Gernot Müller is a Professor of Economics at the School of Business and Economics, University of Tübingen. His research focuses on international macroeconomics, monetary policy, fiscal policy, and economic networks, with a particular emphasis on how news, expectations, and structural shocks propagate through economies. Current Affiliation: Professor, University of Tübingen Research Areas: Monetary policy, fiscal policy, climate economics, economic networks, conflict economics Recent publications explore topics such as the economic impact of war, tariff shocks in production networks, green transition policies, and the role of expectations in business cycles. His work appears in journals like the American Economic Review , Journal of Monetary Economics , and European Economic Review . Active collaborations with researchers across Europe and the U.S. highlight his interdisciplinary and global approach. Contact: gernot.mueller@uni-tuebingen.de
Dr. Jie Gao is an Assistant Professor at the School of Information Technology , Carleton University, with cross-appointments at Dalhousie University (Adjunct Faculty, 2024) and Carleton University (2025). He holds a Ph.D. in Electrical and Computer Engineering from the University of Alberta (2014) and has held postdoctoral and research associate positions at Ryerson University (2017-2019), University of Waterloo (2019-2020), and Marquette University (2020-2022). His research focuses on machine learning for communications/networking , 6G wireless networks , cloud/multi-access edge computing , IoT/industrial IoT solutions , and network virtualization/digital twins . Research Leadership: Co-investigator on projects related to AI-assisted network slicing, digital twin-driven resource allocation, and integrated satellite-terrestrial networks Led work on energy-efficient UAV-assisted edge computing (IEEE Best Land Transportation Paper Award 2024) Professional Roles: Senior Member, IEEE Lead Associate Editor, IEEE Access Vehicular Technology Society Section (2020-present) Associate Editor, Springer Peer-to-Peer Networking and Applications (2020-present) IEEE Vehicular Technology Society Young Professional Ambassador (2024) Notable Contributions: Authored/co-authored books on Intelligent Computing and Communication for the Internet of Vehicles (Springer, 2023) and Connectivity and Edge Computing in IoT (Springer, 2021) Holds patents on medium access control methods (US Patents 2022, 2024) Received multiple IEEE service awards (2018-2024)
Dr. Zhengyu Lin is a Reader in Power Electronics at Loughborough University's Wolfson School of Mechanical, Electrical and Manufacturing Engineering, affiliated with the Centre for Renewable Energy Systems Technology (CREST). Previously, he held a Lecturer position at Aston University for over five years and worked in UK industry for six years, including roles at Sharp Laboratories of Europe and Nidec Control Techniques. His academic journey includes a Ph.D. from Heriot-Watt University (2004), an MSc from Zhejiang University (2001), and a BSc from Zhejiang University (1998). Lin's research focuses on advancing power electronics and renewable energy systems, particularly in DC microgrid control, grid resilience, and energy storage. His work addresses challenges in power sharing accuracy, fault detection, and infrastructure robustness under severe weather or disasters. He has contributed to policy analysis for EV adoption in South Asia and innovative solutions for wireless power/data transfer in EV charging. Key achievements include the EPSRC UKRI Innovation Fellowship (2018-2021) and over 80 peer-reviewed publications. His research bridges academic theory with industrial applications, emphasizing sustainable energy transitions and smart grid technologies. Education: Ph.D. (Heriot-Watt), MSc/BSc (Zhejiang University) Awards: EPSRC UKRI Innovation Fellowship Research Themes: DC Microgrids, Grid Resilience, Renewable Energy Integration Labs: Centre for Renewable Energy Systems Technology (CREST)
Valentina Breschi is an Assistant Professor in the Control Systems Group at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). She holds a Ph.D. from IMT School for Advanced Studies Lucca, with postdoctoral and junior faculty experience at Politecnico di Milano. Her research focuses on data-driven control, jump model learning, meta-learning for system identification, and human-centered policy design for mobility systems. She contributes to UN Sustainable Development Goals related to sustainable infrastructure and innovation. Education: B.Sc. in Electronic and Telecommunication Engineering (University of Florence, 2011) M.Sc. in Electrical and Automation Engineering (University of Florence, 2014) Ph.D. in Control Systems (IMT School for Advanced Studies Lucca, 2018) Research Interests: Her work spans data-driven control methodologies, including LPV control, predictive control, and ethical frameworks for policy design. She explores applications in sustainable mobility, energy systems, and healthcare, emphasizing fairness and social impact. Labs/Teams: She is part of the Control Systems Group, collaborating on projects like the CONSIDER study and the design of fair-MPC frameworks. Her work integrates theoretical control principles with real-world applications in smart systems and social networks.
Ingrid Moerman is a part-time Professor at Ghent University and a staff member at the Internet Technology and Data Science Lab (IDLab), a core research group of imec embedded within Ghent University and the University of Antwerp. She coordinates mobile and wireless networking research and leads a team of over 30 researchers at Ghent University, with extensive involvement in European and national funding initiatives. She received her Electrical Engineering degree (1987) and Ph.D. (1992) from Ghent University. Her research spans collaborative networks, cognitive radio, software-defined radio, IoT, LPWAN, and high-density wireless access, emphasizing experimentally-supported development of next-generation wireless systems with practical implementations in spectrum management and real-time control. Recent publications (2024-2025) reveal a strong pivot toward AI-integrated wireless networking, featuring OFDMA scheduling innovations, Wi-Fi 6/7 interference mitigation, and time-sensitive networking for industrial applications. Key trends include 5G/6G convergence, vehicular communication enhancements, and digital twin frameworks for network observability, reflecting her focus on mission-critical industrial use cases. Her accolades include: 9 Best Paper Awards 2 FWO Prizes (Research Foundation - Flanders) IMEC Prize of Excellence 2001 MSc Thesis Award (as promoter) Best Demo/Exhibit Award at ICT 2013 DARPA Spectrum Collaboration Challenge Prize ($750,000) She has coordinated major EU projects (FP7/H2020: CREW, WiSHFUL, eWINE, ORCA) with industry partners, securing substantial funding for experimental wireless research. Her grant portfolio emphasizes collaborative innovation in spectrum sharing and neutral-host architectures for multi-operator environments. At IDLab, she directs advanced wireless testbeds supporting real-world validation of technologies like openwifi and White Rabbit, with active experimentation in time-sensitive networking and spectrum collaboration for industrial IoT deployments.
Prof. Tanya Bondarouk is a distinguished academic affiliated with the Digital Society Institute and Faculty of Behavioural, Management and Social Sciences at the University of Twente. Her research focuses on Human Resource Management (HRM), electronic HRM systems, and the impact of disruptive technologies on work environments. She holds leadership roles including Board Member of the National Network of Female Professors (Landelijk Netwerk Vrouwelijke Hoogleraren). Her academic contributions span over 250 publications, including influential works on AI in HRM, open innovation, and gig economy challenges. Notable awards include the Best HRM Scientist in The Netherlands (2018) and the Inspiration Award (2019). Research interests: Technology-human interaction in workplaces, HRM strategies for innovation, and digital transformation in organizations. Recent articles analyze AI-driven recruitment, generational differences in tech engagement, and algorithmic management dilemmas. Prof. Bondarouk actively engages in academic networks, organizing conferences like the 38th EGOS Colloquium (2022), and provides expert commentary on digital labor platforms and employer branding strategies. Her work bridges theoretical HRM frameworks with real-world organizational challenges.
Ini Kong is a PhD candidate at Delft University of Technology's Faculty of Technology, Policy and Management (TPM), within the Engineering Systems and Services Department. She is affiliated with the Information and Communication Technology group. Her research focuses on designing quantum-secure Public Key Infrastructure (PKI) systems and developing growth-stage models to guide organizations toward a controlled transition to quantum-safe futures. Ini holds an MSc in Environment and Society studies from Radboud University (Netherlands) and a BA (Honors) in Political Science and Sociology from the University of Toronto (Canada). During her MSc, Ini conducted a research internship at Provincie Gelderland’s Energy Transition department, contributing to the Wijk van de Toekomst program through her thesis on knowledge management systems for local energy initiatives, which proposed governance models for municipalities and stakeholders. Her expertise spans ICT governance, digital trust, and transition management in both public and private sectors. Her research interests emphasize practical frameworks for organizational readiness in adopting quantum-safe technologies, government roles in steering these transitions, and policy recommendations addressing implementation challenges. No scientific awards have been explicitly mentioned. As a PhD candidate, her advising and grant information are not detailed in the provided texts, though her work aligns with national cybersecurity initiatives. She is part of the Information and Communication Technology research group at TPM.
Spyros Galanis is a Professor in Economics at Durham University Business School and Director of the Durham Research in Economic Analysis and Mechanisms (DREAM) Research Centre. Previously, he served as Associate Professor and Head of the Department of Economics at City, University of London, and held academic positions at the University of Southampton. He earned his PhD from the University of Rochester (2008), MSc from the University of Warwick (2002), and BSc from Athens University of Economics and Business (2001), all in Economics. His research focuses on decision theory, game theory, experiments, and finance, particularly examining how uncertainty, information, and bounded perception influence decision-making. Key areas include the value of information in speculative trade, prediction markets' efficiency, and the impact of unawareness on economic behavior. He leads the ESRC-funded grant (2021–2024) on prediction markets' forecasting efficiency and collaborates with the Competition and Markets Authority (CMA) through the CMA Durham Partnership. Notable publications include Information Aggregation Under Ambiguity (Review of Economic Studies, 2024) and Financial Complexity and Trade (Games and Economic Behavior, 2018). His work bridges theoretical insights with experimental and practical applications, including advising on crypto investments and organizing academic conferences like the Makris Symposium in Economic Theory. Scientific recognition includes the Jaffray Lecture (2015). He supervises PhD students and teaches advanced microeconomics, international trade theory, and financial economics. His research teams actively engage in interdisciplinary projects, such as applying group testing strategies for pandemic control and exploring blockchain's economic implications.
Justin Johnson is the Deane W. Malott Professor of Management at Cornell University's Samuel Curtis Johnson Graduate School of Management. He specializes in industrial organization, antitrust economics, and business strategy, with a focus on high-tech markets, algorithmic competition, and digital platforms. Johnson teaches Business Strategy to Executive MBA students and has been recognized with multiple teaching excellence awards. His research addresses topics like algorithmic collusion, platform design, and merger analysis, often collaborating with global regulatory bodies such as the US FTC and EU Competition Directorate. He holds a PhD from MIT (1999) and a BA from the University of Florida (1994). Education PhD in Economics, Massachusetts Institute of Technology, 1999 BA in Economics, University of Florida, 1994 Research Interests Johnson's work applies economic theory and game theory to analyze firm strategies in evolving markets, particularly in high-tech sectors. Key themes include antitrust issues in digital platforms, pricing algorithms, and the impact of mergers on market competition. His research often intersects with policy, advising governmental agencies on antitrust enforcement and regulatory frameworks. Editorial Roles Past editor, Journal of Industrial Economics Past editor, International Journal of Industrial Organization Associate editor, RAND Journal of Economics Professional Engagements Consults with US Department of Justice, EU Directorate General for Competition, and UK Competition Authority on antitrust matters. Active in executive education, emphasizing strategic decision-making in dynamic markets.
Sijia Yang is an Associate Professor at the School of Journalism and Mass Communication at the University of Wisconsin-Madison . His research focuses on message effects and persuasion in digital media, particularly in public health and science communication. He employs experimental, computational (e.g., causal machine learning, multimodal analysis), and community-engaged methods to address challenges in health communication interventions. Ph.D. in Communication: Annenberg School for Communication, University of Pennsylvania (2019) M.A. in Communication: University of Illinois at Urbana-Champaign (2012) B.A. in English Language and Literature: Renmin University of China (2010) His current research explores three key areas: (1) moralization/politicization of health issues and intervention design, (2) causal machine learning for evaluating multimodal messages, and (3) leveraging AI for pro-social messaging in underserved communities. His work bridges computational methods with societal impact, emphasizing ethical considerations and practical applications. Recent articles highlight his contributions to topics like cannabis warning labels, misinformation correction via TikTok, and AI-driven health chatbots. Despite no explicitly listed awards, his active research portfolio reflects significant scholarly engagement in health communication and digital media studies. His advising and grants focus on collaborative projects with rural communities and under-resourced populations, though specific grants are not detailed here. No lab or team affiliations are mentioned in the provided texts.
Andrea Boggio serves as Professor of Legal Studies in Bryant University's College of Arts and Sciences, Department of History and Social Sciences, teaching graduate and undergraduate courses in business law, health law, and international law. He is currently on sabbatical for 2025-26 as Fulbright-Lund University Distinguished Scholar in Public International Law at Sweden's Lund University, fostering US-Sweden human rights research collaboration. His academic credentials include: JSD, Stanford Law School JSM, Stanford Law School LLD, Università Cattolica del Sacro Cuore, Italy Professor Boggio's research pioneers the human right to science framework, examining legal-ethical dimensions of biosciences through lenses of science diplomacy, innovation policy, and global health governance. His seminal 2024 Oxford University Press book The Human Right to Science: History, Development and Normative Content establishes foundational principles for applying human rights law to emerging technologies. Current work investigates gene editing regulation, biobank governance, and scientific freedom during global health emergencies, emphasizing transnational policy coherence and equitable benefit-sharing mechanisms. Analysis of his recent publications reveals a critical trajectory connecting international human rights instruments with contemporary scientific challenges, particularly in biotechnology regulation where he advocates for human rights-based approaches over purely ethical frameworks. His scholarship demonstrates increasing focus on operationalizing the right to science through indicator development and model legislation. Key recognitions include: Santander Faculty Research Collaboration Award (2017) Fulbright-Lund University Distinguished Scholar (2025-26) Multiple MERIT Awards (2009-2015) Summer Research Stipends (2013-2015) As Associate Editor of Human Reproduction (European Society of Human Reproduction publication) and Journal of Legal Studies Education , he shapes scholarly discourse while serving on the Massachusetts Science & Technology Policy Fellowship Advisory Board, College Board's CLEP Business Law Committee, and as GESDA Foundation consultant. A New York Bar member, he maintains active legal practice alongside academia. His Faculty Fellowship at Bryant's Center for Health and Behavioral Sciences drives interdisciplinary integration of legal perspectives into health sciences research, particularly through science diplomacy initiatives examining how human rights frameworks can guide international scientific collaboration during geopolitical tensions.
Liuba Shrira is a Professor of Computer Science at Brandeis University, affiliated with the Michtom School of Computer Science and the Benjamin and Mae Volen National Center for Complex Systems. Her research focuses on distributed systems, storage systems, blockchain technology, concurrent programming, and system architectures. She holds a Ph.D., M.S., and B.S. from the Technion – Israel Institute of Technology. Her work emphasizes reliable and highly available systems, including innovations in snapshot management, transactional memory, and adversarial cross-chain commerce. She has been recognized with awards such as the ACM Distinguished Scientist (2009), Lady Davis Fellowship (2010-2011), and a Best Paper Award (2020). Her research has been supported by grants from the National Science Foundation and other institutions. Recent publications highlight advancements in optimistic concurrency control, blockchain interoperability, and modular past-state systems. Shrira has also contributed to middleware design and distributed computing frameworks, with applications in both academic and industry settings.
Tara Javidi holds the Jerzy (George) Lewak Endowed Chair and is a Professor in the Department of Electrical and Computer Engineering and Halicioglu Data Science at the University of California San Diego (UCSD). She leads multiple initiatives, including serving as Founding CTO of KavAI, Co-Director of the Center for Machine Intelligence, Computing and Security, and Co-Principal Investigator (CoPI) of the NSF AI Institute TILOS. Her research focuses on stochastic analysis, design, and control of information systems, emphasizing active learning, decentralized optimization, and wireless networks. Key areas include information acquisition/utilization, stochastic control, and AI-driven communication solutions. Her work bridges theoretical foundations and practical implementations, such as drone systems for information gathering (via detecdrone.ucsd.edu) and optical data center networking. Notable contributions include end-to-end scheduling for all-optical data centers and hybrid wireless-optical architectures. Javidi is an IEEE Fellow and has received significant grants, including leading UCSD’s Schmidt AI in Science Postdoctoral Fellowship program. She actively collaborates with industry and academia, with a focus on next-generation wireless networks and decentralized systems. Education: Ph.D. in Electrical Engineering (implied from title). Affiliations: IEEE Journal of Selected Areas in Information Theory (Editor-in-Chief), CALIT2, CNS, and TILOS. Grants: NSF AI Institute TILOS ($20M over 5 years), Schmidt AI Fellowship program. Her research group emphasizes both theoretical rigor (e.g., sequential hypothesis testing) and practical testing, with applications in service drones, cognitive networks, and federated learning. Recent articles highlight advancements in optical networking, secure communication, and distributed learning protocols. Awards: IEEE Fellow, Jerzy Lewak Chair. Labs/Teams: Center for Machine Intelligence, TILOS Institute, KavAI, and UCSD’s AI in Science initiatives.
Professor Andrew Bayliss is a Professor in Psychology at the University of East Anglia's School of Psychology, where he serves as Social Cognition Research Group Lead and UEA UOA4 Psychology REF coordinator. He joined UEA in 2011 after completing his PhD at Bangor University and holding postdoctoral fellowships with the ESRC, Leverhulme Trust, and University of Queensland. Undergraduate Degree: Bangor University PhD: Bangor University Postdoctoral Fellowships: ESRC, Leverhulme Trust, University of Queensland His research spans social cognition, attention-action interactions, and individual differences, with specific focus on face perception, eye gaze processing, and objects in social contexts. Utilizing methodologies including eye tracking, motion capture, EEG, and fMRI, his work examines how social cues guide attention and influence behavior. Current projects investigate gaze understanding development, interpersonal agency, and autism interventions using natural scenes. Analysis of his recent publications reveals a strong emphasis on social attention mechanisms, particularly gaze leading phenomena, interpersonal distance effects, and neural correlates of shared attention. His work increasingly integrates autism research with social cognition paradigms while maintaining core investigations into attentional orienting and agency perception. Bayliss actively contributes to the academic community through editorial roles at Psychological Review and Psychonomic Bulletin and Review, peer review activities, and consultancy work including the Social Neuroscience of Cinema Attendance project. He maintains international collaborations, notably with Paris Nanterre University. As Social Cognition Research Group Lead, he oversees a dynamic team investigating the neural and cognitive mechanisms underlying social interactions. His lab employs multimodal approaches to study real-time social processing, with recent work expanding into human-robot interaction and pandemic-related social adaptations.
Kun An is a Professor at the Department of Traffic Information and Control Engineering within the College of Transportation Engineering at Tongji University. She has previously held academic positions at Monash University (Senior Lecturer, 2018–2019; Lecturer, 2016–2018) and conducted postdoctoral research at the University of Illinois at Urbana-Champaign (2015–2016) and The Hong Kong University of Science and Technology (2014–2015). Her academic journey includes a PhD in Civil Engineering from HKUST (2014) and a Bachelor's degree from Tongji University (2009). PhD: Civil Engineering, The Hong Kong University of Science and Technology (2014) Bachelor's: Transportation Engineering, Tongji University (2009) Dr. An specializes in intelligent transportation systems, focusing on optimizing complex traffic networks, characterizing traveler behavior in stochastic environments, and advancing electric vehicle sharing infrastructure. Her research spans urban transit planning, carsharing logistics, battery electric bus deployment, and real-time traffic signal optimization, with applications to mitigate rail disruptions and enhance multimodal connectivity. Her publications emphasize solving transport challenges through stochastic programming, game theory, and behavioral analysis. Key themes include autonomous vehicle integration, demand uncertainty modeling, and sustainable mobility solutions. Awards include the Hong Kong PhD Fellowship and multiple best paper recognitions. Hong Kong PhD Fellowship (2010–2014) TRBADB30 Best Paper Nomination (2014) Best Paper at 18th Hong Kong Transportation Annual Meeting (Second Author, 2013)
