The IEEE Brain Initiative eNewsletter is a quarterly online publication launched in January 2017. It features practical and timely information and forward-looking commentary on neurotechnologies and neuroengineering. eNewsletter articles can describe recent breakthroughs in research, primers on methods of interests, or report recent events such as conferences or workshops. You can contact the eNewsletter editor with any questions concerning the topic or content of your article.
eNewsletter articles are practical rather than highly technical in nature – not journal papers – to keep the community up to date on neurotechnology-related issues and developments around the world. The articles should be approximately 800-1200 words in length and can be authored by a mix of IEEE and non-IEEE members. We encourage authors to include 1-2 images or drawings to help illustrate your article, and a maximum of 20 references. Citations should be referenced as number and formatted as follows:  Doe, J. et al. Article title. Journal Name. 2012;32(43):14915-20. DOI: xx.xxx/yyy-zz-zz
Please make sure your opening paragraphs communicate your main message, and convey why that message is relevant or important for readers to appreciate right now. Potential elements of newsletter articles include the following:
- Statement of the challenge/opportunity: gaps, opportunities, and drivers
- Technological innovation/advances with some good simple illustrations. What is the state-of-the-art? What are emerging or pivotal? Why is this novel and important?
- Why is this important and high potential?
- Process/how to get it deployed/implemented
Please submit your manuscript to the eNewsletter managing editor. Submissions should include the author’s bio – approx. 100 words and including details of your IEEE affiliation – and headshot photo. Please also ensure to provide high-resolution files for your images.
Submitted articles are edited and reviewed for acceptance to a specific issue. According to IEEE policies, all articles will be validated with CrossCheck, IEEE’s plagiarism checker. Submissions found to be plagiarized according to CrossCheck guidelines will not be published.
Final articles, revised if necessary to accommodate reviewers’ comments, are required 4 weeks prior to the planned issue date. The Managing Editor will provide the specific deadline.
Yiwen Wang received B.S. and M.S. degrees from University of Science and Technology of China (USTC), Hefei, Anhui, China in 2001 and 2004 respectively. She received Ph.D. degree from University of Florida, Gainesville, FL, USA in 2008. She then joined the Department of Electronics and Computer Engineering as a Research Associate at the Hong Kong University of Science and Technology, Kowloon, Hong Kong. In 2010, she joined the faculty as an Associate Professor at Zhejiang University, Hangzhou, China. In 2017, she joined the faculty as an Assistant Professor at the Department of Electronic and Computer Engineering, Department of Chemical and Biological Engineering, the Hong Kong University of Science and Technology. Her research interests are in neural decoding of brain-machine interfaces, adaptive signal processing, computational neuroscience, neuromorphic engineering. She serves as the chair in the IEEE Brain Publications Subcommittee, IEEE BRAIN, vice chair in the IEEE EMBS Neural Engineering Tech Committee, board member in Brain Computer Interfaces Society, the editorial board of the Journal of Neural Engineering, the editorial board of Frontiers in Human Neuroscience (Brain-Computer Interfaces) and is an associate editor of the IEEE Transactions on Neural Systems and Rehabilitation Engineering. She holds one US patent and has authored more than 100 peer-reviewed publications.
Jun Wang (S’16) received the B.S. degree in instrumentation from Jiangsu University, Jiangsu, China, and the M.S. degree in precision instruments from Tsinghua University, Beijing, China, in 2011 and 2014, respectively. He then got his Ph.D. degree with best thesis award in bioengineering of UC San Diego in 2019. He is currently a postdoctoral fellow at Harvard University. His current research interests include neuromorphic chip design, neural interfaces, biomedical instrumentation, and bioMEMS.
Sung-Phil Kim received the B.S. degree from the Department of Nuclear Engineering at Seoul National University and the M.S. and Ph.D. degrees from the Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA. Afterward, he conducted postdoctoral research at Brown University, Providence, RI, USA. He is an Associate Professor working in the Department of Biomedical Engineering at the Ulsan National Institute of Science and Technology (UNIST), Ulsan, Korea. His research interests include brain–computer interfaces, computational neuroscience, and statistical signal processing.
Ning Jiang, PhD, IEEE Senior Member, received the B.S. degree in electrical engineering from Xi’an Jiaotong University, Xi’an, China, in 1998, and the M.Sc. and Ph.D. degrees in Engineering from the University of New Brunswick, Canada, in 2004 and 2009, respectively. He was a Research Assistant Professor with Aalborg University, Denmark from 2009 to 2010, a Marie Curie Fellow with Otto Bock Healthcare GmbH, Germany, from 2010 to 2012, and a Research Scientist with University Medical Center Göttingen, Germany, from 2012 to 2015. Since 2015, he has been an Assistant Professor with the Department of Systems Design Engineering, University of Waterloo, Canada, where he was promoted to Tenured Associate Professor in July 2020. His research interests include signal processing of electromyography and electroencephalogram, and their applications in neurorehabilitation. He has authored and co-authored more than 170 journal papers and conference papers/abstracts. He is currently an Associate Editor of the IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Journal of Biomedical and Health Informatics, the Brain-Computer Interface, and Frontiers in Neuroscience.
Dongrui Wu received a B.E in Automatic Control from the University of Science and Technology of China, Hefei, China, in 2003, an M.Eng in Electrical and Computer Engineering from the National University of Singapore in 2006, and a PhD in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 2009. He was a Lead Engineer of GE Global Research, Niskayuna, NY. He is now Professor and Deputy Director of the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.
Prof. Wu’s research interests include affective computing, brain-computer interface, computational intelligence, and machine learning. He has more than 170 publications (8,100+ Google Scholar citations; h=45), including a book “Perceptual Computing” (Wiley-IEEE Press, 2010), and 11 patents. He received the IEEE Computational Intelligence Society (CIS) Outstanding PhD Dissertation Award in 2012, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award in 2014, the North American Fuzzy Information Processing Society (NAFIPS) Early Career Award in 2014, the IEEE Systems, Man and Cybernetics (SMC) Society Early Career Award in 2017, the IEEE SMC Society Best Associate Editor Award in 2018, the USERN Prize in Formal Sciences in 2020, the IEEE International Conference on Mechatronics and Automation Best Paper Award in 2020, and the IEEE Transactions on Neural Systems and Rehabilitation Engineering Best Paper Award in 2021. He was a selected participant of the Heidelberg Laureate Forum in 2013, the US National Academies Keck Futures Initiative (NAKFI) in 2015, and the US National Academy of Engineering German-American Frontiers of Engineering (GAFOE) in 2015. His team won the First Prize of the China Brain-Computer Interface Competition in three successive years (2019-2021).
Prof. Wu is Editor-in-Chief of the IEEE SMC Society eNewsLetter, and an Associate Editor of the IEEE Transactions on Fuzzy Systems (2011-2018; 2020-), the IEEE Transactions on Human-Machine Systems (since 2014), the IEEE Computational Intelligence Magazine (since 2017), and the IEEE Transactions on Neural Systems and Rehabilitation Engineering (since 2019). He is a Senior Member of the IEEE, and Associate Vice-President for Human-Machine Systems of the IEEE SMC Society.
Yuxiao Yang is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) and the Disability, Aging and Technology (DAT) Faculty Cluster at the University of Central Florida (UCF). His research interests include neural engineering, stochastic signal processing, control theory, and machine learning. His research has centered on designing closed loop BMIs for neural decoding and control, aiming to provide new therapies for neurological and neuropsychiatric disorders. Prior to joining UCF, he was a postdoc at the University of Southern California (USC). He received the Ph.D. and M.S. degree in Electrical and Computer Engineering from USC in 2019 and 2018, respectively. He received the B.S. degree from Tsinghua University in 2013, majoring in Electrical and Electronics Engineering. He has received various awards including the International Brain-Computer Interface (BCI) Award (2019), the IEEE EMBC best student paper award (2015), and the McMullen fellowship from Cornell University (2013).