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Christian WeberView profile

Senior Lecturer

• Cybersecurity
• Digital Health
• Smart Environments
• +4 more

Christian Weber serves as a Senior Lecturer & Researcher at the Institute of Business Information Technology within the Zurich University of Applied Sciences (ZHAW) School of Management and Law. He directs the CAS Cyber Security program and contributes to the ZHAW Digital Health Lab, focusing on sustainable digital ecosystems and security frameworks. His educational background includes an Executive MBA in General and Entrepreneurial Management from Johannes Gutenberg-Universität Mainz/McCombs School of Business and a Dipl.-Ing in Industrial Electronics & Electrical Power Engineering from RheinMain University of Applied Sciences. His continuing education spans numerous certifications in AI, sustainability, and digital health from institutions including Hasso Plattner Institute. Weber's research centers on sustainable smart solutions for digital ecosystems, including digital health, ambient assisted living, and smart environments. His work explores computer-supported cooperative working scenarios, applications of open source systems in SMEs, and data protection, cybersecurity, compliance, and forensics as enablers for digital ecosystems. His teaching portfolio spans multiple modules in IT Security, Emerging Technologies, IoT-Data Streaming & Analytics, and Digital Transformation across BSc and MSc Business Informatics programs. His recent publications demonstrate strong interdisciplinary connections between cybersecurity, digital health, and organizational transformation, with particular emphasis on practical applications in real-world settings. His work bridges technical implementations with organizational and societal impacts of digital technologies. Best Paper Award at SMART 2018 for "Citizens as Sensors" research "Educate to lead" award from Soroptimist International Europe for STEM outreach Weber's professional experience combines academic leadership with industry expertise, having served as Managing Director of the Cisco Networking Academy since 2012 and holding previous positions as Administrative Professor and Lecturer at University of Applied Sciences Braunschweig/Wolfenbüttel. His industry background includes executive roles as CIO/CTO and IT management consulting. He contributes to the ZHAW Digital Health Lab and has led projects including the ZHAW Digital Culture Assessment and Digital Health Hackathon, focusing on practical implementations of digital health solutions and organizational transformation.

Barbara NamerView profile

Adjunct Professor

• Translational Pain Research
• Neurophysiology
• Peripheral Nervous System
• +6 more

Barbara Namer is an Adjunct Professor at Friedrich-Alexander University Erlangen-Nuremberg and leads the IZKF-funded "Neuroscience: translational pain research" group at RWTH Aachen University Hospital. Her career spans 20+ years in neurophysiological pain research with clinical translations. Doctor of Medicine (2000-2004), Erlangen-Nuremberg Venia Legendi (Habilitation) in Physiology (2010) Adjunct Professor title (2018) Her research focuses on nociceptor mechanisms in diabetic neuropathy, migraine pathophysiology, and TRPA1 channel dynamics . Computational modeling and human microneurography techniques are central to her work. Key publication trends show expertise in peripheral nerve sensitization , diabetic pain mechanisms , translational pain modeling , and ion channel pharmacology . She has received multiple DGSS and German Neurology Society awards for her pain research. 2019 - DGSS Poster Award 2015 - DGSS Poster Award 2010 - EFIC Grünenthal Grant 2003 & 2018 - German Neurology Society Awards National and international collaborations include research stays in Norway and Sweden, with extensive grant funding from DFG and IZKF projects.

Gerhard WolberView profile

Professor

• Computational Drug Design
• G-Protein Coupled Receptors (GPCRs)
• Cytochrome P450 Enzymes
• +3 more

Professor Gerhard Wolber leads the Molecular Drug Design research group at the Institute of Pharmacy , Freie Universitaet Berlin. His work focuses on computational approaches to drug discovery, with expertise in G-protein coupled receptors (GPCRs) , cytochrome P450 enzymes , Toll-like receptors , and viral protease inhibitors . He supervises a team of 13 PhD candidates 3 researchers 2 Master's students engaged in projects ranging from calcium channel blockers to CYP enzyme modulators for cancer therapy. Recent publications highlight his lab's contributions to pan-coronavirus drug discovery, TLR8 antagonism, and calcium channel inhibition. The team employs advanced methodologies including Molecular dynamics simulations Fragment-based de novo design Bayesian neural networks DFT calculations 3D pharmacophore modeling to bridge computational predictions with experimental validation. Notable projects include Virtual screening for TREM2-targeted glioblastoma therapeutics Allosteric communication path analysis via MDPath Immune checkpoint inhibitors for cancer immunotherapy Biased GPCR ligand development demonstrating a multidisciplinary approach to contemporary drug design challenges.

• Computer Vision
• Applied Machine Learning
• Computer Graphics
• +3 more

Fahim Hasan Khan is an Assistant Professor in the Computer Science and Software Engineering Department at California Polytechnic State University, San Luis Obispo (Cal Poly). His research focuses on computer vision, applied machine learning, and citizen science applications, with a special emphasis on environmental monitoring and education. He holds a PhD in Computer Science and Engineering from UC Santa Cruz, where he was advised by Professors Alex Pang and James Davis, and a Master's in Computer Science from the University of Calgary. Key research contributions include real-time rip current detection systems (RipFinder, RipScout), mobile citizen science platforms (SmartCS), and educational tools to engage high school students in STEM research. His work has received media attention for innovations in drowning prevention and environmental safety. Notable awards include the Best Poster Presentation Award at ICIAR 2019 and the Best of the Baskin School of Engineering Award at UC Santa Cruz in 2022. Dr. Khan collaborates extensively with industry and academic partners to develop practical solutions for challenges in marine safety, autonomous systems, and healthcare diagnostics. He actively mentors students and seeks to democratize access to machine learning tools through no-code platforms.

• Scanning Transmission Electron Microscopy (4D-STEM)
• Open Source Scientific Software Development
• Big Data Processing in Electron Microscopy
• +4 more

Magnus Nord is an Associate Professor in the Department of Physics, Faculty of Natural Sciences at Norwegian University of Science and Technology (NTNU). His research focuses on advanced electron microscopy techniques and computational tools for materials characterization. Research Interests : Scanning Transmission Electron Microscopy (4D-STEM), Open Source Scientific Software Development (Python), Big Data Processing, Magnetic/Electric Field Imaging, Structural Characterization using Higher Order Laue Zones. Publications span cutting-edge applications in functional materials, nanomagnets, and perovskite thin films, with emphasis on machine learning and precession-enhanced imaging. Key keywords include Materials Science , Electron Microscopy , and Computational Imaging . Software Development : Lead developer of Atomap and pyxem , contributing to HyperSpy and merlin_interface for electron microscopy data analysis. Current Research Funding : InCoMa (Research Council of Norway) IMPRESS (Horizon EU Program)

Jeffrey YoungView profile

Researcher

• High-Performance Computing (HPC)
• Computer Architecture
• Quantum Programming
• +6 more

Jeffrey Young is a Principal Research Scientist at Georgia Institute of Technology, working with the Partnership for Advanced Computing Environments (PACE) and leading Georgia Tech’s Open Source Program Office. His research focuses on high-performance computing (HPC), computer architecture, and novel accelerators including GPUs, FPGAs, and Arm/RISC-V processors. He leads next-generation computing strategy at PACE and directs the NSF-funded CRNCH Rogues Gallery testbed, which explores post-Moore accelerators like neuromorphic and near-memory systems. His work bridges hardware-software co-design and scientific software engineering. Recent research trends show expertise in quantum programming (Qwerty/ASDF), heterogeneous computing (Cupbop), and memory system optimization across GPUs, FPGAs, and CPUs. He has contributed to exascale workflows (HIPLZ), safe HPC libraries, and UAV co-simulation frameworks. Scientific Awards: NSF-funded CRNCH Rogues Gallery testbed (2020-2024) Education: Ph.D. in Computer Architecture (2013), advised by Dr. Sudhakar Yalamanchili Labs & Initiatives: Director, CRNCH Rogues Gallery testbed Co-Director, Georgia Tech Center for Scientific Software Engineering Director, Georgia Tech Open Source Program Office

Kevin A AdkinsView profile

Professor

• Advanced Air Mobility (AAM)
• Uncrewed Aircraft Systems (UAS)
• UAS Applications
• +5 more

Dr. Kevin A. Adkins is a Professor in the College of Aviation at Embry-Riddle Aeronautical University , where he teaches aerodynamics, aircraft performance, and uncrewed aircraft systems (UAS) courses. He pioneered the first collegiate Advanced Air Mobility (AAM) course in the U.S. in 2023 and directs two labs: the Advanced Air Mobility Research and Innovation Lab (AAMRIL) and the Uncrewed Vehicle and Atmospheric Investigation Lab (UNVAIL) . Education : Ph.D. in Aerospace Engineering (Mississippi State University), M.Eng. and B.S. in Aerospace Engineering (University of Michigan-Ann Arbor) His research focuses on atmospheric boundary layer meteorology using UAS, AAM concepts of operation (ConOps), and flight test engineering. He collaborates extensively on sensor development for environmental monitoring, including low-cost particulate matter sensors and bioaerosol sampling mechanisms. Recent publications emphasize UAS applications in wildfire detection, urban microclimate analysis, and wind farm humidity studies. Dr. Adkins serves on advisory committees for the Florida Department of Transportation's AAM initiative and ASTM International's UAS standards. Awards : Fellow of the Royal Aeronautical Society, ERAU Researcher of the Year (2020), PIEoneer Real Life Learning Award (2019), AUVSI Best Paper Award (2019) He mentors numerous student projects on UAS sensor development and atmospheric research, with teams winning symposium awards. His labs integrate experiential learning with international fieldwork in Puerto Rico, Norway, and Lithuania.

Guannan LiuView profile

Assistant Professor

• Cybersecurity
• Network Security
• System Security
• +4 more

Guannan Liu is an Assistant Professor of Computer Science at the Colorado School of Mines, specializing in cybersecurity and network security. He holds a Ph.D. in Computer Engineering from Virginia Tech (2023) and a BS from Purdue University (2016). His research focuses on system/network security, human-factor security, cloud computing security, and user authentication mechanisms. He has identified critical vulnerabilities in online services, collaborating with major tech firms to address resource mismanagement issues. Dr. Liu's work has been published in top-tier security conferences. He actively seeks motivated students for cybersecurity research projects. His honors include a Student Travel Grant for DSN 2022 and academic recognition through Dean’s List distinctions. His research bridges theoretical insights with practical impact, particularly in identifying real-world system vulnerabilities through comprehensive measurements. Key areas of exploration include container registry typosquatting, cloud gaming service misuse, DNS query analysis, and acoustic side-channel attacks on IoT devices. His interdisciplinary work integrates software engineering, artificial intelligence, and network measurement techniques to enhance security across diverse systems.

Erjia YanView profile

Associate Professor

• Informetrics
• Scientometrics
• Scholarly Data Mining
• +6 more

Erjia Yan is an Associate Professor in the Department of Information Science at Drexel University's College of Computing & Informatics. His research focuses on informetrics, scientometrics, scholarly data mining, and knowledge diffusion studies, contributing to understanding scientific activity, innovation propagation, and equitable science policymaking. PhD, Information Science, Indiana University Bloomington Master of Information Science, Indiana University Bloomington Bachelor of Science, Nanjing University Dr. Yan's work integrates network science and data analysis to examine scholarly communication methods, academic mobility patterns, and the impact of software in scientific literature. He has published extensively on topics including HBCU faculty dynamics, open access effects, and biases in citation practices. Recent publications highlight trends in academic mobility, knowledge transfer across sectors, ethical data collection, and the role of software in research. His studies span interdisciplinary collaborations, digital equity, and the evolution of disciplinary vocabularies. Dr. Yan's research has implications for equitable scientific workforce development, transparent policymaking, and enhancing bibliographic information retrieval systems.

• Biomechanics
• Tissue Engineering
• Prosthetics Design
• +5 more

Professor Mark Thompson is an Associate Professor in Engineering Science at the University of Oxford and a Tutor/Fellow at Wadham College. He holds an MEng in Engineering and Materials Science (Oxford, 1997) and a PhD in Biomechanics from the University of London (2001). His research focuses on biomechanical engineering with emphasis on tissue repair, prosthetic design, and trauma modeling. Key projects include the OxVent ventilator and in vitro microvasculature systems for traumatic injury studies. His work bridges clinical and engineering challenges, addressing issues like prosthetic maintenance, musculoskeletal modeling, and biomaterials for regenerative medicine. Thompson collaborates with institutions like the Institute of Biomedical Engineering and has contributed to open-source frameworks for motion capture analysis. Current research trends involve mechanobiology of soft tissues and bioprinting for trauma research. Labs/Teams: Affiliated with the Institute of Biomedical Engineering and Oxford e-Research Centre. His work aligns with translational medicine and emergency medical device development. Future directions include optimizing 3D-printed bio-artificial tissues and advancing tactile feedback systems for prosthetics.

Ana PaivaView profile

Professor

• Social Robotics
• Affective Computing
• Virtual Agents
• +5 more

Ana Paiva is a Full Professor in the Department of Computer Science and Engineering at the University of Lisbon's Instituto Superior Técnico (IST), and coordinator of the GAIPS research group at INESC-ID, now focused on AI for People and Society. She holds a Katherine Hampson Bessell Fellowship at Harvard University's Radcliffe Institute for Advanced Study. Her work centers on creating socially intelligent AI and robots through agent-based approaches, emphasizing emotional and cultural competencies. Key research areas include Social Robotics, Affective Computing, and Pro-social Computing. She leads projects like the EU-funded ANIMATAS ITN network and Portugal's AMIGOS/AGENTS initiatives. Notable contributions include the FAtiMA Toolkit for developing emotional AI agents and pioneering work in hybrid human-machine societies. She has received awards such as the EurAI Fellowship (2019) and the Blue Sky Ideas Award at AAAI’18. Her research explores how machines can foster prosocial behaviors like altruism and cooperation, with applications in education, therapy, and ethical AI design. Her advising includes PhD students like Fernando Santos (Victor Lesser Award winner) and Elmira Yadollahi (ACM award recipient). Current projects focus on inclusive robotics for mixed-ability classrooms and ethical frameworks for human-robot collaboration.

Sandra Diaz PierView profile

Researcher

• Computational Neuroscience
• High Performance Computing
• Machine Learning
• +3 more

Dr. Sandra Diaz Pier is a Scientific Lead at the Jülich Supercomputing Centre (JSC) within the Jülich Research Centre , Germany. Specializing in computational neuroscience , high performance computing (HPC) , and machine learning , she bridges neuroscience and advanced computational methods through her research. Education: B.Sc. in Electronic Systems Engineering, Mexico M.Sc. in Computer Science (focus: machine learning, quantum computing), Mexico Second M.Sc. in Electrical Engineering, Ontario, Canada Ph.D. in Computer Science, Germany (2021) Her research focuses on modeling and simulating brain dynamics and plasticity at multiple scales, leveraging HPC to accelerate large-scale neural network simulations. She actively contributes to EU projects like the Human Brain Project (HBP) , Virtual Brain Cloud , and EBRAINS 2.0 , emphasizing infrastructure development and educational training. Her work includes open-source tools such as the NEST simulator , The Virtual Brain , and L2L , enabling efficient parameter exploration and multiscale co-simulation frameworks. The 15 most recent publications highlight her interdisciplinary approach, spanning topics from quantum computing in biomolecular simulations to neural plasticity algorithms and cloud-based brain modeling . These articles reflect her expertise in integrating machine learning , multi-scale simulation , and HPC infrastructure for neuroscience challenges, including seizure propagation, Parkinson’s disease progression, and swarm intelligence in spiking networks. She leads technical coordination in projects like EBRAINS and serves as a task leader in the HBP infrastructure work package , while also organizing workshops and hackathons for open-source tools. Her role involves supporting domain scientists through methodological research and workflow optimization for brain simulations.

• Markov chain Monte Carlo
• Monte Carlo methods
• Bayesian computation
• +1 more

Dootika Vats is an Associate Professor in the Department of Mathematics & Statistics at Indian Institute of Technology Kanpur (IIT Kanpur). She earned her PhD in Statistics from the University of Minnesota, Twin-Cities, and her research focuses on advancing Monte Carlo and Bayesian computational methods, especially Markov chain Monte Carlo diagnostics. Education: PhD, Statistics, University of Minnesota, Twin-Cities, Feb 2017 MS, Statistics, University of Minnesota, Twin-Cities, Nov 2016 MS, Statistics, Rutgers University, New Brunswick, May 2012 BA (honors), Mathematics, University of Delhi, Lady Shri Ram College, May 2010 Research Interests: Her work lies at the intersection of computational statistics and Bayesian inference, with core emphases on: Markov chain Monte Carlo (MCMC) methodology Monte Carlo variance estimation and output analysis Bayesian computation and diagnostics Geometric ergodicity and convergence rates of MCMC algorithms Recent Publications Trend: Across her recent articles and preprints, Dr. Vats has consistently tackled open problems in MCMC output analysis, introducing new diagnostics, optimal batch-size selection, and visualization tools that directly impact practical Bayesian computation. Her contributions bridge theoretical rigor—such as proving strong consistency of spectral variance estimators—with immediately applicable software and graphical methods. Awards & Honors: Director’s Award, University of Minnesota School of Statistics, 2016 Graduate Research Partnership Program Fellowship, Summer 2016 Louise T. Dosdall Fellowship for Women in STEM, 2016–2017 School of Statistics Alumni Fellowship, 2015–2016 Martin–Buehler Fellowship in Statistics, Fall 2015 Bernard W. Lindgren Graduate Student Teaching Award, Spring 2014 Lynn Lin Fellowship in Statistics, Summer 2014 Teaching & Mentoring: At IIT Kanpur she continues to teach and mentor within the statistics curriculum. Earlier, at the University of Minnesota, she served as Instructor for STAT 3011 and as a teaching assistant across multiple undergraduate and graduate courses; at Rutgers University she was a part-time lecturer in calculus and pre-calculus. Labs & Collaboration: While no specific lab is named, her research is computational and collaborative; she has worked with James M. Flegal, Galin L. Jones, and other leading MCMC methodologists, and her Google Summer of Code participation demonstrates engagement with the open-source statistics community.

• Educational Psychology
• Student Motivation
• STEM Learning
• +4 more

David A. Bergin is a Professor of Educational Psychology at the University of Missouri, specializing in student motivation, STEM learning, and the development of interest. He holds a PhD and an Educational Specialist degree from Stanford University. His work emphasizes understanding how motivation influences academic and informal learning, particularly for underrepresented groups. Bergin is a past president of APA's Division 15 (Educational Psychology) and has contributed to editorial boards of top journals like Journal of Educational Psychology . Research Interests : Bergin investigates how interest and motivation drive learning outcomes, classroom engagement, and career choices. He explores the impact of teacher-student relationships, competition, and cultural factors on student achievement. His recent work includes studies on robotics-based engineering education, interdisciplinary neuroscience curricula, and interventions for underrepresented students. Awards & Recognition : Outstanding College Teaching Award (University of Missouri College of Education, 2018) Fulbright Scholar (2013, teaching motivation courses in Chile) Key Contributions : Co-author of Child and Adolescent Development in Your Classroom (3rd ed.), a widely used teacher-training textbook. He has also developed the Classroom Engagement Inventory and contributed to TIMSS data analysis on international education trends. Advising & Grants : Bergin has advised numerous studies on STEM motivation, low-stakes testing, and college access programs for marginalized students. His grants include funding for neuroscience education initiatives and engineering design learning projects.

Deborah GreavesView profile

Professor

• Offshore Renewable Energy
• Marine Renewable Energy
• Ocean Engineering
• +12 more

Professor Deborah Greaves is a leading academic in Ocean Engineering at the University of Plymouth, where she holds the position of Professor in the School of Engineering, Computing and Mathematics. She is Director of the Supergen Offshore Renewable Energy (ORE) Hub and the Coastal, Ocean and Sediment Transport (COAST) Laboratory, and served as Head of School from 2017 to 2022. Her work is central to advancing offshore renewable energy in the UK and globally. Her research focuses on offshore and marine renewable energy, particularly wave and tidal technologies, wave-structure interactions, and the integration of physical and numerical modelling. She leads major collaborative projects including the Collaborative Computational Project in Wave Structure Interaction (CCP-WSI) and PRIMaRE, and has secured significant funding from EPSRC, EU Interreg, H2020, and InnovateUK. Her research supports the UN Sustainable Development Goals, especially those related to affordable and clean energy and climate action. The 15 most recent articles reflect a strong trend toward interdisciplinary research, combining engineering innovation with environmental sustainability, policy development, and public engagement. Her work spans fundamental hydrodynamics, technology development, commercialization challenges, and societal impact, with increasing emphasis on decarbonisation, net zero strategies, and inclusivity in engineering. Officer of the Order of the British Empire (OBE), 2018 Fellow of the Royal Academy of Engineering (FREng) Fellow of the Institution of Civil Engineers (FICE) Deborah leads a large team of researchers and PhD students, securing over £20 million in research funding. She is deeply involved in mentoring and outreach, particularly in promoting gender diversity in engineering through initiatives like WISE and Supergen ORE’s EDI programs. She has advised numerous PhD students and leads multidisciplinary teams across academia and industry. She directs the COAST Engineering Research Group and the COAST Laboratory, a state-of-the-art facility with wave basins and flumes for testing marine renewable technologies. She also leads the Supergen ORE Hub, a national consortium uniting universities and industry, and is instrumental in the development of the new Engineering and Design Facility at Plymouth, fostering interdisciplinary collaboration between engineering, computing, and design.