Contact Info

Biography

Website: http://users.rowan.edu/~polikar

Education:
BS - Electrical Engineering (Istanbul Technical University)
MS -  Electrical Eng. and Biomedical Eng (Iowa State University)
Ph.D. - Electrical Eng. and Biomedical Eng. (Iowa State University)

Research Expertise:
The overarching scope of my research is development of fundamental computational intelligence approaches and statistical learning models for challenging problems in machine learning. Under this main umbrella, my work has focused on three primary areas 1) incremental (continuous) learning from streaming or batches of data obtained from dynamic, nonstationary, drifting, uncertain or even adversarial environments where the learning model may possibly be under malicious attack; 2) development and adaptation of ensemble based approaches for a broad spectrum of underexplored areas of machine learning, such as missing data, data fusion and concept drift in recurrent nonstationary environments,  and 3) applications of above mentioned approaches to practical problems, such as early diagnosis of neurological disorders or species identification and classification in metagenomics.

Honors and Awards:
IEEE Computational Intelligence Magazine Best Paper Award

IEEE Computational Intelligence Society Service Award for Chair of Technical Committee
on Data Mining and Big Data Analytics

Electrical and Computer Eng. Dept. Heads Association, Innovative Program of the Year Award

Professional Progress in Engineering Midcareer Alumni Award, Iowa State Univ., Ames, IA

Rowan University Research and Scholarly Activity Achievement Award

IEEE Senior Member Elevation

National Science Foundation CAREER award

New Century Scholars Fellowship, Stanford University, Palo Alto, CA

Biomedical Engineering Society Young Investor Travel Award

National Effective Teaching Institute, American Society of Engineering Education

Professional Memberships:
Member of Editorial Board, Neural Networks                      
Associate Editor, IEEE Transactions on Neural Networks and Learning Systems              
IEEE   
International Neural Network Society                                              
ABET, Program Evaluator

 

Recent Publications:
Binaco R., Calzaretto N., Epifano J., McGuire S., Umer M., Emrani S., Wasserman V., Libon J. and Polikar R., “Machine Learning Analysis of Digital Clock Drawing Test Performance for Differential Classification of Mild Cognitive Impairment Subtypes versus Alzheimer’s Disease,” Journal of the International Neuropsychological Society, accepted, 2020. 

Umer M., Frederickson C., Polikar R., “Vulnerability of Covariate Shift Adaptation Against Malicious Poisoning Attack,” Int. Joint Conf. on Neural Networks (IJCNN 2019), Budapest, Hungary, 2019. DOI: 10.1109/IJCNN.2019.8851748

Frederickson C., Moore M., Dawson G., Polikar R., “Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning,” Int. Joint Conf. on Neural Networks (IJCNN 2018), Rio de Janerio, Brazil, 2018. DOI: 10.1109/IJCNN.2018.8489495

G. Ditzler, J. LaBarck, J. Ritchie, G. Rosen and R. Polikar, “Extensions to Online Feature Selection Using Bagging and Boosting,” IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 9, pp. 4504-4509, 2018. DOI: 10.1109/TNNLS.2017.2746107

G. Ditzler, R. Polikar, and G. Rosen, “A Sequential Learning Approach for Scaling up Filter-Based Feature Subset Selection,” IEEE Transactions on Neural Networks & Learning Systems, vol. 29, no. 6, pp.2530-2544, 2018. DOI: 10.1109/TNNLS.2017.2697407