in Proceedings of New York Scientific Data Summit (NYSDS), Brookhaven National Laboratory, August 2018.

Tursynbek, N., Ghahramany, G., Nabavi, S., Zollanvari, A., Predictive Meta-analysis of Multiple Microarray Datasets: An Application to Classification of Malignant Gliomas, in Proceedings of International Conference on Bioinformatics and Biomedicine, IEEE BIBM, Spain, 2018.

Bagheri, M. Nurmanova, V., Zollanvari, A., Nezhivenko, S., Phung, B. T., IoT Application in Transformer Fault Prognosis Using Vibration Signal, in Proceedings of IEEE International Conference on High Voltage, Athens, Greece, September 2018.

B. Saduanov, D. Tokmurzina, T. Alizadeh, and B. Abibullaev, Brain-computer interface humanoid pre-trained for interaction with people, in 2018 ACM/IEEE International Conference on Human-Robot Interaction.1em plus 0.5em minus 0.4emACM, March 5-8, 2018, pp. 229–230, Chicago, IL, USA.

A. Oleinikov, B. Abibullaev, A. Shintemirov, and M. Folgheraiter, Feature extraction and real-time recognition of hand motion intentions from emgs via artificial neural networks, in Brain-Computer Interface (BCI), 2018 6th International Conference on.1em plus 0.5em minus 0.4em IEEE, 2018, pp. 1-5, GangWon, South Korea.

G. Lee, S. H. Jin, S. T. Yang, J. An and B. Abibullaev, Cross-correlation between HbO and HbR as an effective feature of motion artifact in fNIRS signal, 2018 6th International Conference on Brain-Computer Interface (BCI), pp. 1-3, 2018, IEEE, GangWon, South Korea.

B. Saduanov, T. Alizadeh, J. An, and B. Abibullaev, Trained by demonstration humanoid robot controlled via a bci system for telepresence, in Brain-Computer Interface (BCI), 2018 6th International Conference on.1em plus 0.5em minus 0.4emIEEE, 2018, pp. 1–4, January, GangWon, South Korea.

B. Saduanov, T. Alizadeh, J. An, and B. Abibullaev, Trained by demonstration humanoid robot controlled via a bci system for telepresence, in Brain-Computer Interface (BCI), 2018 6th International Conference on.1em plus 0.5em minus 0.4emIEEE, 2018, pp. 1–4, January, GangWon, South Korea.

2017

Reihanian, S., Zollanvari, A., James, A. Adaptive Face Space Model with Dynamic Neural Priors and Sparse Coding, IEEE International Conference on Circuits and Systems, 389-392, 2017.

Zollanvari, A., An Analytical Perspective on Challenges and Future Trends in Genomic Data Analysis, 3rd International Conf. on Personalized Medicine & Global Health, Kazakhstan, 2017.

G. Lee, S. H. Jin, S. H. Lee, B. Abibullaev, and J. An, FNIRS motion artifact correction for overground walking using entropy based unbalanced optode decision and wavelet regression neural network, in Multisensor Fusion and Integration for Intelligent Systems (MFI), 2017 IEEE International Conference on.1em plus 0.5em minus 0.4emIEEE, 2017, pp. 186–193, Daegu, South Korea.

A. Zhumadilova, D. Tokmurzina, A. Kuderbekov and and B. Abibullaev. Design and Evaluation of a P300 Visual Brain-Computer Interface Speller in Cyrillic Characters. In the 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), IEEE, 2017, Aug 28 — Sept 1, Lisbon, Portugal.

B. Abibullaev. Learning Suite of Kernel Feature Spaces Enhances SMR-Based EEG-BCI Classification. In the 5th International Winter Conference on Brain-Computer Interface, IEEE, 2017, January 9-11, GangWon, South Korea.

D. Nurseitov, A. Serekov, A. Shintemirov and B. Abibullaev. Design and Evaluation of a P300-ERP based BCI System for Real-Time Control of a Mobile Robot. In the 5th International Winter Conference on Brain-Computer Interface, IEEE, 2017, January 9-11, Gangwon, South Korea.

2016

Hassani Saadi, H., Sameni, R., Zollanvari, A., Interpretive Time-Frequency Analysis of Genomic Sequences, ACM-BCB, Seattle, 2016.

B. Abibullaev and J An. On Robust Classification of Hemodynamic Signals for BCIs via Multiple Kernel ν-SVMs. Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference, 2016, Oct10-15, Daejeon, South Korea.

2015

J.G. Cruz-Garza, Z.R. Hernandez, M. Megjhani, B. Abibullaev, T. Tse, E. Caducoy, and JL Contreras-Vidal. Neural development of social cognition in the first two ears of life — Early findings. In Society for Neuroscience 2015 Oct 17-21; Chicago, USA.

Z.R. Hernandez, A.J. Arenas-Castellanos, J.G. Cruz-Garza, M. Megjhani, B. Abibullaev, Sri. R.P. Maddi, T. Tse, C. Armstrong, W. Long, J.L. Contreras-Vidal Decoding Intent From Non-invasive EEG in Freely Behaving Infants In Ninth Biennial Meeting of the Cognitive Development Society 2015 Oct 9-10; Ohio, USA.

A.J. Arenas-Castellanos, Z.R. Hernandez, J.G. Cruz-Garza, M. Megjhani, B. Abibullaev, Sri. R.P. Maddi, T. Tse, C. Armstrong, W. Long, J.L. Contreras-Vidal A developmental Analysis of Behaviors Related to the Mirror Neuron System in 6-24 Months Infants In Ninth Biennial Meeting of the Cognitive Development Society 2015 Oct 9-10; Ohio, USA.

Z.R. Hernandez, J.G. Cruz-Garza, T. Tse, E. Caducoy, B. Abibullaev, J.L. Contreras-Vidal. Supervised Classification of Intended Behaviors Using Electroencephalography (EEG) from Freely-Behaving Infants: Early Findings. In 12th Annual GCC Conference on Theoretical and Computational Neuroscience, Rice University, Houston, TX, United States, February 6-7, 2015.

2014

Bobba, S. S., Zollanvari, A. & Alterovitz, G., Bayesian Prognostic Model for Genomic Discovery, Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC), 248-250, 2014.

N. A. Bhagat, A Venkatakrishnan, B. Abibullaev, E. J. Artz, A.A. Blank, J. A. French, N. Yozbatiran, and R. G. Grossman, M. K. OMalley, J. L. Contreras-Vidal, G. E. Francisco Control of a Therapeutic Exoskeleton to Facilitate Personalized Robotic Rehabilitation of the Upper Limb. , Westin Arlington, Nov. 19-20 2014, United States.

C.H.Park, B. Abibullaev, E.Y. Joo, S.C. Hong, and S.B. Hong. The evaluation of accuracy and clinical usefulness of 3D EEG source localization analysis. In the 19th Korean Epilepsy Congress, Seoul, Republic of Korea, June 12-14 2014.

2013

Zollanvari, A. & Dougherty, E., Application of Double Asymptotics and Random Matrix Theory in Error Estimation of Regularized Linear Discriminant Analysis. (Invited paper), Proceedings of Global SIP Conference, 57-59, 2013.

Zollanvari, A. & Dougherty, E., Random Matrix Theory in Pattern Classification: An Application to Error Estimation. Presented in Asilomar Conference on Signals, Systems & Computers (November 2013).

Zollanvari, A., Braga-Neto, U., & Dougherty E., Effect of Mixing Probabilities on the Bias of Cross-Validation Under Separate Sampling, Proceedings of IEEE Genomic Signal Processing and Statistics (GENSIPS), 98-99, 2013.

Zollanvari, A., Hua. J, & Dougherty E., Performance of Linear Discriminant Analysis in Stochastic Settings, Proceedings of IEEE International Conference on Acoustic, Speech and Signal Processing, (ICASSP), 3437-3441, 2013.

Warner, J. Zollanvari, A., Zhang, P. & Alterovitz, G., Temporal Phenome Analysis of a Large Clinical Cohort Predicts Hospital-Acquired Complications, Presented at American Medical Informatics Association symposium (Summit on Clinical Research Informatics), 2013 (Poster).

Alessandro, V. & Zollanvari, A. & Sonis S., Modulating Cancer Progression from Leukoplakia via Bayesian Gene Networks, Presented at American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2013 (Poster).

Koppula, S., Zollanvari, A., & Alterovitz, G., Robust Prediction-Based Analysis for Genome-Wide Association and Expression Studies, Presented at American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2013 (Podium).

S.H. Lee, J. An, G. Jang, S.H. Jin, B. Abibullaev, and J.I. Moon. Neural activity during observation, imagery, and execution of eating: An fNIRS pilot study. In the 19th Annual Meeting of the Organization for Human Brain Mapping, Seattle, WA, United States, June 16-20 2013.

J. An, S.H. Jin, S.H. Lee, G. Jang, B. Abibullaev, J. Ahn, H. Lee, and J.I. Moon. Cortical activation pattern for grasping during observation, imagery, execution, FES, and observation-FES integrated BCI: An fNIRS pilot study. In the 35th Annual Int. Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Osaka, Japan, July 3-7 2013.

J. An, S.H. Lee, S.H. Jin, B. Abibullaev, G. Jang, J. Ahn, H. Lee, and J.I. Moon. The beginning of neurohaptics: Controlling cognitive interaction via brain haptic interface. In the 2013 IEEE International Winter Workshop on Brain-Computer Interface, Gangwon Province, Korea, Feb. 18-20 2013.

2012

Deng, M., Zollanvari A., & Alterovitz, G., A Bayesian framework for knowledge propagation, discovery, and integration under specific contexts, Proceedings of American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2012.

Parikh, N., Zollanvari, A., & Alterovitz, G., An automated Bayesian framework for integrative gene expression analysis and predictive medicine, Proceedings of American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2012.

Marwah, K., Katzin, D., Zollanvari, A., Noy, N. F., Ramoni, M., & Alterovitz, G., Context-Specific Ontology Integration: A Bayesian approach, Proceedings of American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2012.

Zollanvari, A. & Alterovitz, G., Prediction-based Bayesian network analysis of gene sets for genome-wide association and expression studies, Presented at American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2012 (Podium).

Marwah, K, Zollanvari, A., & Alterovitz, G., Hyper-experiments: Bayesian inference and annotation For GEO, Presented at American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2012 (Podium).

Zollanvari, A., Thomas, J., & Alterovitz, G., A Prediction-based Bayesian framework for quantifying the interaction of demographics and genetics: application to alcohol dependence, Presented at American Medical Informatics Association symposium 2012 (Poster).

Alterovitz, G., A., Zollanvari, A., &. Wu, A., ­Multinet Bayesian Networks for Integrative Genomic Discovery: Application to Genetic Epistatic Interactions in HIV, Presented at American Medical Informatics Association symposium (Summit on Translational Bioinformatics) 2012 (Poster).

B. Abibullaev, J. An, J.I. Moon, S.H. Lee, and S.H. Jin. A study on the BCI-Robot assisted stroke rehabilitation framework using brain hemodynamic signals. In the 9th Int Conference on Ubiquitous Robots and Ambient Intelligence, IEEE proceedings, Daejon, Korea, November 26-29,2012.

B. Abibullaev, J. An, S.H.Lee, S.H. Jin, J.I Moon, H.J. Lee. Decoding of Brain Hemodynamic Responses for Brain-Computer Interfaces via Ensemble Support Vector Learning. In the Human-Computer Interaction Conference, Gangwon-Do, Korea, January 11-13,2012.

2011

Esfahani, M. S., Zollanvari, A., Yoon, B., & Dougherty E., Designing Enhanced Classifiers Using Prior Process Knowledge: Regularized Maximum-Likelihood, Proceedings of IEEE Genomic Signal Processing and Statistics (GENSIPS), 2011.

Zollanvari, A., Saccone, N. L, Bierut, L. J., Ramoni, M. F., & Alterovitz, G. Is the reduction of Dimensionality to small number of features always necessary in constructing predictive models for analysis of complex diseases or behaviors? Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC), 2011.

2010

Zollanvari, A., Braga-Neto, U., & Dougherty E., RMS bound and sample size consideration for error estimation in linear discriminant analysis, Proceedings of IEEE Genomic Signal Processing and Statistics (GENSIPS), 2010.

B. Abibullaev, W.S. Kang, S.H. Lee, J. An, and H.D. Seo. Near-infrared spectroscopy in the analysis of functional brain activity during cognitive tasks. In 2010 IEEE Sensors Conference, Hawaii, United States, November 1-4, 2010.

B. Abibullaev, W.S. Kang, S.H. Lee, and J. An. Recognition of brain hemodynamic mental response for brain-computer interface. In International Conference on Control Automation and Systems, IEEE proceedings, Gyeonggi-do, Korea, October 27-30 2010.

S.H. Lee, B. Abibullaev, W.S. Kang, and J. An. Analysis of attention deficit hyperactivity disorder in EEG using wavelet transform and self organizing maps. In International Conference on Control Automation and Systems, IEEE proceedings, Gyeonggi-do, Korea, October 27-30 2010.

W.S. Kang, B. Abibullaev, S.H. Lee, and J. An. Path planning algorithm using the values clustered by k-means. In the 15th Int. Symposium on Artificial Life and Robotics, Japan, February 4-6 2010.

2009

Zollanvari, A. & Masnadi-Shirazi, M. A., A class of comprehensive constraints for the PCWLSE filter design: A boost in performance. Proceedings of IEEE International Conference on Acoustic, Speech and Signal Processing, (ICASSP), 2009.

Zollanvari, A., Braga-Neto, U., & Dougherty E. Sample size calculation from specified RMS of the resubstitution error for linear classifiers. Proceedings of IEEE Genomic Signal Processing and Statistics (GENSIPS), 2009.

B. Abibullaev, H.D. Seo, W.S. Kang, and J. An. A wavelet-based method for detecting and localizing epileptic neural spikes in EEG signals. In the 2nd Int. Conf. on Interaction Sciences: Information Technology, Culture and Human. ACM, Seoul, Korea, Nov. 24- 26 2009.

B. Abibullaev and H.D. Seo. Epileptic seizures detection using continuous time wavelet based neural networks. In the 6th International Conference on Information Technology: New Generations, IEEE Computer Society, Las Vegas,Nevada, United States, April 27-29 2009.

W.S. Kang, B. Abibullaev, S.H. Lee, and J. An. A study on brain activation during playing a computer game using fNIRS. In the 32th conference of Korean Info. Proc. Soc., Seoul Korea, November 22-24, 2009.

2007

B. Abibullaev, H.D. Seo, and M.S. Kim. Classification system of EEG during cognitive mental tasks. In Int. Conference on Engineering and ICT, Melaka, Malaysia, November 27-29, 2007.

H.D. Seo and B. Abibullaev. Analysis of EEG signals by the continuous wavelet transforms. In the 5th Int. Joint Conference on Global Academic Networking, Vladivastok, Russia, June 7-9 2007.

2006

Zollanvari, A. & Masnadi-Shirazi, M. A., Peak constraint weighted least square Laguerre network implementation in complex domain by a new method satisfying continuous constraints of the problem. Proceedings of IEEE International Conference information & communication technologies: from theory to applications, (ICTTA), 2006.

Masnadi-Shirazi, M. A. & Zollanvari, A., A novel approach to optimal array pattern synthesis. Proceedings of IEEE International Conference information & communication technologies: from theory to applications, (ICTTA), 2006.

Zollanvari, A. & Masnadi-Shirazi, M. A., An extended e-perturbation method to semi-infinite quadratic programming of constrained Laguerre filters, Proceedings of 14th Iranian Conference on Electrical Engineering (ICEE), 2006.

Zollanvari, A. & Masnadi-Shirazi, M. A., An extended dual parameterization method to constrained least square Laguerre filter design. Proceedings of IEEE International Conference on Acoustic, Speech and Signal Processing, (ICASSP), 2006.

Masnadi-Shirazi, M. A. & Zollanvari, A., An extended perturbation method to semi-infinite quadratic programming of constrained FIR filters. Proceedings of IEEE International Conference on Acoustic, Speech and Signal Processing, (ICASSP), 2006.

2005

Masnadi-Shirazi, M. A. & Zollanvari, A., Constrained weighted least square design of digital Laguerre filters. Proceedings of International Symposium on Telecommunications, 2005.