J. Artur Serrano is a Professor at the Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU). His research focuses on Care technology for neurocognitive disorders Social robots in dementia care User participation in technology design His work spans Health Informatics , Gerontechnology , and Human-Robot Interaction , with a strong emphasis on Immersive environments for dementia Emotional connection through technology Co-creation in healthcare Notable trends in his publications include SENSE-GARDEN Project applications, smart furniture systems , and VR/ICT-based therapies for elderly care. He is affiliated with research platforms like IMRO-lab and LIFEBOTS Exchange , focusing on Robot deployment in homes Context-aware assistive devices Ethical technology adoption across Norway.
Krishnadas Nanath is a Researcher at Middlesex University's CPC Computer Engineering & Informatics PG Research Institute in Dubai. His work spans machine learning, smart technologies, and sustainability. Research Focus: Mental health modeling during pandemics Fake news virality analysis Smart tourism systems Green IT implementation Cloud computing adoption Decision analytics Article Trends: Recent work combines sentiment analysis with machine learning for social impact studies, while earlier research focuses on cloud computing and sustainability. Key disciplines include Computer Science, Environmental Science, and Education Technology. Contact: K.Nanath@mdx.ac.uk | ORCID
Shan Bao is a Professor and Chair in the Department of Industrial and Manufacturing Systems Engineering at the University of Michigan-Dearborn, with a joint appointment as Research Professor at the University of Michigan Transportation Research Institute (UMTRI) Human Factors Group. She is affiliated with the UM Civil and Environmental Engineering department, UM Robotics Institute, and the Institute of Data Science. Ph.D. in Mechanical and Industrial Engineering, University of Iowa (2009) B.E. in Mechanical Engineering, Hefei University of Technology, China (2000) Dr. Bao specializes in human factors related to connected and automated vehicle technologies, ADAS system evaluation, big data analysis, driving behavior modeling, and vulnerable road user safety. Her research includes algorithm development, statistical modeling, and evaluation of safety technologies. Her recent publications focus on multimodal interfaces for AV accessibility, driver fatigue analysis, pedestrian conflict modeling, and machine learning applications in transportation safety. Grants include projects on global AEB testing harmonization, inclusive AV design, and driver-to-driver communication infrastructure.
Isabel Pedrosa is an Associate Researcher at ISTAR-Iscte Research Center within ISCTE - University Institute of Lisbon. She specializes in Information Systems with a focus on computer-assisted auditing, fraud detection analytics, and gender disparities in technology. Her academic journey includes a PhD in Information Science and Technology (ISCTE-IUL), a Master's in Systems and Informatics, and a Bachelor's in Informatics Engineering (both from University of Coimbra), complemented by postgraduate studies in People and Team Management at Coimbra Business School. Her research explores Computer-assisted Audit Tools , Fraud Analytics , and Business Intelligence , with significant work on technology adoption models in auditing. Recent publications analyze AI's impact on accounting, cybersecurity disclosures, and gender bias in STEM education. She maintains active collaborations across Portuguese academic institutions including Instituto Superior de Contabilidade e Administração de Coimbra. Scientific Awards: International CIDA Certification, Certified IDEA Data Analyst (2017) Ambassador for ISACA Lisbon Chapter's She Leads Tech gender equality initiative She coordinates postgraduate programs in Audit, Risk and Control of Information Systems and has advised over 80 Master's students on topics spanning data analytics, AI in auditing, and business intelligence. Her teaching includes the course 'Analytical Methods for Fraud Detection' at INDEG-IUL.
Raghava Gundala is an Associate Professor of Marketing at the University of Wisconsin-Parkside. His academic work focuses on marketing strategy , consumer behavior , and digital transformation in retail . Key research areas: Marketing, Consumer Behavior, Digital Marketing, Brand Management His recent publications analyze AI chatbots in customer engagement , AR-based fashion retail , CSR impacts on purchasing , and gender dynamics in organic food consumption . He contributed expert insights to MoneyGeek's car insurance analysis, linking marketing principles to consumer risk perception. Raghava's scholarly output spans 20 years, covering topics like experiential learning , glocalization in the Caribbean , and brand switching in telecom markets . His work integrates theoretical frameworks with real-world case studies across diverse industries.
Alexei Efros is a Professor in the Electrical Engineering and Computer Sciences Department at UC Berkeley's College of Engineering, where he holds the Howard Friesen Professorship. He is a leading researcher in computer vision and computer graphics, with a focus on data-driven techniques and self-supervised learning. His work bridges the intersection of vision and graphics, leveraging large quantities of unlabeled visual data to tackle complex problems. Dr. Efros received his PhD from UC Berkeley in 2003 and joined the Berkeley faculty in 2013 after spending a decade at Carnegie Mellon University. He has also held affiliations with École Normale Supérieure/INRIA and the University of Oxford. His research group is part of the Berkeley Artificial Intelligence Research Lab (BAIR). His research interests span computer vision, computer graphics, artificial intelligence, and machine learning, with particular emphasis on data-driven approaches, self-supervised learning, computational photography, and visual data mining. Efros has pioneered numerous techniques in image synthesis, scene understanding, and visual representation learning that have shaped modern computer vision research. An analysis of his recent publications reveals a strong focus on generative models, particularly diffusion models and their applications; interpretability of vision-language models like CLIP; 3D scene understanding and reconstruction; and the application of self-supervised techniques to video and spatial reasoning problems. His work continues to push boundaries in how machines understand and generate visual content. Among his numerous accolades are the ACM Prize in Computing (2016), multiple Helmholtz Test-of-Time Prizes, the SIGGRAPH Significant New Researcher Award, Sloan and Guggenheim Fellowships, and teaching awards including the Jim and Donna Gray Award for Excellence in Undergraduate Teaching (2023). Professor Efros has mentored an impressive cohort of students who have gone on to prominent positions in academia and industry, including faculty positions at CMU, TTIC, Stanford, and research scientist roles at OpenAI, Google DeepMind, and Anthropic. His teaching includes core computer vision courses at both undergraduate and graduate levels.
Dan Andrei Iancu is an Associate Professor in the Operations, Information & Technology department at Stanford Graduate School of Business . He is also a Faculty Affiliate at the Woods Institute and affiliated with the Emmett Interdisciplinary Program in Environment and Resources (E-IPER) . A Romanian native, he holds a PhD in Operations Research from MIT, an S.M. in Engineering Sciences from Harvard, and a BS in Electrical Engineering and Computer Science from Yale. Education PhD, Operations Research, MIT (2010) S.M., Engineering Sciences, Harvard (2006) BS, Electrical Engineering and Computer Science, Yale (2004) His research bridges operations, finance, risk management, and ethics , focusing on responsible analytics and data-driven optimization . Key methodological contributions include robust optimization , fairness frameworks , and dynamic risk modeling , with applications spanning global supply chains , FinTech , and healthcare . Recent work emphasizes environmental sustainability and equitable decision-making in complex systems. His publications in Management Science , Operations Research , and Mathematics of Operations Research reveal a focus on supply chain resilience , financial covenants , and AI ethics . Awards include multiple INFORMS best paper prizes , Stanford faculty scholarships , and the Herman Goldstine Fellowship . Scientific Awards INFORMS Optimization Society Young Researchers Prize (2018) INFORMS JFIG Best Paper Award (2013) Best Student Paper Prize, INFORMS Optimization Society (2009) Herman Goldstine Fellowship (2010) Outstanding Teaching Assistant Award, MIT Sloan (2010) Finalist, INFORMS George Nicholson Student Paper Competition (2018) Winner, SAWIT Challenge (2016) MSOM Interface of Finance, Operations and Risk Management Best Paper Award (2018) He has advised students across Stanford's OIT, E-IPER, and Wharton , with placements at institutions like Mit Sloan and companies such as Uber and Morgan Stanley . Collaborative grants and projects often involve IBM Watson Research and USAID partnerships.
Panagiotis Adamopoulos is an Associate Professor of Information Systems at Emory University's Goizueta Business School. His research explores how information systems and digital technologies shape user behavior and business transformation, focusing on personalization, mobile/social commerce, and online education. Education: PhD from NYU Stern, MPhil from NYU, BSc from Athens University of Economics and Business (ranked 2nd in department history). Research Interests: He investigates personalization systems (e.g., mitigating 'filter bubbles'), IoT-driven sales channels, mobile recommendation effectiveness, personality traits' impact on social media WOM, and MOOC design. His work combines big data analytics, machine learning, econometrics, and experimental designs. Scientific Recognition: INFORMS and AIS Mid-Career, Young Scholar, and Early Career Awards Amazon, Wharton Customer Analytics, and Marketing Science Institute Grants Best Paper Award Nominations at INFORMS and ACM Teaching Excellence Awards at Emory and University of Minnesota Teaching Impact: He has taught courses like Machine Learning II, Managing Big Data, and Capstone Projects with high student evaluations (4.7-5.0/5.0). Clients for his capstone projects include Amazon, Delta Air Lines, and The Home Depot. Industry Background: Prior roles at Relational S.A. (Senior BI Engineer) and Toyota Hellas (IT Business Analyst).
Adam Berry is a Professor and Deputy Director of the Human Technology Institute at the University of Technology Sydney (UTS). He previously served as Deputy Director of the UTS Data Science Institute from 2021-2024. His work focuses on leading inclusive, responsible and innovative artificial intelligence for Australia, with emphasis on translating data into real-world impact through data curation, machine learning, and statistical approaches. Education: PhD in Computer Science, University of Tasmania (2004-2008) BSc (Hons) in Computer Science, University of Tasmania (1999-2003) Professor Berry's research spans ethical AI, energy systems, and accessibility. His work consistently bridges theoretical research with practical implementation, focusing on human-centered AI that delivers value while upholding rights and preventing harm. He has a strong track record in multi-disciplinary collaboration, bringing together expertise from computer science, social science, electrical engineering, and ethics. His recent publications reveal a strategic evolution from foundational work in energy systems and reinforcement learning toward increasing focus on ethical and responsible AI frameworks. While maintaining strong contributions to energy analytics (electricity price forecasting, carbon intensity prediction), his 2021 survey on ethical AI principles marks a significant pivot toward governance and implementation frameworks for trustworthy AI systems. Scientific Awards: CSIRO Collaboration medal (inaugural winner) Professor Berry has secured substantial funding from diverse sources including the Digital Health CRC, Australian Renewable Energy Agency, Department of Home Affairs, and industry partners. He has led multi-million dollar initiatives like the National Energy Analytics Research Program and currently oversees the Human Technology Institute's mission for responsible AI. His industry collaborations include partnerships with Reejig (ethical talent AI), Sydney Trains (delay prediction systems), and numerous energy sector organizations. He actively contributes to the Disability Research Network, applying data-driven approaches to improve outcomes in the disability sector. As part of the Trustworthy Digital Society research center, he advances human-centered AI through cross-disciplinary work that integrates technical expertise with social considerations. His leadership spans research design, capability development, and strategic partnership building across government, industry, and academic sectors.
Jennifer Calhoun, Ph.D., is an Associate Professor at the College of Business , Coastal Carolina University , specializing in Hospitality and Tourism Management . With over two decades of academic and industry experience, her research focuses on sustainability practices, sharing economy dynamics, organizational reliability, and cross-cultural workforce development in the hospitality sector. Education: Ph.D. in Hospitality Management (Auburn University), MBA (University of Central Florida), Bachelor of Science in Hotel Management (University of West Indies) Her scholarly work explores intersections between technology adoption, service management, and environmental responsibility. Current projects examine human-robot interaction anxieties and their impact on workforce retention. Dr. Calhoun maintains active industry engagement through consultancy work with J&J Calhoun and Associates and leadership roles at the American Hotel & Lodging Educational Institute.
Dr. Abid Mehmood serves as an Associate Professor at The Beacom College of Computer & Cyber Sciences, Dakota State University, leveraging over 20 years of combined academic and industry expertise to advance artificial intelligence applications in critical domains including healthcare, precision agriculture, and surveillance systems. His educational foundation includes: Ph.D. in Computer Science from Universiti Teknologi Malaysia (2014) M.Sc. in Computer Science from Quaid-i-Azam University (2001) B.Sc. in Computer Science from University of Peshawar (1998) Dr. Mehmood's research centers on applied machine learning and deep learning , with pioneering work in computer vision for medical diagnostics (skin lesion classification, glaucoma detection), precision agriculture solutions (automated fruit disease identification, crop yield estimation), and surveillance technologies (real-time anomaly detection in video streams). His predictive analytics expertise extends to healthcare sentiment analysis, financial forecasting, and driver behavior monitoring, consistently translating theoretical AI advances into practical implementations across diverse sectors. Analysis of his 15 most recent publications (2021-2024) reveals a pronounced interdisciplinary focus, with 60% dedicated to healthcare applications (medical imaging diagnostics), 27% to agricultural technology, and 13% to surveillance/security systems. This trajectory demonstrates strategic alignment with societal needs while maintaining technical rigor in computer vision and deep learning architectures. No scientific awards were documented in the provided materials. Dr. Mehmood has secured substantial research funding through 14 competitively awarded grants (2021-2024) totaling SAR 400,000+ from Saudi Arabian institutions, including King Faisal University and the Ministry of Education. His grant portfolio demonstrates exceptional breadth: Healthcare Innovation : Driver depression monitoring systems, skin lesion classification frameworks, glaucoma diagnostics, and obesity/fatty liver correlation studies Agricultural Technology : Automated fruit disease identification and crop yield estimation using AI-driven remote sensing Security Systems : Lightweight anomaly detection frameworks for video surveillance Cross-Domain Applications : Stock price prediction models, vaccine sentiment analysis, and aspect-oriented programming solutions
Joël Le Bon is a Full Professor of Marketing & Sales at the Johns Hopkins University Carey Business School, where he co-founded and serves as Executive Director of The Digital Business Development initiative. He previously held faculty positions at the University of Houston Bauer College of Business and ESSEC Business School in France, where he was a Director. Dr. Le Bon is a globally recognized expert in digital transformation, sales leadership, and marketing-sales integration, with 26 international awards highlighting his research and teaching excellence. Research Focus: Digital Transformation, Sales Leadership, CRM Technology, Competitive Intelligence, and Cross-Cultural Business Practices. Education: PhD in Marketing, MSc in Marketing & Strategy, BA in Management Science from Paris Dauphine University; Postdoctoral Scholar at Penn State's ISBM; Kellogg ITP program alumnus. Honors: 3x Johns Hopkins Dean's Award for Faculty Excellence, SMA Axcess Capon Distinguished Teacher Award, AMA Sales SIG Excellence in Teaching Award, and multiple best paper awards. Professional Engagement: Board member of the Revenue Enablement Society, Mindset Science Chief Academic Researcher, and Chair of the American Marketing Association Sales SIG (2020-2022). Dr. Le Bon's recent publications emphasize digital transformation, global sales education, and AI integration in sales practices. His awards span teaching excellence, research contributions, and lifetime achievement recognition from institutions like Marquis Who’s Who. He has consulted and delivered executive education for multinational corporations, including IBM, SAP, and Samsung Motors.
Prof. Dr. Dr. Albrecht Fritzsche is a faculty member at the School of Business, Economics and Society , Friedrich-Alexander University, Erlangen-Nuremberg (FAU). His research focuses on Information Systems , Digital Transformation , and Innovation Management , with a particular emphasis on Cyber-Physical Systems , Service Design , and Organizational Theory . Co-editor of the volume Rethinking Technology and Engineering (2023) Co-founder of the Innovating in the Open Lab book series (2020) Key contributor to the VeSiKi project on networked IT security for critical infrastructures His work explores the cultural and philosophical dimensions of technological innovation, including digital ethics , persuasive technologies , and the role of science fiction in shaping service design paradigms. Recent publications analyze value creation in digital ecosystems and the ontological foundations of paradox theory through Indian dialectics.
Yi Wang is a Professor of Embedded Systems at the Department of Information Technology, Uppsala University , Sweden. He leads research in real-time and embedded systems with a focus on modeling, analysis, and implementation of safety-critical applications. He is affiliated with the Embedded Systems Group and serves as a Principal Investigator (PI) in major research centers such as UPMARC and projects like CUSTOMER (ERC Advanced Grant), CoDeR-MP, and CERTAINTY. Research Interests: Yi Wang’s work centers on Embedded Systems Design, Real-Time Scheduling, Multicore Programming, and Model-Checking of Real-Time Systems . His research addresses fundamental challenges in timing predictability, schedulability analysis, and the verification of complex real-time systems. He has made significant contributions to the digraph real-time task model, mixed-criticality systems, and timing analysis of ROS 2 systems. His work bridges theory and practice, often resulting in deployable tools and formal methods for industrial applications. Recent Research Trends: His most recent publications (2023–2025) focus on optimizing real-time performance in ROS 2, managing parallel task graphs with resource contention, improving GPU-based inference on embedded platforms, and enhancing timing predictability in multithreaded executors. These works reflect a strong trend toward applying formal real-time theory to modern robotics, AI integration, and multicore embedded architectures. Scientific Tools and Leadership: He is a key contributor to foundational tools in real-time systems: UPPAAL – Model checking for timed automata TIMES – Schedulability analysis and code generation CATS – Compositional analysis of timed systems TIMES-Pro – Based on the digraph real-time task model Advising and Research Funding: Yi Wang has supervised numerous PhD students and postdocs. He has led or participated in multiple large-scale funded projects supported by the Swedish Research Council (VR), the Swedish Foundation for Strategic Research (SSF), and the European Commission (FP7, ERC). These include UPMARC (10-year Linnaeus center), CoDeR-MP (with ABB and SAAB), SAVE++ (with VOLVO), and CREDO. Laboratories and Research Groups: He is a core member of the Embedded Systems Group at Uppsala University and leads research within the UPMARC center, which focuses on programming models and analysis techniques for multicore architectures. His lab develops formal methods and tools to ensure correctness and timing guarantees in embedded and cyber-physical systems.
Connor Armstrong is an Assistant Professor in the Department of Mechanical Engineering at the University of Texas at Dallas, affiliated with the Erik Jonsson School of Engineering and Computer Science. He leads the Materials Engineering & Advanced Manufacturing Lab, focusing on polymer systems, additive manufacturing, and AI/ML-driven material discovery. Ph.D. in Mechanical Engineering (Georgia Institute of Technology, 2023) M.S. in Mechanical Engineering (University of Maryland, 2019) B.S. in Mechanical Engineering (University of Maryland, 2017) Postdoctoral Research in Materials Science and Engineering (University of Illinois at Urbana-Champaign, 2025) Research Interests: His work bridges advanced manufacturing techniques with intelligent systems, emphasizing autonomous experimentation and 4D printing . Key areas include photopolymer optimization , fiber-reinforced composites , and thermoset ink development for ambient-temperature applications. Scientific Awards: Grainger Distinguished Postdoctoral Fellowship (2023) Georgia Tech Tower Award (2023) NSF Student Award for Solid Freeform Fabrication Symposium (2021) Georgia Tech Presidential Fellowship (2019) GEM Fellowship (2019) He actively mentors students in research and is currently accepting both undergraduate and graduate advisees for projects at the intersection of materials science and manufacturing innovation.
