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Vicente Alarcon-AquinoView profile

Professor

• Cybersecurity
• Network Monitoring
• Anomaly Detection
• +7 more

Dr. Vicente Alarcon-Aquino is a Professor in the Department of Computing, Electronics, and Mechatronics at Universidad de las Americas Puebla (UDLAP), Mexico. He received his Ph.D. and D.I.C. degrees in Electrical and Electronic Engineering from Imperial College London in 2003. He previously served as department head from October 2012 to June 2018 and spent a research stay at King's College London in 2017. Dr. Alarcon-Aquino is a Senior Member of IEEE, a Level I member of the Mexican National System of Researchers (SNI), and a Fellow of the Mexican Academy of Sciences. His educational background includes: Ph.D. and D.I.C. in Electrical and Electronic Engineering, Imperial College London, UK (2003) Dr. Alarcon-Aquino's research focuses on cybersecurity, network monitoring, anomaly detection, wavelet analysis, and machine learning. His work spans theoretical foundations to practical applications in network security, with significant contributions to intrusion detection systems, cryptographic techniques, and machine learning approaches for security applications. He has developed innovative methods combining wavelet transforms with neural networks for various security and signal processing applications. His scholarly contributions include over 180 research articles in refereed journals and conference proceedings, a book on MPLS networks, and numerous citations. As an editor, he serves as Associate Editor for IEEE Access Journal and as Academic & Section Editor for PeerJ Computer Science, focusing on Security & Privacy. Notable professional recognitions include: Senior Member of IEEE Mexican National System of Researchers (SNI Level I) Member of the Mexican Academy of Sciences Dr. Alarcon-Aquino has supervised over 70 theses, including 8 Ph.D. dissertations, 15 Master's theses, and more than 37 Bachelor's theses. His supervision spans topics including network intrusion detection, information security, encryption algorithms, wavelet-based signal processing, neural networks, EEG signal processing, and biometric cryptosystems. He has hosted international research students from institutions including the Polytechnic University of Madrid and Kiel University of Applied Sciences. His research group at UDLAP focuses on developing advanced security solutions for modern network environments, with particular emphasis on applying machine learning techniques to cybersecurity challenges. Current projects include blockchain-based security solutions, federated learning approaches for intrusion detection, and advanced anomaly detection systems for IoT environments.

• Artificial Intelligence
• Machine Learning
• Biomedical Signal Processing
• +3 more

Dr. S M Shafiul Hasan serves as Assistant Professor of Computer Science in the Department of Informatics and Mathematics at Mercer University's College of Professional Advancement. His academic journey includes a PhD and MSc in Electrical and Computer Engineering from Florida International University, complemented by MSc and BSc degrees from Bangladesh University of Engineering and Technology. Prior to Mercer, he conducted postdoctoral research at Emory University developing ML models for stroke recovery diagnostics. His research bridges artificial intelligence and healthcare through: Biomedical signal processing for stroke and Parkinson's diagnostics Neurovascular coupling analysis using transfer entropy EEG-based movement intention prediction systems EHR data mining for atrial fibrillation and dementia risk With 15 peer-reviewed publications since 2016 spanning IEEE Transactions, Stroke, and Frontiers in Neurology, his work demonstrates consistent translational impact. Recent publications (2023-2025) focus on contralateral neurovascular coupling in stroke patients and real-time gait intention prediction, reflecting an evolving research trajectory toward clinical implementation. As an active IEEE member, he contributes to professional discourse while mentoring students through research-intensive projects. His Emory postdoctoral experience indicates strong NIH-relevant grant activity, though specific awards aren't publicly listed. Current work integrates computer vision with prosthetic control systems, showing expansion into assistive robotics.

Miriam PrimbsView profile

Professor

• Applied Mathematics
• Numerical Methods
• Mathematical Simulation
• +4 more

Professor Miriam Primbs is a faculty member at Hochschule Ruhr West (HRW) in the Institute of Natural Sciences, where she teaches Mathematics and Simulation. She has been a professor at HRW since 2011 and coordinates the HRW research focus MARTA since 2022. Professor Primbs studied Mathematics and Physics (Diplom and 1. Staatsexamen) and earned her PhD in Mathematics at the University of Duisburg-Essen. Her career includes a research stay at IMATI CNR in Italy, teaching on the school ship Thor Heyerdahl, and working in Research and Development at Siemens Energy Mülheim before joining HRW. This blend of academic and industry experience informs her teaching and research approach. Her research focuses on applying mathematical and numerical methods to technical problems across engineering disciplines, from mechanics to electrical engineering. As coordinator of the MARTA research focus, she leads various projects including those funded by BMBF and collaborations with industry partners like Siemens Energy. Her scholarly work spans wavelet analysis, numerical methods, signal processing, and power systems analysis. Professor Primbs teaches Engineering Mathematics I and II, Mathematics for E-Commerce, MATLAB, Scientific Simulation, and LaTeX Basics. She employs a flipped classroom approach for foundational courses, providing students with tailored materials and prompt feedback through weekly exercises. In higher semesters, she emphasizes project-based learning and specialized topics. Currently supervising doctoral student Martin Wachs in cooperation with University of Duisburg-Essen Member of the Senate Committee for Research and Transfer at HRW Encourages industry collaboration for practical research applications Professor Primbs maintains strong connections between academic research and industrial applications, leveraging her Siemens Energy experience to bridge theory and practice in mathematical engineering.

• Harmonic Analysis
• Fourier Analysis
• Representation Theory of Lie Groups
• +5 more

Jordy Timo van Velthoven is a researcher in the Department of Mathematics at the University of Vienna's Faculty of Mathematics. His office is located at Oskar-Morgenstern-Platz 1, Room 05.135 in Vienna, Austria. He teaches advanced seminars in Harmonic Analysis (course codes 510003 SE, 510004 SE, 510005 SE) for the 2024W, 2025S, and 2025W academic terms. His research focuses on Harmonic Analysis, Fourier Analysis, and Representation Theory of Lie Groups , with specific expertise in asymptotics of matrix coefficients, density conditions for coherent state subsystems, localisation of frames and Riesz bases, and multiparameter function spaces. His work bridges pure mathematics with applications in signal processing and functional analysis. Analysis of his recent publications reveals a strong emphasis on frame theory, coorbit spaces, and function space classifications across homogeneous groups. His collaborations span international institutions, with frequent work on density conditions, wavelet analysis, and Lie group representations. Key recurring themes include anisotropic spaces, discrete geometry in harmonic analysis, and operator theory applications. His scientific contributions have been published in top-tier mathematics journals including Annals of Mathematics , Journal of Functional Analysis , and Proceedings of the American Mathematical Society , though no specific awards or fellowships are documented in the provided materials. Van Velthoven actively mentors graduate students through his Harmonic Analysis seminars and supervises research projects. His work involves significant collaboration with prominent mathematicians like Führ, Voigtlaender, and Romero. Current research directions include extending density theorems to non-unimodular groups and developing molecular decompositions for quasi-Banach coorbit spaces.

Joseph MadsenView profile

Professor

• Epilepsy
• Neurosurgery
• Brain Mapping
• +6 more

Joseph Madsen is a Professor of Neurosurgery at Harvard Medical School and a neurosurgeon at Boston Children's Hospital. His career uniquely bridges clinical neurosurgery with fundamental neuroscience research, focusing on improving surgical treatments for epilepsy through advanced brain mapping techniques and physiological understanding. Dr. Madsen's educational background includes: Undergraduate studies at University of Utah (1976) Medical degree from Harvard-MIT Program in Health, Science, and Technology (1981) Surgical internship at Beth Israel Deaconess Medical Center (1982) Neurosurgery residency at Massachusetts General Hospital (1989) Fellowship at Beth Israel Deaconess Medical Center/Massachusetts General Hospital (1983) His research program integrates clinical data with basic neuroscience to develop safer, more effective epilepsy surgeries. A key focus is studying human electrocorticograms recorded during behavioral cortical tasks to answer fundamental questions about cortical physiology while simultaneously improving the ability to map cortical function for surgical planning. His laboratory combines digital signal processing, wavelet analysis, and cognitive science approaches to investigate brain function and epilepsy mechanisms. He also conducts significant research on vagal nerve stimulation for epilepsy treatment, examining both efficacy and safety profiles. Analysis of Dr. Madsen's recent publications reveals an increasingly sophisticated integration of computational approaches with neurophysiological data. His work on machine learning applied to intracranial EEG has advanced the identification of biomarkers for surgical planning and outcome prediction. There's also growing emphasis on genetic aspects of epilepsy and the detailed physiological mechanisms underlying seizure generation and propagation. Dr. Madsen has provided clinical and research leadership through numerous publications and patient care innovations, though specific awards are not highlighted in the available information. As a mentor, Dr. Madsen has likely guided numerous neurosurgery residents, fellows, and graduate students through his extensive career, contributing to the training of specialists in epilepsy surgery and functional neurosurgery. His research has been supported by various grants that have enabled the development of advanced techniques for brain mapping and epilepsy treatment. Dr. Madsen leads a research laboratory that uniquely combines clinical neurosurgery with fundamental neuroscience investigation. His team utilizes advanced technologies including digital signal processing, wavelet analysis, and cutting-edge cognitive science methods to study cortical physiology in humans. The laboratory environment facilitates the direct translation of clinical observations into basic research questions and vice versa, creating a powerful feedback loop for advancing epilepsy surgery techniques.