Francisco Sepulveda is a full Professor of Neural Engineering and Intelligent Systems. He was the coordinator for 10 years and a co-Founder of the Essex BCI group. He has been involved in efforts that have secured c£2.5million in external funds from the UK’s Research Councils, HEFCE, and MTHR, including receiving an EPSRC First Grant for early career researchers. Since 2004, the Essex BCI-NE group has become the largest in the UK and has attracted more funding than all other UK-based BCI groups combined. Prior to joining the University in 2002, Dr. Sepulveda was an Assistant Professor of Biomedical Engineering at Aalborg University, Denmark, where he was involved in projects on the use of implanted cuff electrodes for the extraction of afferent signals related to joint angles and foot pressure, and in pattern recognition applied to implanted EMG for control of hand prostheses. He received his PhD Summa Cum Laude in Biomedical Engineering from the University of Campinas, Brazil (with a fellowship at the Bioengineering Unit, University of Strathclyde, UK) in 1996, an MSc (with Distinction) in Bioengineering from Clemson University (USA) in 1990, and a BSc in Nuclear Engineering from the University of California, Santa Barbara, in 1988, having received the ‘The Outstanding Student’ award at graduation. His PhD was on the development of an artificial neural controller for FES-generated gait in individuals with spinal cord injury, which gave him the best paper award at the World Congress on Medical Physics and Biomedical Engineering in 1994. In the UK, he has been very active in public dissemination of science, with many appearances in the media and public venue. Dr. Sepulveda has more than 160 peer reviewed publications (>120 in neural engineering), is a member of the Peer Review College of the EPSRC and of the editorial board of Frontiers in Human Neuroscience.

Dr Luca Citi's primary research focus is on the application of machine learning and statistics to neural signal decoding. He has a laurea degree (corresponding to a MSc) in Electronic Engineering with major in Biomedical Engineering from Università di Firenze (Italy). He joined the Essex BCI lab for the first time in 2004 as a visiting student. Under the supervision of Prof Riccardo Poli, he worked on his master's thesis about an ERP-based brain-computer interface mouse. In 2009, he obtained his PhD under the supervision of Prof Silvestro Micera and Dr Oliver Tonet at IMT Lucca and Scuola Superiore Sant'Anna (Pisa, Italy). The topic of the PhD was the development of an algorithm to translate the neural activity recorded from the nerve residuum of an amputee into control commands for a robotic hand prosthesis. Afterwards, he worked for three years as post-doctoral researcher in the “Neuroscience Statistics” laboratory led by Prof Emery Brown at MGH / Harvard Medical School and MIT (Cambridge, USA), where he accumulated a wealth of experience on the point-process analysis of biological signals, including neural spike trains. He worked with Dr Riccardo Barbieri on the study of heart-rate variability and computational physiology. They entered the “PhysioNet 2012 challenge”, a machine learning competition about the prediction of in-hospital mortality, and their algorithm came first and second in the two events organized. Since 2012, Dr Citi is a lecturer in computational intelligence at the university of Essex and a member of the Essex BCI lab. In 2014, Dr Citi was selected to participate to the 2nd Heidelberg laureate forum where young researchers met Abel, Fields and Turing laureates for a week of scientific exchange.

John Q. Gan received the BSc degree in electronic engineering from Northwestern Polytechnic University, China, in 1982 and the MEng degree in automatic control and the PhD degree in biomedical electronics from Southeast University, China, in 1985 and 1991, respectively. He is a professor in the School of Computer Science and Electronic Engineering of the University of Essex. His research interests include neurofuzzy computation, machine learning, machine intelligence, brain-computer interface, robotics and intelligent systems, pattern recognition, signal processing, data fusion, computer vision and multimodal human-machine interaction. He has coauthored a book and published more than 200 research papers. He is an associate editor for the IEEE Transactions on Systems, Man, and Cybernetics—Part B and serves on the editorial board of other journals. He is a senior member of the IEEE.

My research interests include attention, multisensory perception, memory, brain-computer interfaces and assisted living. I obtained my first degree in Cognitive Psychology from University of Padova (Italy), where I started doing neuropsychology research based on single-case studies (aphasia and number processing). I then continued my studies at the University of Birmingham (UK), first as an Erasmus student, then with a master degree in Cognitive Science and a PhD in Cognitive Psychology. During that time (1996-2001) I investigated feature binding in visual and cross-modal perception in normal and brain-damaged population. Since 2002 I work at the University of Essex as a research assistant. Here I am currently investigating mechanisms of retrieval and forgetting in the Psychology Department and I am also a member of the BCI group (since 2004). With the BCI group I have contributed at the development of P300-based BCIs (BCI speller and mouse) and am now engaged at exploring collaborative BCI based on EEG and other physiological measures. I am also involved in a study investigating the possibility of reducing Parkinson’s disease tremor through brainwave entrainment.

Ian Daly received the M.Eng. degree in Computer science and the Ph.D. degree in Cybernetics from the University of Reading, Reading, U.K. Between May 2011 – 2013 he was a post-doctoral researcher in the Laboratory of Brain-Computer Interfaces, Graz University of Technology, Graz, Austria, where he researched Brain-computer interfaces for individuals with stroke and cerebral palsy. He was then a post-doctoral researcher in the University of Reading until October 2016 when he joined the University of Essex (and the BCI-NE lab) as a Lecturer. His research interests focus on BCIs, nonlinear dynamics, machine learning, signal processing, bio-signal analysis, meta-heuristic search techniques, and connectivity analysis in the EEG and fMRI. He is also interested in the neurophysiological correlates of motor control, emotion, and stimuli perception and how they differ between healthy individuals and individuals with neurological and physiological impairments.

Ana obtained her BEng + MEng in Telecommunication Engineering from the Universidad de Valladolid (Spain) and her MSc in Biomedical Engineering from the University of Surrey (awarded Distinction). She joined the BCI-NE lab in 2012 to do her PhD in the topic of collaborative BCIs under the supervision of Prof. Riccardo Poli. As part of her PhD she visited NASA JPL as a fellow researcher. She worked as a senior research officer in the H2020 DeTOP European project before joining the Institute for Analytics and Data Science as an Artificial Intelligence Industry Fellow. Her research interests are in the area of biomedical signal processing, and uses EEG to study memory and emotion in response to complex visual and audio-visual stimuli.

Sebastian Halder received his MSc degree in Bioinformatics from the University of Tübingen, Germany in 2006 and his PhD in Computer Science from the same institution in 2011. From 2002 to 2006 as a student and from 2006 to 2012 he worked in the group of Prof. Niels Birbaumer in particular on brain-computer interfaces (BCIs) for communication with persons severe motor impairments. During this time he worked on the online processing of electroencephalography data, the design of new communication paradigms and the analysis of electrocorticography and functional magnetic resonance data with a focus on clinical applications. Since then he has held positions at the University of Würzburg in Germany, the National Rehabilitation Center for Persons with Disabilities in Japan and the University of Oslo in Norway. His research interests include auditory BCIs for communication, the neural mechanisms of learning with BCIs, the neural signature of pain and disorders of consciousness. He has authored or co-authored over 40 publications in peer reviewed journals that have been cited over 4500 times (according to Google Scholar). He joined the BCI-NE lab in January 2019.

Serafeim Perdikis was born in Thessaloniki, Greece in 1984. He received the M.E. degree in Electrical and Computer Engineering from the Aristotle University of Thessaloniki (AUTH) in 2007 and the Ph.D. degree in brain-computer interaction (BCI) from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 2014, where he subsequently served as a post-doctoral researcher until May 2015. In June 2015 he joined the Wyss Center for Bio- and Neuro-engineering at Campus Biotech, Geneva, Switzerland working on BCI-based stroke rehabilitation. As of February 2019 he is serving as a Lecturer of the Neural Engineering and BCI Laboratory at the University of Essex, School of Computer Science and Electronic Engineering, UK. His main areas of research interest include theoretical and applied machine learning, bio-signal processing, mutual learning and co-adaptation in BCI, as well as translational and rehabilitation applications of BCI.

Delaram completed her PhD in Biomedical Signal Processing at the University of Surrey, UK, in 2011. Her research was focused on processing of brain signals using electroencephalography. She has been involved in development of algorithms for motion analysis using body-worn sensors at Imperial College London and unobtrusive heart rate monitoring from peripheral sites at University of Manchester. She was also a member of computational health informatics lab at University of Oxford, and worked on wearable sensors to contribute to the design of a wearable multivariate patient monitoring system for use at scale in clinical practice. Her research interests include time-series analysis, adaptive signal processing and machine learning for bio-signal processing.

Junhua Li received his PhD from the Department of Computer Science and Engineering at the Shanghai Jiao Tong University, China. He currently is a lecturer in the School of Computer Science and Electronic Engineering at the University of Essex, UK, and was a senior research fellow at the National University of Singapore, Singapore. His research interests include brain-computer interfaces, neurophysiological signal processing, machine learning, computational neuroscience, and neuroimaging data analytics. Particularly, he is recently focusing on the understanding of mental diseases such as Schizophrenia and Alzheimer’s disease from the perspective of neuroimaging and the applications of passive brain-computer interfaces to mental states. He is a Senior Member of the IEEE. As of May 2019, he has published 48 peer-reviewed papers.