Dr. Antje Strauß is a Researcher at the Department of Linguistics, University of Konstanz, where she serves as Principal Investigator for a DFG-funded project on theta oscillations and prelexical abstraction since October 2018. Her work bridges speech processing, auditory cognition, and neural oscillations, with a focus on lexical and sublexical mechanisms in noisy environments. PhD in Neural Oscillatory Dynamics of Spoken Word Recognition (2011–2014, Max Planck Institute) Magistra Artium in German Philology and Philosophy (2004–2010, Albert Ludwig University) Her research explores how brain rhythms like alpha and theta oscillations support auditory selective inhibition, speech segmentation, and predictive processing. She has pioneered studies on cued speech applications for enhancing speech-in-noise perception and developed the Fharvard corpus—a phonemically-balanced resource for audiology research. Recent publications highlight her expertise in neural oscillations, auditory perception, and speech-in-noise intelligibility. Collaborative work spans institutions like CNRS, MPI CBS, and Freiburg Institute for Advanced Studies. Post-doctoral fellow at Zukunftskolleg, University of Konstanz (2016–2018) Post-doctoral fellow at CNRS, GIPSA-lab (2015–2016) She contributes to peer review for journals including Journal of Neuroscience , Cortex , and PLOS Biology , and maintains memberships in the Society for the Neurobiology of Language, European Society for Cognitive Psychology, and related organizations.
Ghyslain Gagnon is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS) in Montreal, Canada. He leads research activities within the LACIME – Communications and Microelectronic Integration Laboratory, focusing on cutting-edge developments in microelectronics, sensors, and communication systems. His work bridges theoretical research and practical applications across multiple domains including health technologies, wireless communications, and quantum engineering. Education: B.Ing. from École de technologie supérieure M.Ing. from École de technologie supérieure Ph.D. from Université de Carleton Professor Gagnon's research spans several interconnected domains with emphasis on Radiofrequency circuits and antennas, Microelectronics, Wireless communications, Sensors and monitoring systems, Machine learning applications, Health technologies, and Quantum engineering. His work demonstrates a strong commitment to translating theoretical concepts into practical solutions with real-world impact, particularly in the areas of health monitoring systems and advanced communication technologies. His recent publications reveal a clear trajectory toward increasingly interdisciplinary research, combining traditional electrical engineering with machine learning, health monitoring, and quantum technologies. The trend shows growing emphasis on practical applications in automotive safety systems, wireless communications for next-generation networks, and health monitoring technologies that leverage flexible electronics and novel sensor designs. Professor Gagnon has successfully supervised numerous graduate students through their doctoral and master's research, with recent theses focusing on smart hearing protection devices, machine learning applications, energy monitoring systems, and flexible sensor technologies. His supervision record demonstrates consistent productivity and relevance to contemporary engineering challenges. He is an active member of the LACIME research laboratory, which focuses on six key areas: Functional materials, Micro- and nanofabrication processes, Conception and design of integrated circuits, Design and fabrication of hybrid components, Photonic and electronic microsystems, and Signal processing and communication. This environment provides students with access to cutting-edge tools and fosters innovation through interdisciplinary collaboration.
Ilia Polushin is an Associate Professor at the Department of Electrical and Computer Engineering , Western University . His research focuses on Robotics, Teleoperation, Control Systems, and Biomedical Applications . Education : Ph.D. in Electrical Engineering (Carleton University), Cand. Sci. in Automatic Control (Saint-Petersburg Electrotechnical University) His work primarily addresses stability and control of teleoperation systems with communication delays, using scattering transformation techniques and projection-based force reflection algorithms . He has contributed to haptic systems, surgical robotics , and networked control applications , including drilling systems and cooperative teleoperation. Recent publications emphasize stabilization of conic systems , multi-agent synchronization , and nonlinear networked control . His research spans Robotics, Control Theory, Biomedical Engineering, and Industrial Automation . Scientific Awards : Best Conference Paper Award, IEEE International Conference on Mechatronics and Automation (2006) He has advised students and collaborated with researchers in Robotics , Control Systems , and Biomedical Applications . His laboratory focuses on teleoperation systems and haptic interfaces .
Dr. Puren Ouyang serves as an Associate Professor in the Department of Aerospace Engineering at Toronto Metropolitan University, where he holds a Professional Engineering license (PEng). His academic foundation includes a BASc from Huazhong University of Science and Technology (1985), followed by MSc and PhD degrees from the University of Saskatchewan (2002, 2005). He teaches core courses including AER 509 Control Systems, AER 520 Stress Analysis, and AE 8141 Advanced Aerospace Manufacturing. His educational credentials: PhD in Engineering, University of Saskatchewan (2005) MSc in Engineering, University of Saskatchewan (2002) BASc in Engineering, Huazhong University of Science and Technology (1985) Ouyang pioneered position domain control methodology, replacing traditional time/frequency references with position-based systems to enhance robotic precision in contour tracking. His research directly addresses industrial manufacturing challenges where 24/7 machine reliability determines product accuracy. Key focus areas include robotic control systems, mechatronics integration, hybrid system dynamics, and synchronized multi-DOF manipulation for CNC applications. His 2013-2016 publications reveal consistent innovation in position-domain robotics control, with emphasis on contour tracking algorithms, multi-axis synchronization, and adaptive learning techniques. These works bridge theoretical control frameworks with industrial manufacturing applications, frequently targeting CNC machine optimization where 80% of North American factories rely on automated systems. Key recognitions: Best Conference Paper in Integration Award at IEEE ICIA 2011 NSERC Postdoctoral Fellowship (2005-2007) As an active supervisor, Ouyang mentors graduate students in robotics and control systems through the ISRMM Laboratory. His NSERC fellowship demonstrates sustained research capability, while his industry-focused publications suggest ongoing grant activity in advanced manufacturing automation. Current supervision availability indicates active research program development. The Intelligent Systems & Robotics / Micro Manufacturing (ISRMM) Laboratory serves as his primary research hub, driving innovations in robotic precision manufacturing, micro-scale production systems, and real-time control architectures for industrial applications.
Vikaas Sohal, MD, PhD is a Professor in the Department of Psychiatry at the University of California, San Francisco (UCSF) School of Medicine and a member of the UCSF Weill Institute for Neurosciences. He directs a neuroscience laboratory investigating the brain circuits underlying fundamental aspects of cognition and emotion, with particular focus on gamma oscillations in normal cognition and schizophrenia, as well as how rhythmic brain activity encodes emotional states. Dr. Sohal is also a board-certified psychiatrist who supervises residents in the Early Psychosis (PATH) clinic. Dr. Sohal earned his A.B. and S.M. in Applied Mathematics from Harvard University in 1997, followed by an M.A.St. in Mathematics from the University of Cambridge in 1998. He completed his M.D./Ph.D. in Neuroscience at Stanford University in 2005, where he also completed his residency in adult psychiatry. During his residency, he conducted postdoctoral research with Dr. Karl Deisseroth, performing some of the first experiments using optogenetics to study information processing in brain circuits. Dr. Sohal's research has focused on neural circuit mechanisms underlying cognitive and emotional processes, with particular emphasis on gamma oscillations, prefrontal-hippocampal interactions, and the role of specific interneuron subtypes in information processing. His laboratory has made significant contributions to understanding how parvalbumin interneurons generate gamma oscillations that organize prefrontal networks to promote behavioral adaptation. His recent work has explored the circuit basis of emotional states, pain-related aversion, and neuropsychiatric disorders. His publication record shows a consistent trajectory of high-impact research, with recent publications spanning topics from psilocybin effects to thalamocortical organoids for neuropsychiatric disorder modeling. His work demonstrates a progression from fundamental circuit mechanisms to translational applications for psychiatric disorders, particularly focusing on schizophrenia and emotional processing abnormalities. Dr. Sohal has secured continuous NIH funding as Principal Investigator since 2009, including multiple R01 grants, an R56, DP2, R00, and K99 awards, demonstrating sustained research productivity and significance. His research program represents a sophisticated integration of molecular, cellular, circuit, and behavioral approaches to understand and potentially treat neuropsychiatric disorders.
Denny Yu is an Associate Professor at the Edwardson School of Industrial Engineering, Purdue University. His work bridges human factors, neuroergonomics, and healthcare safety through advanced sensor systems and AI. Primary Affiliation : Edwardson School of Industrial Engineering, Purdue University Research Themes : Surgical ergonomics, autonomous vehicle human factors, cognitive workload assessment, multimodal physiological sensing Dr. Yu's research focuses on neuroergonomics and human-robot interaction , particularly in surgical and transportation contexts. His team develops sensor-based systems for workload monitoring, including: EEG-eye tracking fusion for situation awareness Wearable exoskeletons for surgical posture support Computer vision tools for lifting task risk analysis Smart infusion pump usability frameworks AI-driven surgical coaching systems Recent publications emphasize deep learning applications in soft tissue deformation estimation and real-time adaptive systems for robotic surgery augmentation. His work spans both occupational health (veterinary surgeons, airport workers) and medical device innovation domains.
Professor Georg Gottwald is a distinguished academic in the School of Mathematics and Statistics at the University of Sydney, where he has been a faculty member since 2002, progressing from Lecturer to his current position as Professor since 2013. He also holds a Visiting Professor position at the University of Surrey in the UK since 2013. His extensive research career spans dynamical systems theory, geophysical fluid dynamics, and the intersection of machine learning with complex systems. Professor Gottwald's research focuses on dynamical systems theory as an abstract formalism for studying systems evolving in time and space. His work has significant applications across diverse fields including climate modeling, biological systems, and complex networks. He is particularly known for developing methods for model reduction of complex dynamical systems, stochastic modeling approaches, and the application of machine learning techniques to dynamical systems. His research aligns with the Faculty of Science Research Strengths in Understanding the Universe, Fundamental Laws of Nature, Complex Systems, Climate and Environmental Change, Data and Decisions, and National Security. His most recent publications demonstrate a strong trajectory toward integrating machine learning with dynamical systems theory, particularly in developing stable generative models, learning dynamical systems with random feature maps, and combining data assimilation with machine learning for forecasting. His work spans pure mathematical theory to practical applications in climate science, finance, and biological systems, showing remarkable breadth while maintaining deep mathematical rigor. Future Fellowship, 'Stochastic methods in mathematical geophysical fluid dynamics', Australian Research Council, 2010-2014 Australian Research Fellowship, 'Stochastic methods in mathematical geophysical fluid dynamics', Australian Research Council, 2010-2015 (declined) Australian Research Fellowship, 'Geometric methods in geophysical fluid dynamics', Australian Research Council, 2004-2009 Professor Gottwald has successfully supervised numerous PhD and Master's students who have gone on to academic and industry positions worldwide. His current research group includes postdocs and PhD students working on machine learning for dynamical systems, stochastic model reduction, physics-informed machine intelligence, and tensor methods for scientific machine learning. He has secured multiple ARC Discovery Project grants and has been involved in significant international collaborative research projects. He is actively involved with the Sydney Dynamics Group, which he co-founded in 2007, fostering collaboration between the University of Sydney and UNSW. Professor Gottwald maintains strong editorial commitments as Associate Editor for Geophysical and Astrophysical Fluid Dynamics, SIAM Journal of Applied Dynamical Systems, and Journal of Computational Dynamics, and serves on the Editorial Advisory Board for Chaos and the Editorial Board for Physical Review E. His professional activities demonstrate leadership in the dynamical systems community through organizing workshops, seminars, and special journal issues.
Professor Ulysses Sengupta is a leading academic and practitioner in architecture and urbanism at the Manchester School of Architecture , where he holds the Professor of Architecture and Urbanism title. He is the founding director of the [CPU]lab (Complexity Planning and Urbanism Research Laboratory) and leads the [CPU]ai master’s design atelier, which integrates data-driven design and computational thinking into architectural education. His work bridges academic research, pedagogy, and practice through Softgrid Limited , an internationally networked architecture and urban research firm. Founding director of [CPU]lab Leader of [CPU]ai atelier Director of Softgrid Limited International collaborations with institutions like the Architectural Association and University of Westminster Research Interests focus on cities as complex adaptive systems, utilizing big data, IoT, and machine learning to address urban sustainability and governance. Key themes include: Smart cities and digital urban disruption Agile governance and participatory planning Complexity-based design methodologies Global South urbanism and resource-limited settings Interdisciplinary tools for urban data analysis Eco-architecture and futureproofing urban systems Articles highlight his work on urban data analysis, mobility-as-a-service, transdisciplinary systems mapping, and the intersection of social/environmental justice in smart cities. His Google Scholar profile reflects a consistent focus on computational urbanism and sustainable transformation frameworks. Scientific Awards include shortlisting for the Colvin Prize (2025), a prestigious honor in architectural research. His projects span ESRC, H2020, and Innovate UK grants, including leadership in the DACAS network and Synchronicity EU initiative. Professional Contributions encompass advisory roles for international organizations like RIBA, policy briefs for the United Nations University, and design competitions in China, India, and the UK. His [CPU]ai atelier redefines architectural education through computational complexity.
Stavros Vologiannidis serves as an Assistant Professor in the Department of Informatics, Computer and Telecommunications Engineering at the International University of Greece. His academic career spans both teaching and research in control theory, robotics, and machine learning applications. Previously, he was associated with the Mathematics Department at Aristotle University of Thessaloniki where he completed his education and conducted postdoctoral research. Education: B.Sc. in Mathematics from Aristotle University of Thessaloniki (1997) Ph.D. in Control Theory from Aristotle University of Thessaloniki (2005) with dissertation titled 'ALGEBRAIC-POLYONYMICAL COMPUTING METHODS IN CONTROL THEORY' Dr. Vologiannidis' research focuses on Classical and Intelligent Control Theory, Robotics, and Machine Learning, with particular expertise in polynomial matrices and automatic control systems. His work bridges theoretical mathematics with practical engineering applications, especially in educational robotics and industrial control systems. He has developed several educational platforms including EUROPA, a ROS-based educational robot for teaching sensor integration and data acquisition. His publication record shows a clear evolution from theoretical control systems research toward applied machine learning and educational technology. Recent work demonstrates increasing focus on practical applications of AI in education, urban feature recognition, industrial monitoring, and robotics education across multiple educational levels from middle school through university. His research combines mathematical rigor with real-world implementation. Scientific Recognition: Excellence Scholarship in the 'Excellence Scholarships 2010' program of the Research Committee Total citations exceeding 250 with Scopus H-index of 9 Dr. Vologiannidis has secured numerous research grants and led multiple projects including 'Rapid Earthquake Damage Assessment Consortium – REDACt', 'Predictive Maintenance 4.0', and 'Development of computational methods for optimization of eigenvalue assignment problems'. He has collaborated extensively with institutions across Europe including UTIA Foundation in Prague and has participated in EU-funded projects like GALENOS and GN4-1 GÉANT Research and Education Networking. His laboratory work centers around the EUROPA educational robotics platform and the StreetScouting urban feature detection system, both of which integrate hardware, software, and educational applications. These projects demonstrate his commitment to translating theoretical research into practical educational and industrial tools.
Gregory Key serves as a Turkish Lecturer within the Middle Eastern and Ancient Mediterranean Studies program at Binghamton University. His responsibilities encompass teaching modern Turkish language courses at elementary and intermediate levels, as well as Ottoman Turkish, Turkish literature in translation, and Turkish media and pop culture. Key's research is centered on Turkish linguistics, with a focus on morphosyntax. He investigates the structural properties of Turkish, including causative constructions, unaccusative verbs, and differential object marking. His theoretical work aims to understand Turkish as a coherent synchronic system, and he actively explores the implications of linguistic theory for language pedagogy. His scholarly output demonstrates a consistent emphasis on syntactic and morphological phenomena in Turkish and related languages. Recent publications address complex predicates, language contact between Turkic and Persian, and the decomposition of verbal structures. These contributions highlight his expertise in theoretical linguistics and its application to the Turkish language.
Prosper Dovonon is Full Professor of Economics at Concordia University, Montréal, Canada, where he holds the Tier 1 Concordia University Research Chair in Econometrics of Large Datasets . He is concurrently Adjunct Professor at the University of Adelaide, Australia, and has previously served as Associate and Assistant Professor at Concordia, Visiting Professor at HEC Montréal, and Assistant Vice-President at Barclays Wealth in London. Education Ph.D. in Economics, Université de Montréal (2007) M.Sc. in Statistics and Economics, ENSEA, Abidjan, Côte d’Ivoire (2000) M.Sc. in Mathematics, Université Nationale du Bénin, Abomey-Calavi, Benin (1996) Research Interests Professor Dovonon’s research lies at the intersection of theoretical econometrics and financial data applications . He focuses on developing robust inferential procedures for moment-condition models, bootstrap techniques for high-frequency data, identification issues in GMM, and volatility modeling with factor structures that accommodate skewness and leverage effects. His work on large-dimensional datasets emphasizes scalable methods for estimation and testing in big-data environments. Scientific Awards & Recognition Concordia University Research Chair, Tier 1, in Econometrics of Large Datasets (2022–present) Collaborations & Affiliations Beyond Concordia and the University of Adelaide, he is affiliated with the Centre Interuniversitaire de Recherche en Économie Quantitative (CIREQ) in Montréal and has collaborated with leading scholars across North America, Europe, and Australia. His research is frequently cited in top econometrics and statistics journals, attesting to its broad impact.
Christoph Mulert is a Professor at the Department of Psychiatry and Psychotherapy , Justus-Liebig-Universität Gießen, and serves as the Clinic Director at the University Hospital Giessen. His research focuses on neurophysiological and neurochemical mechanisms underlying visual perception and their alterations in schizotypy. Key research areas include: Gamma oscillations in sensory processing Schizophrenia pathophysiology EEG and fMRI neuroimaging Reward processing networks Dopamine and E/I balance Neural synchronization and hallucinations Recent work explores ketamine models for schizophrenia, tACS applications in psychiatry, and interhemispheric connectivity. Collaborators include G. Leicht, S. Steinmann, and C. Andreou. His team utilizes multimodal neuroimaging to characterize neurophysiological disturbances in psychiatric disorders.
Dr. Silke Hamann is a researcher at the University of Amsterdam, Faculty of Humanities, Department of Linguistics. Her work bridges phonology and phonetics, focusing on the emergence of phonological features, perceptual cues in segmental contrasts, and the interaction of phonology with orthography and language acquisition. Current projects: diachronic loanword adaptation, congenital amusia's impact on speech perception, Bantu languages (with Nancy Kula and Laura Downing), Catalan studies (with Francesc Torres-Tamarit) Research interests span synchronic/diachronic phonology, phonetic perception, computational modeling of phonological acquisition, and cross-linguistic analysis of retroflex consonants. Her publications analyze phenomena in Korean, Japanese, Bantu languages, German, Portuguese, and Slavic languages, with recurring themes of cue weighting, phonological constraints, and orthographic influence. Recent articles highlight her focus on creaky voice diagnostics, loanword phonotactics, congenital amusia, and Bantu intonation systems. Collaborations with Nancy Kula (Bantu) and Francesc Torres-Tamarit (Catalan) underscore her international research network.
Peiyuan Chen is an Associate Professor at the Department of Electric Power Engineering, Chalmers University of Technology. He holds a B.Eng. from Zhejiang University (2004), an M.Sc. from Chalmers (2006), and a Ph.D. from Aalborg University (2010). His research focuses on power system operation and planning with wind power integration, emphasizing time series modeling, statistical analysis, and optimization. He contributes to projects on grid-forming converters, inertia estimation, frequency control, and renewable energy system stability. Research Interests: • Power Systems and Renewable Integration • Grid-Forming Converters and Stability Analysis • Time Series Modeling and Statistical Methods • Machine Learning for Energy Applications • Frequency Control and Synthetic Inertia Recent Publication Trends include studies on deep learning for heating load classification, wind turbine type optimization, fault ride-through capabilities, and inertia estimation in converter-dominated grids. His work bridges theoretical power system analysis with practical implementations in Nordic and European energy networks. Projects (2017-2024) include grants from the Swedish Energy Agency, Swedish Research Council (VR), and collaborations with institutions in Sweden, China, and Italy. Key areas: grid strength metrics, multiport converter applications, and citizen energy communities.
Sophie N. Parragh is Professor and Head of the Institute of Production and Logistics Management at Johannes Kepler University Linz, where she also serves as program director of the master's degree program in Economic and Business Analytics. She received her PhD from the University of Vienna in 2009 and completed her habilitation in 2016, following postdoctoral research at the IBM Center for Advanced Studies in Porto and a visiting professorship at the Vienna University of Economics and Business. Her research focuses on developing exact and heuristic optimization algorithms for complex logistics and transportation problems. Key areas include vehicle routing, green logistics, disaster relief distribution planning, scheduling, and multi-objective optimization. She has particular expertise in branch-and-bound, branch-and-price, column generation, and metaheuristics approaches to solve challenging combinatorial optimization problems. Dr. Parragh's publication record shows a consistent trend toward increasingly complex multi-objective problems, with recent work focusing on electric vehicle routing, multi-echelon production planning under uncertainty, and bi-objective facility location problems with applications in disaster relief. Her research bridges theoretical optimization methods with practical applications in logistics and transportation. Scientific Awards: ÖGOR (Austrian Society for Operations Research) dissertation prize doc.award from the University of Vienna Hertha Firnberg Postdoc fellowship from the Austrian Science Fund (FWF) Dr. Parragh has served as department editor for OR Spectrum and as associate editor for Transportation Science, Transportation Research Part B: Methodological, INFORMS Journal on Computing, and Networks. She has led and participated in numerous third-party funded research projects in operations research, including work in healthcare logistics, field staff routing, production planning, and electric vehicle routing. In 2021-2022, she co-organized the monthly VeRoLog webinar series, demonstrating her active engagement with the international operations research community. She maintains strong research collaborations across Europe, evidenced by her co-authored publications with researchers from institutions in Austria, France, Portugal, Denmark, and beyond. Her work consistently addresses both theoretical challenges in optimization and practical applications in industry and public service contexts.
