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Maroš ServátkaView profile

Professor

• Experimental Economics
• Behavioral Economics
• Public Policy Analysis
• +4 more

Maroš Servátka is a Professor of Economics at Macquarie Business School and Founding Director of the MQBS Experimental Economics Laboratory. He also serves as Deputy Director of the MBA Program. Previously, he held roles such as Economics Discipline Leader at Macquarie Graduate School of Management and Associate Professor at the University of Canterbury, where he directed the New Zealand Experimental Economics Laboratory. He is a former President of the Slovak Economic Association and holds editorial roles at the Journal of Behavioral and Experimental Economics and the Economic Science Association's Executive Committee. Maroš Servátka earned his MA in Quantitative Methods from the Warsaw School of Economics and a PhD in Economics from the University of Arizona. He held a postdoctoral position at the University of Mannheim. His research focuses on experimental and behavioral economics, with applications in charitable giving, business strategy (advertising, customer service, project planning), government policy (budget execution, public policy), stock exchange algorithms, and organizational governance. He employs experimental methods to explore topics such as honesty, trust, project management inefficiencies, and behavioral nudges to combat procrastination. He has received notable awards including the Excellence in Research Award (2021) for Prosperous Economies research and the Ronald Coase Institute Outstanding Achievement Award (2019). Maroš has advised various organizations, including government agencies and non-profits, on behavioral solutions. His funded projects include studies on windfall gains and natural resource governance. He teaches MBA students to apply experimental techniques in organizational problem-solving. He leads the MQBS Experimental Economics Laboratory and collaborates internationally, focusing on behavioral economics applications across disciplines.

• Applied Economics
• Commercial Law
• Law in Context
• +3 more

Carsten Gerner-Beuerle is a Professor of Commercial Law at University College London (UCL) since 2017, part of the Faculty of Laws. He previously held positions at the London School of Economics, King’s College London, and Humboldt University Berlin. His academic background includes degrees from Humboldt University Berlin (Ph.D., First and Second Legal State Exam), the University of Minnesota (LL.M.), and the University of London (M.Sc. in Economics). He is also a Global Distinguished Professor of Law at Notre Dame Law School and has held visiting roles at Duke University, UC Berkeley, Trinity College Dublin, and others. His research focuses on applied economics, commercial law, private law, public law, and the intersection of law with economic policies. Key areas include corporate governance, financial regulation, private international law, and the legal implications of AI. He advises a German law firm on corporate law and insolvency matters and contributed studies to the European Commission on corporate governance reforms. Current projects include a Leverhulme-funded initiative on AI regulation. He is a research member of the European Corporate Governance Institute (ECGI) and has authored influential works on topics like EU company law harmonization, directors’ liability, and algorithmic trading regulation. His interdisciplinary approach bridges legal theory with practical regulatory challenges in global markets.

• Blockchain Technology
• Distributed Systems
• Permissioned Blockchains
• +3 more

Artem Barger is a researcher specializing in blockchain technology, distributed systems, and database optimization. With affiliations primarily in blockchain development and academic research, he has contributed extensively to Hyperledger Fabric enhancements and decentralized information systems. Research Interests Optimizing state databases for blockchain platforms Byzantine Fault Tolerance in distributed networks Permissioned blockchain architectures Tokenization of real-world assets AI applications in soft skills evaluation Recent Publications Barger's work focuses on improving blockchain scalability and security through techniques like certification blocks, Patricia Merkle tries, and verifiable randomness. He has also explored tokenization applications in charity and energy sectors.

• Service-Oriented Architectures
• Cloud Computing
• Data Management
• +7 more

Professor Kyriazis Dimosthenis holds a faculty position at the Department of Digital Systems, University of Piraeus. He earned his diploma in Electrical & Computer Engineering from the National Technical University of Athens (2001) and a cross-disciplinary MSc in Techno-Economic Systems (2004). His academic rank is Professor specializing in service-oriented architectures with a focus on quality of service and workflow management. He has led European projects like BigDataStack, CrowdHEALTH, and CYBELE, addressing challenges in cloud computing, edge computing, and AI-driven solutions for healthcare, finance, and industrial sectors. His research emphasizes resilient service-oriented systems, AI explainability, and human-centric digital transformation. Notable contributions include frameworks for dynamic resource allocation in hybrid cloud/edge environments, AI applications for maritime safety, and data governance solutions for cross-sector integration. He coordinates initiatives such as the Future Internet Architecture Board and Cloud QoS&SLAs, driving advancements in federated data marketplaces and sustainable computing practices. His recent work explores Large Language Model (LLM) applications in financial decision-making, conversational AI for MLOps, and neurosymbolic systems for defect detection. He also investigates XAI methodologies, including VirtualXAI, which leverages GPT-generated personas for explainability assessment. His projects often bridge technical innovation with societal impact, such as the iHELP platform for holistic health records and SmartCHANGE for behavioral change strategies in youth health. Key themes in his publications include bias mitigation in machine learning, dynamic deployment prediction in hybrid cloud settings, and energy-efficient data spaces for mobility. He has contributed to standards like the H2020-funded IRMOS and 5GTANGO, emphasizing interoperability and fault-tolerant architectures. His work frequently intersects with EU policy frameworks, particularly in data governance and ethical AI implementation.

Tijl De BieView profile

Professor

• Foundations of Data Science
• Human-Centric Data Science
• Exploratory Data Analysis
• +2 more

Tijl De Bie is a Senior Full Professor at the University of Ghent, specializing in machine learning, data science, and their applications in bioinformatics, computational social sciences, and HR analytics. He leads the AI and Data Analytics (AIDA) research group within IDLab-ELIS. PhD in Machine Learning (KU Leuven, 2005) Worked at U.C. Berkeley, U.C. Davis, University of Southampton, and University of Bristol His research focuses on foundational aspects of data science, including fairness in AI, network embeddings, and human-centric methodologies. Recent work explores temporal network simulation, bias mitigation, and large-scale career trajectory datasets. Notable awards include an FWO Odysseus Group I grant and three ERC grants (Consolidator, Proof of Concept, Advanced). Current projects involve ethical AI frameworks and dynamic network analysis. Scientific Awards : FWO Odysseus Group I, ERC Consolidator, ERC Proof of Concept, ERC Advanced Grant He collaborates extensively in interdisciplinary research, applying machine learning to social media analysis and financial domains. His team develops open-source tools like EvalNE and Fondue for network embedding evaluation.

Jeremy Fei WangView profile

Professor

• Artificial Intelligence
• AI-Driven Recommendation Systems
• E-Commerce
• +4 more

Jeremy Fei Wang is a Professor of Computer Information Systems at Flagler College within the School of Liberal Arts and Sciences and Department of Math & Technology, also serving as Director of the China Program. He leverages extensive industry experience from senior consulting roles at Cap Gemini Ernst & Young and Meritage Technologies, where he collaborated with global clients including Procter & Gamble and General Electric on enterprise IT solutions. Dr. Wang's academic credentials include: Ph.D. in Business Information Technology from Virginia Tech (2022) M.B.A. with MIS concentration from Ohio University (1998) B.A. in Economics from Marietta College (1996) His research centers on artificial intelligence applications in business contexts, with particular expertise in AI-driven recommendation systems, e-commerce frameworks, and Web 2.0/mobile platform development. Dr. Wang investigates user trust in AI agents through affordance theory, examines AI's impact on customer relationship management, and explores localization strategies for digital platforms in international markets. His work bridges theoretical innovation with practical business implementations across consumer products, finance, and healthcare sectors. Analysis of Dr. Wang's publication history (2010-2023) reveals a consistent trajectory from foundational Web 2.0 and e-commerce studies toward cutting-edge AI research, particularly in recommendation agent design. His recent work demonstrates increasing focus on China's digital ecosystem and dual-process models for user behavior, while maintaining strong connections to enterprise systems and mobile application development. The integration of affordance theory across his publications provides a unifying framework for understanding human-AI interaction. Professional recognition includes: Honored Guest Professor appointments at three Chinese universities Cap Gemini Ernst & Young's 'Consultant of the Month' (awarded twice) Cap Gemini Ernst & Young's 'Ace Award' (top 3% globally) Phi Kappa Phi honor society membership Beta Gamma Sigma and Omicron Delta Epsilon distinctions As an educator, Dr. Wang developed and teaches courses spanning business analytics, ERP systems, mobile application development, and information security. His China Program leadership involves strategic partnership development, recruitment innovation, and family support systems for Chinese students. His industry background directly informs classroom practice through real-world case studies and hands-on technical training.

Yacine RekikView profile

Professor

• Supply Chain Management
• Operations Research
• Digital Transformation
• +4 more

Yacine Rekik is a Full Professor of Decision Sciences at ESCP Business School's Paris campus. He holds a PhD in Industrial Engineering from École Centrale Paris and an HDR from INSA Lyon. Previously, he served as a Research Associate at the University of Cambridge and spent 15 years as a Professor at emlyon business school. Primary roles: Academic leadership in supply chain management and operations research Affiliations: ESCP Business School, ECR Community His research focuses on digital transformation of supply chains, RFID technology applications, omnichannel strategies, and inventory inaccuracy solutions. Notable contributions include data-driven models for inventory optimization and blockchain-based agricultural cooperatives. His work bridges theoretical frameworks with practical industry applications. Recent articles analyze energy market regulations, grocery retail promotions' impact on inventory accuracy, and cooperative formation in agriculture. He emphasizes sustainability in transportation and integrates machine learning for supply chain efficiency. No scientific awards listed, but his extensive publication record reflects scholarly impact. Advising activities and grants are not detailed here, but his HDR and research at top institutions indicate active involvement in doctoral supervision.

• Construction Technologies
• Project Management
• Construction Management
• +5 more

Assoc. Prof. Dr. Onur Behzat Tokdemir is an Associate Professor in the Civil Engineering Department at Istanbul Technical University (ITU), with prior affiliation at Middle East Technical University (METU). His expertise spans Construction Technologies, Project Management, and Construction Management, with a focus on integrating Artificial Intelligence (AI) and Machine Learning (ML) into infrastructure development. He holds a Ph.D. from Illinois Institute of Technology and has extensive industry experience in project management roles with firms like Renaissance Holding and Qatar Project Management. Education: B.Sc. from METU (1990-1995), M.Sc. from Illinois Tech (1995-1997), Ph.D. from Illinois Tech (1997-2003). His research emphasizes AI-driven solutions for construction safety, cost prediction, and digital twin applications. Notable projects include the EU-funded 'DIGITWINS4CIUE' and the strategic tender decision support system leveraging ML. Awards include the ITU Academic Performance Publication Award (2022-2024) and METU's Prof. Dr. Mustafa N. Parlar Award (2019). He has advised over 15 theses on topics like AI in safety assessment, labor efficiency prediction, and post-disaster housing frameworks. Active memberships include the American Society of Civil Engineers (ASCE) and the Chamber of Civil Engineers.

Elena EspositoView profile

Professor

• Communication theory
• Systems theory
• Digital communication
• +5 more

Elena Esposito is a Full Professor at the Department of Political and Social Sciences, University of Bologna, and at the Faculty of Sociology, University of Bielefeld. She holds the scientific-disciplinary sector GSPS-06/A (Sociology of cultural and communicative processes). Her work bridges systems theory, digital communication, and algorithmic futures, with a focus on artificial intelligence, prediction mechanisms, and media sociology. She has received prestigious fellowships from institutions like the ERC, Wissenschaftskolleg Berlin, and Columbia University. PhD in Sociology (1990, University of Bielefeld) Habilitation (2001, University of Bielefeld) National Scientific Qualification (2013, Italy) Degree in Philosophy (1987, University of Bologna, summa cum laude) Degree in Sociology (1983, University of Bologna, summa cum laude) Esposito's research spans algorithmic prediction, artificial communication, digital media, and systems theory. Her work examines how algorithms shape social intelligence in insurance, medicine, and policing, the paradoxes of contingency in financial markets, and the societal implications of virtuality. She connects Niklas Luhmann's theoretical frameworks to contemporary issues like AI ethics and pandemic-era social systems. Her recent publications emphasize AI's role in constructing unpredictable futures, the social management of algorithmic opacity, and the transformation of risk perception in digital societies. She has authored 13 books and over 100 peer-reviewed articles, exploring topics from media memory to financial forecasting. ERC Advanced Grant (2018): €2.08M for algorithmic prediction studies Volkswagen Foundation Grant (€1.5M) for U3B project Leverhulme Trust funding for international network on value performances Esposito serves on editorial and advisory boards for journals like Sociologica and organizations including the Weizenbaum Institute. She directs the FAIR project on AI implications and co-leads initiatives like DEMOPE (Democracy under Pressure) and CRC 1567 on Virtual Worlds.

• Data Privacy
• Cyber Security
• Cloud Security
• +5 more

Professor Xun Yi is a faculty member at RMIT University's School of Computing Technologies, specializing in cybersecurity, data privacy, and distributed computing. His research focuses on privacy-preserving technologies in cloud systems, blockchain applications, federated learning, and secure communication protocols. He has published over 150 papers in top-tier journals and conferences, including IEEE Transactions on Dependable and Secure Computing. Since 2014, he has served as an Associate Editor for the IEEE Transactions on Dependable and Secure Computing, and has organized major events like the Australasian Information Security Conference (AISC) in 2015 and 2016. Professor Yi actively supervises PhD and Master's research projects, focusing on topics like secure IoT systems, privacy-aware machine learning, and blockchain-enabled frameworks. His work emphasizes practical solutions for real-world challenges in data security and privacy. Research Interests: Data Privacy, Cyber Security, Cloud Security, Wireless/Mobile Security, Applied Cryptography Blockchain-based Systems, Federated Learning, Privacy-Preserving AI Recent Contributions: Developed frameworks for secure data aggregation in smart grids and healthcare systems Advanced techniques for privacy-preserving federated learning and graph neural networks Contributed to standards for secure authentication in vehicular networks (VANETs) Supervision: Open to mentoring students in cybersecurity, privacy-enhancing technologies, and IoT security.

Selin AhipasaogluView profile

Professor

• Operational Research
• Convex Optimization
• Robust Optimization
• +5 more

Prof. Selin Damla Ahipasaoglu is a Professor in Operational Research at the University of Southampton's School of Mathematical Sciences . She serves on the management team of the UKRI CDT SustAI (Artificial Intelligence for Sustainability) as Senior Tutor and Co-Lead for the Transportation and Logistics Theme . Her work bridges mathematical optimization with practical applications in sustainability, finance, and transportation systems. Research Interests : Convex Optimization Robust Optimization Discrete Choice Theory Experimental Design Machine Learning Current Research : Focused on robust optimization and its applications in discrete choice modeling, portfolio optimization, and transportation systems. She explores theoretical frameworks alongside real-world implementations, particularly through interdisciplinary projects like the UKRI CDT SustAI. Teaching : In the 2025/2026 academic year, she teaches MATH3017: Mathematical Programming and MATH2013: Operational Research II . She supervises PhD students in Mathematical Sciences, including Kexin Lai, Samuel Jericho Ward, and others.

Yuanyuan GuView profile

Associate Professor

• Health Economics
• Economics of Ageing
• Choice Modelling
• +7 more

Yuanyuan Gu is an Associate Professor at Macquarie University's Centre for the Health Economy. His expertise spans health economics, aging, choice modeling, and econometrics, with a focus on preferences and decision-making in healthcare systems. He leads the health preference research stream and advises on health technology assessments. He has secured over A$14 million in funding, including a Marie Skłodowska-Curie Fellowship. Education: PhD in Economics (UNSW, 2011), MCom (Hons) in Economics (UNSW), BSc in Statistics (Fudan University). Research Interests include improving healthcare quality through preference analysis, cost-effectiveness studies, and policy-relevant research. Recent projects address aged care financing, patient preferences for treatments, and precision medicine applications. Key Awards: MQBS Research Impact Prize (2023, 2025), Centre for Health Economy Publication Prize (2023). Advising & Grants: Supervises 6 current PhD students (e.g., Zobaida Ahmed Piu on oral contraceptives, Han Cheng on income inequality and health) and advises on PBAC evaluations. Active in editorial roles for PharmacoEconomics and Journal of Hospital Management and Health Policy . Labs/Teams: Collaborates on projects like sensory support interventions for dementia patients and outcomes-based care evaluations for vulnerable populations.

Ronghong HuangView profile

Senior Lecturer

• Behavioural Corporate Finance
• Corporate Investment
• Capital Structure
• +2 more

Dr. Ronghong Huang is a Senior Lecturer in Finance at the UQ Business School , part of the Faculty of Business, Economics and Law at The University of Queensland. Prior to his academic career, he worked for four years in a regulatory cost of capital advisory role. Research Focus: Behavioural corporate finance, capital structure decisions, cost of capital optimization, and regulatory impact on investment efficiency Education: PhD from The University of Queensland, focusing on managerial overconfidence and corporate finance policies Research Contributions Dr. Huang's work explores the intersection of behavioral finance and corporate decision-making, particularly examining: CEO contract durations and acquisition behavior Market factor validation through data mining Economic uncertainty and stock return patterns Debt maturity strategies influenced by executive psychology His research has been published in top-tier journals like the Journal of Corporate Finance and Pacific-Basin Finance Journal . Awards Best Paper Award, 6th Behavioural Finance and Capital Markets Conference Supervision Currently supervising PhD students on topics including: Firm-level political risks and executive compensation Trading frictions in anomaly profitability Equity term structure effects Private equity strategies

• Artificial Intelligence (AI) in Financial Markets
• Large Language Models (LLMs) in Finance
• Reinforcement Learning for Portfolio Management
• +3 more

Dr. Manuel Nunes is a Lecturer in Banking and Finance and Deputy Director of the Centre for Digital Finance at Southampton Business School, University of Southampton. His research focuses on AI-driven financial technologies, including reinforcement learning for portfolio management, large language models in finance, and explainable AI for financial markets. He holds a PhD in Computer Science applied to Financial Markets from the University of Southampton, with prior PhDs in Engineering and an MBA in Financial Studies from the University of Nottingham. His current research includes enhancing asset pricing models with LLMs and developing a dynamic vehicle booking system for port logistics funded by UKRI. Education: PhD in Computer Science (University of Southampton), PhD in Engineering (University of Nottingham), MBA in Financial Studies (University of Nottingham), 5-year Engineering degree (University of Porto), MSc in Finance (Nova University of Lisbon). Research interests span AI in finance, fixed income markets, and fintech innovation. He is actively supervising PhD students in multidisciplinary projects involving finance and computer science, emphasizing industry collaboration. Awards include Fellow of the Higher Education Academy (FHEA). Teaching responsibilities include modules on Finance with Python, Portfolio Theory, and Asset Pricing. Current projects include work on cryptocurrency exchange models and reinforcement learning applications in bond portfolios.

David Huckleberry GutmanView profile

Assistant Professor

• Continuous Optimization Theory
• Large-Scale Optimization
• Optimization over Manifolds
• +3 more

David Huckleberry Gutman is an Assistant Professor in the Department of Industrial & Systems Engineering (ISEN) at Texas A&M University. He holds a Ph.D. in Mathematical Sciences from Carnegie Mellon University (2019), an M.S. in Mathematics from Tulane University (2010), and a B.S.B.A. in Finance & Accounting from Georgetown University (2008). Education: Ph.D. in Mathematical Sciences, Carnegie Mellon University, 2019 M.S. in Mathematics, Tulane University, 2010 B.S.B.A. in Finance & Accounting, Georgetown University, 2008 His research focuses on continuous optimization theory , emphasizing large-scale optimization methods and optimization over manifolds . He has developed innovative algorithms such as tangent subspace descent for Riemannian manifolds and advanced proximal gradient methods with convergence guarantees. Key awards include the 2023 NSF CAREER Award and the 2022 INFORMS Optimization Society Young Researcher Prize (jointly with Nam Ho-Nguyen). His work bridges theoretical optimization with practical machine learning and engineering applications. Advising: Currently mentoring PhD students Allan Gurwicz, George Lobo, and Leandro Maia. Previously held positions at Texas Tech University (2019-2023) and conducted research at Bosch Research and IBM. Labs/Teams: Leads an active research group at Texas A&M exploring optimization algorithms for modern computational challenges, though no open PhD spots are available at this time.