Yufei Huang received his Ph.D. degree in electrical engineering from the State University of New York at Stony Brook in 2001. Since 2002, he has been with the Department of Electrical and Computer Engineering at the University of Texas at San Antonio (UTSA), where he is now Professor. He is also an adjunct professor at the Dept. of Epidemiology and Biostatistics at the University of Texas Health Science Center at San Antonio. He has been a visiting professor at the Center of Bioinformatics, Harvard Center for Neurodegeneration & Repair.
Dr. Huang’s expertise is in the areas of computational biology, computational neuroergonomics, brain computer interface, statistical modeling, and Bayesian methods. He is currently focusing on uncovering the functions of mRNA methylation using high throughput sequencing technologies, developing passive EEG-based brain-machine-interaction, and deep learning algorithms for EEG data analysis. He was a recipient of US National Science Foundation (NSF) Early CAREER Award in 2005, Best Paper Award of 2006 Artificial Neural Networks in Engineering Conference, and 2007 Best Paper Award of IEEE Signal Processing Magazine. His research has been supported by NSF, National Institute of Health, Air Force Office of Scientific Research, Army Research Lab, Department of Defense, and Qatar National Research Fund. He has been an organizer of workshops and several special sessions including the IEEE Workshop on Genomic Signal Processing and Statistics, and Workshop on Systems Biology and Medicine, and IEEE Bioinformatics and Biomedicine Conference. He is an Associate Editor of IEEE Transactions on Signal Processing, BMC Systems Biology, EURASIP Journal on Bioinformatics and Computational Biology, and International Journal Machine Leaning and Cybernetics.
To prospective students:
Research assistant positions are available for highly motivated students, who are committed to pursue Ph.D. degrees in the area of statistical signal processing for system biology. Students must have strong mathematics, statistics, orsignal processing background. Preference will be given to those with MS degree