The College of Engineering - Electrical & Computer Engineering
Professor and Chair of Electrical and Computer Engineering
Dr. Polikar's (Ph.D. 2000, Iowa State University) current research interests include signal processing, pattern recognition, neural systems, machine learning and computational models of learning, with applications to biomedical engineering and imaging, chemical sensing and nondestructive evaluation. He received his M.S. in Biomedical Engineering and Electrical Engineering from Iowa State University in 1995 and the B.S. degree in Electronics and Communications Engineering from Istanbul Technical University in 1993. Dr. Polikar teaches upper level undergraduate and graduate courses in wavelet theory, signal processing, machine learning and pattern recognition, bioinformatics, neural networks and biomedical systems and devices. He is a senior member of IEEE, and member of ASEE, Tau Beta Pi and Eta Kappa Nu. He is also an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems
Executive Summary / Highlights of Academic Resume
Funded Research: Fundamental / theoretical research actively supported by Adaptive Intelligence Systems program within NSF, including a CAREER award on "Ensemble Systems for Incremental Learning". Large scale applied research supported by government agencies as well as industrial partners.
Publication Record Total of 143 all-peer reviewed publications: 31 in journals; 6 in book / encyclopedia chapters, 18 in edited volumes; 90 (also peer reviewed and published) conference proceedings.
Citation Record: Over 2950 total citations, H-index of 22. The highest H-index and the highest number of citations among all faculty at Rowan's College of Engineering.
Student Involvement: 43 students appearing 110+ times (60+ graduate, 50+ undergraduate) as authors or co-authors in 70+ papers since 2002, with five students receiving best paper awards.
Professional Activities: Associate editor of IEEE Transactions on Neural Networks and Learning Systems; chair/co-chair/program committee member in various conference organizations; chair and organizer for several special sessions and tutorials; regularly invited to join NSF review panels; reviewer for numerous journals.
Teaching: Eight new courses developed and taught; consistently high student evaluations (over 4.0/5.0) despite (student perceived) difficulty, high expectations, workload and challenging nature of the courses.
Service: Chair of Electrical and Computer Engineering program, Steering committee chair for establishing a new Biomedical Sciences and Engineering program at Rowan (including Rowan's first PhD program), ECE graduate coordinator, member of graduate executive council, member of senate and various senate committees.
Office: 214 Rowan Hall
For a complete list, please see
For a list of Dr. Polikar's recent and active grants, please see
- Dyer K., Capo R., Polikar R., "COMPOSE: A Semi-Supervised Learning Framework for Initially Labeled Non-Stationary Streaming Data" IEEE Transactions on Neural Networks and Learning Systems, Special issue on Learning in Nonstationary and Dynamic Environments ? accepted (2014).
- Polikar R., "Ensemble Learning," in Ensemble Machine Learning: Methods and Applications, Chapter 1, Cha Zhang and Yunqian Ma, editors, Springer, 2012.
- G. Ditzler and R. Polikar, "Incremental Learning of Concept Drift from Streaming Imbalanced Data," IEEE Transactions on Knowledge and Data Engineering, accepted.
- K. Pourrezaei, Z. Barati, P. A. Shewokis, M. Izzetoglu, R. Polikar, G. Mychaskiw, "Hemodynamic response to repeated noxious cold pressor tests measured by functional near infrared spectroscopy on forehead," Annals of Biomedical Engineering, accepted.
- Capo R., Dyer K., Polikar R., "Active learning in nonstationary environments," Int. Joint Conf. on Neural Networks (IJCNN 2013), Dallas, TX, August 2013.
- Ditzler G., Rosen G., Polikar R., "Incremental Learning of New Classes from Unbalanced Data," Int. Joint Conf. on Neural Networks (IJCNN 2013), Dallas, TX, August 2013 ? accepted.
- Davis S., Frankle M., Ramachandran R.P., Dahm K., Polikar R., A freshman level module in biometric systems," IEEE Int. Symposium on Circuits and Systems (ISCAS 2013), Beijing, May 2013.
- Ditzler G., Rosen G., Polikar R., "Discounted Expert Weighting for Concept Drift," IEEE Symposium Series on Computational Intelligence ? Computational Intelligence in Dynamic and Uncertain Environments (SSCI / CIDUE 2013), Singapore, April 2013.
- Ditzler G., Rosen G., Polikar R., "Information theoretic feature selection for high dimensional meta-genomic data," IEEE Int. Workshop on Genomic Signal Processing and Statistics (GENSIPS 2012), pp. 143-146, Washington, D.C., December 2012.
- Dyer K., Polikar R., "Semi-Supervised Learning in Initially Labeled Non-Stationary Environments with Gradual Drift," World Congress in Computational Intelligence - Int. Joint Conf. on Neural Networks (IJCNN 2012), Brisbane, Australia, June 2012.
- Ditzler G., Rosen G., Polikar R., "Transductive Learning Algorithms for Nonstationary Environments," Int. Joint Conf. on Neural Networks (IJCNN 2012), Brisbane, Australia, June 2012.
- T.R. Hoens, R. Polikar, N. Chawla, "Learning from streaming data with concept drift and imbalance: an overview," Progress in Artificial Intelligence, vol. 1, no. 1, pp. 89-101, 2012.
- Ditzler G., Rosen G., Polikar R., "Forensic identification with environmental samples," IEEE International Conference on Acoustic Speech and Signal Processing (ICASSP 2012), Kyoto, Japan, March 2012 - accepted.
- Ramachandran R., Shetty S., Dahm K., Polikar R., "Open-Ended Design and Performance Evaluation of a Biometric Speaker Identification System," IEEE International Symposium on Circuits & Systems (ISCAS 2012), Seoul, Korea, May 2012.
- Hoens T., Polikar R., Chawla N. "Heuristic Updatable Weighted Random Subspaces for Nonstationary Environments" IEEE Int. Conference on Data Mining (ICDM 2011), pp.241-250, Vancouver, BC, 2011.
- Elwell R. and Polikar R., "Incremental Learning of Concept Drift in Nonstationary Environments" IEEE Transactions on Neural Networks, vol. 22, no. 10, pp. 1517-1531, October 2011.
- Garbarine E., DePasquale J., Gadia V., Polikar R., and Rosen G., "Information-theoretic approaches to SVM feature selection for metagenome read classification," Computational Biology and Chemistry, vol. 35, no. 3, pp. 199-209, doi:10.1016/j.compbiolchem.2011.04.007, 2011.
- Staudinger T. and Polikar R., "Analysis of Complexity Based EEG Features for the Diagnosis of Alzheimer's Disease" IEEE Eng. In Medicine & Biology (EMBC 2011) Boston ? accepted 2011.
- Essinger S., Polikar R., Rosen G., "Ordering Samples along Environmental Gradients using Particle Swarm Optimization" IEEE Eng. In Medicine & Biology (EMBC 2011) Boston ? accepted 2011.
- Ditzler G., Polikar R., "Semi-supervised Learning in Nonstationary Environments," Int. Joint Conf. on Neural Networks (IJCNN 2011), San Jose, CA, - accepted, August 2011.
- Ditzler G., Polikar R., "'Hellinger Distance Based Drift Detection for Nonstationary Environments," IEEE Symposium Series on Computational Intelligence (SSCI 2011), Paris, France, April 2011.
- Rosen G., Caseiro D., Polikar R., Sokhansanj, and Essinger S., "Discovering the Unknown: Improving Detection of Novel Species and Genera from Short Reads," Journal of Biomedicine and Biotechnology, vol. 2011, Article ID: 495849, doi:10.1155/2011/495849, 2011.
- Polikar R., DePasquale J., Syed Mohammed H., Brown G., Kuncheva L.I., " Learn++.MF: A random subspace approach for the missing feature problem," Pattern Recognition, vol. 43, no. 11, pp. 3817-3832, 2010.
- Polikar R., Tilley C., Hillis B., Clark C.M., "Multimodal EEG, MRI and PET data fusion for Alzheimer's disease diagnosis," IEEE Engineering in Medicine and Biology Conference (EMBC 2010) , Buenos Aires, Argentina, September 2010.
- Ditzler G., Chawla N., Polikar R. "An incremental learning algorithm for nonstationary environments and class imbalance," Int. Conf. on Pattern Recognition (ICPR 2010), pp. 2997-3000, Istanbul, Turkey, August 2010.
- Ditzler G. and Polikar R., "An incremental learning framework for concept drift and class imbalance," Int. Joint Conf. on Neural Networks (IJCNN 2010), pp. 736-743 , Barcelona, Spain, July 2010.
- Essinger S., Polikar R., Rosen G., "Neural network-based taxonomic classification for metagenomics," Int. Joint Conf. on Neural Networks (IJCNN 2010), pp. 2962 - 2968, Barcelona, Spain, July 2010.
- Ethridge J., Ditzler G., Polikar R., " Optimal nu-SVM parameter estimation using multi objective evolutionary algorithms," Int. Joint Conf. on Neural Networks (IJCNN 2010), pp. 3570-3577 , Barcelona, Spain, July 2010.
- Rosen G., Sokhansanj B., Polikar R., Bruns, M.A., Russell J., Garbarine E., Essinger S., and Yok, N., "Signal processing for metagenomics: extracting information from the soup," Current Genomics, vol. 10, no. 7, pp. 493-510, 2009.
- Merzagora A.C., Butti M., Polikar R., Izzetoglu M., Bunce S., Cerutti S., Bianchi A.M., Onaral B., "Model comparison for automatic characterization and classification of average ERPs using visual oddball paradigm," Clinical Neurophysiology, vol.120, no. 2, pp. 264-274, 2009.
- Polikar, R., "Ensemble learning," Scholarpedia, vol. 4, no. 1, pp. 2776, 2009.
- Muhlbaier M., Topalis A., Polikar R., "Learn++.NC: Combining Ensemble of Classifiers Combined with Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes," IEEE Transactions on Neural Networks, vol. 20, no. 1, pp. 152 ? 168, 2009.
- Rosen G., Garbarine E., Caseiro D., Polikar R. and Sokhansanj B., "Metagenome fragment classification using N-mer frequency profiles," Advances in Bioinformatics, vol. 2008, pp.1-12, 2008.
- Cevikalp H. and Polikar R., "Local classifier weighting by quadratic programming," IEEE Transactions on Neural Networks, vol. 19, no. 10, pp. 1832 ? 1838, 2008.
- Polikar R., Topalis A., Green D., Kounios J., Clark C.M., Ensemble based data fusion for early diagnosis of Alzheimer's disease, Information Fusion, vol. 9, no. 1, pp. 83-95, 2008.
- Polikar R., "Bootstrap inspired techniques in computational intelligence: ensemble of classifiers, incremental learning, data fusion and missing features, IEEE Signal Processing Magazine, v. 24, no. 4, pp. 59-72, 2007.
- Parikh D. and Polikar R., "An Ensemble based incremental learning approach to data fusion, IEEE Transactions on Systems, Man and Cybernetics, vol. 37, no. 2, pp. 437-450, 2007.
- Polikar R., Topalis A., Green D., Kounios J., Clark C.M., Comparative multiresolution analysis and ensemble of classifiers approach for early diagnosis of Alzheimer's disease, Computers in Biology and Medicine vol. 37, no. 4, pp. 542-558, 2007.
- Polikar R., "Ensemble based systems in decision making," IEEE Circuits and Systems Magazine, vol. 6, no.3, pp. 21-45, 2006.