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Professor Heiko Spallek is Head of School and Dean at the University of Sydney’s Sydney Dental School, leading the school’s integration with the Faculty of Medicine and Health. He also serves as Academic Lead for Digital Health and Health Service Informatics at the faculty level. His research focuses on advancing dental informatics, teledentistry, and evidence-based practice, while advocating for improved oral health policy and public health initiatives. He holds roles including director at Community Connections Australia and membership in the Charles Perkins Centre. Education: DMD, Dr. med. dent., MSBA(CIS), FACD, FAIDH Leadership: Oversees Sydney Dental School’s academic and clinical programs, emphasizing interprofessional education and digital health innovation. Research interests include leveraging big data and machine learning in dentistry, improving access to oral healthcare through teledentistry, and addressing systemic issues in dental education and policy. He has led projects on laser dentistry applications, dental caries prevention, and healthcare workforce regulation. Notable contributions include the OpenWide conference series, the BigMouth dental data repository, and advocacy for equitable dental funding in Australia. Grants include initiatives on oral hygiene in aged care and analysis of healthcare advertising perceptions. Media engagements highlight his role in public discourse on dental access and policy, including commentary on Australia’s dental crisis and aged care reforms. He actively promotes interdisciplinary collaboration through platforms like the Dental Informatics Online Community. Labs/Teams: Directs the Sydney Dental School’s research programs in informatics and public health, collaborating with national and international networks such as the National Dental PBRN.

• Dental Informatics
• Teledentistry
• Oral Health Policy
• +4 more

Jan Akmal is an Assistant Professor at Aalto University, holding dual affiliations in the Department of Energy and Mechanical Engineering and the Materials to Products group. His research specializes in additive manufacturing (AM), focusing on defect detection, smart materials, and 4D printing applications. He leads the AIM-Zero project (2023–2026), exploring AI-driven zero-defect AM processes. Akmal has received the Aalto Doctoral Incentive Scholarship (2023) and an Honorary Award (2023). He serves on editorial boards for Frontiers in Manufacturing Technology and Frontiers in Mechanical Engineering , and chairs the Finnish Rapid Prototyping Association (FIRPA). Key research areas include AI-based defect detection in metal AM, self-sensing components, and hybrid materials for dynamic displays. He collaborates globally on topics like optical tomography in powder bed fusion and medical AM applications. His work addresses sustainability, industrial adoption of AM, and legal frameworks for military logistics. Akmal has authored 24 publications and contributed to datasets on AM inaccuracies and defect classification, emphasizing practical applications and industry integration.

• Additive Manufacturing
• 3D Printing Technology
• Defect Detection
• +5 more

Simon Dobson is a Professor of Computer Science and Deputy Head of the School of Computer Science at the University of St Andrews. His research focuses on complex systems, sensor analytics, computational tools for simulation, and data analytics. He leads grants exceeding EUR30M, including a £5M EPSRC-funded programme in Sensor Systems Software. He is a Fellow of the Royal Society of Edinburgh (2020) and advises the Scottish government. Education: BSc (University of Newcastle), DPhil (University of York), both in Computer Science. Professional: Chartered Engineer, Fellow of the British Computer Society. Research Interests: Complex systems, network science, higher-order networks, epidemiological modeling, and sensor data integration. Teaching: CS4203 (Computer Security), CS5728 (Complex Systems Modelling). Supervises PhD/MSc projects. Awards: Includes RSE Fellowship, BCS Fellowship, and multiple leadership roles in conferences and committees.

• Complex Systems
• Sensor Systems
• Data Analytics
• +3 more

Martin Volk is a Full Professor of Computational Linguistics at the University of Zurich, with a dual affiliation to the Department of Informatics since 2019. He holds a PhD from the University of Koblenz and has held academic positions at institutions including Stockholm University (part-time from 2008-2011), Zurich University of Applied Sciences, and the University of Georgia. His research focuses on grammar engineering, machine translation evaluation, multilingual text analysis, and cross-language information retrieval. Education : Born in Cochem, Germany Studied Computer Science and Computational Linguistics at EWH University, Koblenz Master's in Artificial Intelligence at the University of Georgia (Fulbright Scholar) PhD in Computational Linguistics from the University of Koblenz Research Interests : His work emphasizes data-driven NLP methods, including corpus-based approaches, parsing technologies, and the application of machine learning to historical and multilingual texts. Key focuses include: Machine translation systems and evaluation frameworks Grammar testing environments (e.g., GTU) OCR and digitization of historical documents (e.g., Gothic script) Development of parallel corpora for linguistic research Projects : SMULTRON: Multilingual parallel treebank project Bullinger Digital: Historical document digitization initiative Text+Berg: Digital Humanities project for alpine textual heritage EU-funded MuchMore (cross-language medical IR) Grants & Collaborations : Recipient of grants from the Swiss National Science Foundation, EU projects, and industry partnerships (e.g., Siemens, Xerox). His work integrates academic and industrial perspectives in NLP tool development. Labs & Teams : Leads research teams in the Institute of Computational Linguistics at UZH, focusing on projects like the Zurich Parallel Corpus Collection and MODERN (modeling discourse for MT).

• Computational Linguistics
• Machine Translation
• Natural Language Processing
• +5 more

Alan Marco is an Associate Professor at the Jimmy and Rosalynn Carter School of Public Policy within Georgia Tech's Ivan Allen College of Liberal Arts. His research focuses on innovation policy, patent economics, and intellectual property strategy. Previously, he served as Chief Economist at the U.S. Patent and Trademark Office (USPTO), where he co-created PatentsView.org and led the Cancer Moonshot Patent Challenge. Research interests span antitrust regulation, patent valuation, technology markets, and empirical legal studies. Marco holds a Ph.D. in economics from UC Berkeley and a B.A. from Skidmore College. Publications demonstrate expertise in patent analytics, with recent work examining strategic citation behaviors, FRAND royalty calculations, and links between antitrust enforcement and innovation. Research methodologies emphasize large-scale data analysis of USPTO records, litigation outcomes, and market transactions.

• Innovation Policy
• Patent Economics
• Intellectual Property
• +2 more

Steven Siciliano is a Professor and NSERC/FCL Industrial Research Chair in In Situ Remediation and Risk Assessment at the University of Saskatchewan's College of Agriculture and Bioresources. He leads the CREATE Human and Ecological Risk Assessment Program. His expertise spans soil toxicology, greenhouse gas dynamics in polar ecosystems, and nitrogen cycle interactions in contaminated environments. Education: Ph.D. in Toxicology, University of Saskatchewan B.Sc. in Biochemistry, Concordia University Research Interests: His work focuses on human-soil interaction dynamics, including soil pollution impacts on human health (e.g., PAH toxicity via soil ingestion) and ecosystem resilience (e.g., nitrogen cycle disruptions). He investigates Arctic/Antarctic soil microbiology, greenhouse gas production in polar deserts, and the ecological effects of pollutants like mercury and petroleum hydrocarbons. His lab is divided into toxicology (e.g., metal cardiovascular effects, soil ingestion models) and ecology (e.g., sub-zero water effects on gene expression, Arctic nitrogen cycles). Teaching: Teaches courses on environmental fate analysis, contaminated site management, and advanced risk assessment methodologies at both undergraduate and graduate levels. Courses include EVSC 420, TOX 820, and EVSC 821. Grants & Labs: Directs the CREATE Program and leads projects funded by NSERC and industry partnerships. His lab integrates fieldwork, molecular techniques, and modeling to address environmental remediation challenges. Collaborates on projects like cryoturbation-driven carbon dynamics and microbial community analysis in agricultural systems. Labs/Teams: Active in soil science research teams, including Arctic soil microbiology and bioremediation innovation groups. Engages in interdisciplinary collaborations with environmental engineers and ecologists to advance in situ remediation technologies.

• Soil Toxicology
• Environmental Science
• Polar Ecosystems
• +5 more

Prof. Ivan Cole is an Adjunct Professor at RMIT University's School of Engineering, specializing in rapid materials discovery for corrosion protection, nanostructures, and additive manufacturing. His work integrates computational modeling with high-throughput experimentation, focusing on corrosion inhibitors, biocompatible surfaces, and additive manufacturing process optimization. With over 30 years of experience across academia and industry (including leadership roles at CSIRO and Centro-Svilluppo Materiali), he leads the Rapid Discovery & Fabrication Team (RDF) to advance these research areas. Research Interests: Corrosion science, microbially induced corrosion (MIC), additive manufacturing surfaces, nanostructure sensing, multiscale modeling, and green materials discovery. His team addresses challenges in corrosion protection, biomedical implants, and environmental remediation through innovative methodologies. Awards: 2019 Australian Corrosion Medal 2016 CSIRO Lifetime Achievement Award 2013 Best Paper in NACE Corrosion Supervision & Projects: Active in mentoring PhD/Master’s students across corrosion inhibition, additive manufacturing, and nanostructure design. Notable projects include developing quorum sensing inhibitors for biofilm control, in-situ monitoring for metal AM, and eco-friendly corrosion inhibitors. Labs & Collaborations: Leads the Rapid Discovery & Fabrication Team and collaborates with industry partners to translate research into practical solutions for materials durability and sustainability.

• Corrosion Science
• Multiscale Modelling
• Additive Manufacturing
• +7 more

Reiko Heckel is a Professor of Software Engineering at the University of Leicester, serving as Director of Postgraduate Teaching for Computing degrees and Data Analytics Lead at the Leicester Innovation Hub. She previously held academic roles at the Technical Universities of Dresden and Berlin before joining Leicester in 2004. Her research focuses on graph transformation systems, model-based development, stochastic modeling, and formal methods in software engineering. She earned her PhD (Dr.-Ing.) in Computer Science from TU Berlin in 1998. Her research interests span software engineering pedagogy, formal specification techniques, and applications of graph grammars in system modeling. Recent work explores stochastic graph transformations for social networks, transparency engineering in AI systems, and blockchain-based smart contract frameworks. Her contributions bridge theoretical foundations with practical applications in cybersecurity, data integration, and human-centric systems design. Key contributions include advancements in automated test case generation via graph transformations, visual contracts for software reverse engineering, and formal methods for complex system analysis. Her work frequently intersects with industry through collaborations via the Leicester Innovation Hub, emphasizing data analytics and technology transfer. Education: MSc Computer Science, Technical University of Dresden PhD (Dr.-Ing.), Computer Science, TU Berlin (1998) Leadership Roles: Head of Department (2014-2018) Director of Postgraduate Teaching (Ongoing) Research Themes: Model-Based Development Stochastic Systems Analysis Graph Neural Networks Trustworthy AI Her publications reflect a focus on formal methods, with recent trends in applying graph transformation techniques to social network modeling, blockchain smart contracts, and educational pedagogy.

• Software Engineering
• Graph Transformation Systems
• Model-Based Development
• +5 more

Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.

• Big Data Analytics
• Social Network Analysis and Mining
• Analysis of Human Mobility
• +17 more

Oliver Hohlfeld is a Professor at the University of Kassel, where he leads the Distributed Systems group. He previously held academic positions at Brandenburg University of Technology and RWTH Aachen University, and was a visiting scholar at the University of Wisconsin–Madison. His research focuses on network security, Internet measurements, and Quality of Experience (QoE). He completed his Ph.D. in Computer Science at TU Berlin under Anja Feldmann and holds a B.Sc. and M.Sc. from Darmstadt University of Technology. He also worked at Fraunhofer IGD on telemedical network architectures. His research adopts a data-driven approach, combining large-scale Internet measurements, user studies, and machine learning to understand and improve Internet performance and security. Key areas include DDoS detection, QUIC, HTTP/2, TLS deployment, and BGP analysis. He investigates how protocols like QUIC and HTTP/2 impact user experience and network efficiency, often through empirical studies of real-world deployments. His recent publications highlight a strong trend in network security and protocol analysis, with significant work on DDoS attacks, traffic ingress detection, and web consolidation. He also explores social media dynamics and censorship circumvention through user reviews. 2022 IETF/IRTF Applied Networking Research Prize Best of CCR (2021) for TLS 1.3 deployment study ACM Senior Member (2020) IEEE QoMEX 2019 Best Reviewer Award ACM IMC Community Contribution Award (2018) He has advised numerous Master’s and Bachelor’s students, primarily at RWTH Aachen, and has been a principal investigator in major projects such as AIDOS (AI-based DDoS mitigation), DFG SFB MAKI, COMTEX, and the EU-funded SSICLOPS. He actively serves on the technical program committees of top-tier conferences including SIGCOMM, NSDI, IMC, and CoNEXT, and is a frequent reviewer for leading journals in networking and systems. He leads the Distributed Systems group at the University of Kassel, which conducts research on Internet observability, secure infrastructures, and scalable networking solutions.

• Network Security
• Network Measurements
• Internet Architecture
• +9 more

Associate Professor Sam Kirshner is a faculty member at the University of New South Wales within the School of Information Systems and Technology Management . His research focuses on behavioral decision making , algorithmic impact on operations , and artificial intelligence applications in business contexts. PhD in Management Science from Queen’s University, Canada Teaching expertise in data visualization, predictive analytics, and AI ethics Co-author of Business Analytics: A Management Approach Member of the Ethical AI Advisory His research explores how psychological distance and construal level theory influence decisions in supply chains, technology management, and consumer behavior. Recent work examines ChatGPT's decision biases , algorithm aversion , and sustainable operations under financial constraints. Key publication trends show focus areas: AI ethics and human-AI collaboration Behavioral supply chain analysis Temporal/spatial psychological distance effects CO2 forecasting with sparse data Consumer behavior in digital platforms Virtual reality and cognitive processing Supervision roles include mentoring 2 PhD students and 6 honors students, contributing to the next generation of scholars in business analytics and technology management.

• Behavioral Decision Making
• Operations Management
• Technology Management
• +6 more

Emmanuel Stamatakis is a Professor of Physical Activity, Lifestyle, and Population Health at the University of Sydney's School of Health Sciences (Faculty of Medicine and Health). He holds NHMRC Leadership Fellowships (2021-2025 and 2026-2030) and leads the Charles Perkins Centre's Physical Activity & Exercise Theme. His research focuses on lifestyle behaviors' impacts on cardiometabolic conditions, cancer, and cardiovascular health, using large-scale cohort studies and wearable device data. Key roles include directing the Mackenzie Wearables Research Hub and co-chairing WHO's Physical Activity Guidelines Development Group. Education: PhD from University of Bristol (2003), post-doctoral training at University College London. He leads the ProPASS consortium, involving 45 cohorts with wearable data. Over 460 peer-reviewed publications, including Clarivate's Highly Cited list since 2019. Research interests integrate physical activity, sedentary behavior, and sleep analytics with clinical outcomes. Current projects explore wearables-based measurement innovations, SPAN (sleep-physical activity-nutrition) synergies, and intervention designs for GLP-1 receptor agonist users. Recent articles emphasize VILPA (vigorous intermittent lifestyle physical activity) benefits, sleep-cardiovascular links, and multimodal lifestyle optimization. Awards include Australia's Top Researcher in Sports Medicine and multiple NHMRC grants. Supervises PhD projects on physical activity measurement and intervention design. Active in 50+ peer-reviewed journals and national/international funding bodies.

• Physical Activity Epidemiology
• Public Health
• Cardiometabolic Health
• +4 more

Xiaofan (Fred) Jiang serves as an Associate Professor in the Department of Electrical Engineering within Columbia Engineering at Columbia University, holding dual affiliations as a Data Science Institute (DSI) Member and Smart Cities Chair for the Sense, Collect and Move Data Committee. His academic foundation was established at UC Berkeley through three earned degrees: Bachelor of Science in Electrical Engineering and Computer Science (2004) Master of Science in Electrical Engineering and Computer Science (2007) Doctor of Philosophy in Computer Science (2010) Dr. Jiang's research program bridges systems and data science with a core focus on intelligent embedded systems, driving innovations across mobile/wearable computing, intelligent built environments, IoT infrastructure, and connected health solutions. This interdisciplinary work has generated over four thousand citations and received widespread media coverage in The Economist, New York Post, Mashable, Gizmodo, The Telegraph, and Fast Company. His scholarly excellence is recognized through prestigious honors: National Science Foundation Graduate Research Fellowship Vodafone-US Foundation Fellowship National Science Foundation CAREER Award Prior to his Columbia appointment, Dr. Jiang directed analytics and IoT research as Senior Staff Researcher at Intel Labs China. His current work is funded by competitive grants including the NSF CAREER award while mentoring graduate students in electrical engineering. He actively shapes Columbia's research ecosystem through leadership in the Data Science Institute's Smart Cities initiative and the Sense, Collect and Move Data Committee, advancing urban technology applications.

• Intelligent Embedded Systems
• Mobile Computing
• Wearable Computing
• +3 more

Professor Ute Stephan is a Professor of Entrepreneurship at King's Business School, King’s College London, where she is affiliated with the Strategy, International Management & Entrepreneurship department. She is a globally recognized scholar in the psychology of entrepreneurship, with a focus on entrepreneurial well-being, mental health, social entrepreneurship, and the role of culture and institutions. Research Interests: Entrepreneurial well-being, stress, and mental health Social and inclusive entrepreneurship Cross-cultural innovation and national culture Family business and women entrepreneurs Entrepreneurial resilience during crises (e.g., Covid-19) Feedback-seeking and social networks Her recent publications reveal a strong trend toward understanding the psychological and social dimensions of entrepreneurship, particularly how entrepreneurs navigate uncertainty, maintain well-being, and create inclusive impact. Her work integrates insights from organizational behavior, psychology, and management, often using cross-national data and meta-analytic methods. Scientific Awards and Recognition: 2025 JIBS Decade Award Fellow, International Association of Applied Psychology (IAAP) 21st Century Entrepreneurship Fellow Winner, 2016 GLOBE Robert J. House Best Research Paper Award Highly Commended, 2015 GLOBE Robert J. House Best Research Paper Award Nominee, 2021 Journal of Management Scholarly Impact Award She has secured over £3 million in research funding from the European Commission, UK Government, UK research councils, and German institutions. She serves as Associate Editor at Journal of Management and Entrepreneurship Theory & Practice , and previously held editorial leadership roles at Applied Psychology and Journal of International Business Studies . She is an elected board member of the IAAP and chairs its publication committee. She also advises the Founder Mental Health Pledge and is an IfM Research Fellow at IfM Bonn. Labs and Research Teams: Lead investigator of the 25-country study on Entrepreneurship & COVID-19 Principal investigator of the WEWell project on women entrepreneurs’ well-being Lead investigator of the SEFORIS and SELUSI projects on social enterprises Team member in large-scale international collaborations across Europe, Asia, and the Americas

• Entrepreneurship
• Psychology of Entrepreneurship
• Entrepreneurial Well-being
• +17 more

Academic Profile: Damir Filipovic is a Full Professor and the Swissquote Chair in Quantitative Finance at the College of Management of Technology (CDM) of École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He previously held academic positions at the University of Vienna, University of Munich, and Princeton University, and served as Head of the Vienna Institute of Finance. Research Focus: Quantitative finance, risk management, stochastic processes, term structure modeling, volatility risk, and machine learning applications in financial markets. Industry Collaboration: Co-developed the Swiss Solvency Test for insurance capital requirements while consulting for the Swiss Federal Office of Private Insurance. Publications: Contributed extensively to journals like Journal of Financial Economics, Mathematical Finance, and Annals of Applied Probability, with a textbook on Term-Structure Models. Academic Service: Editorial board member of multiple journals and organizer of advanced workshops on systemic risk and financial technology. Recent Research: His work emphasizes machine learning for portfolio risk management, kernel-based yield curve estimation, and robust stochastic modeling. Keynote speaker at international conferences on finance and insurance mathematics, with over 15 recent publications in 2023-2025 addressing high-dimensional financial problems, neural control systems, and causal inference in market data. Education: Ph.D. in Mathematics from ETH Zurich (2000). Graduate of ETH Zurich and University of Vienna. Teaching & Mentorship: Supervises current and former EPFL Ph.D. students in quantitative finance, including Nicolas Camenzind, Joshua Hayes, Andrea Ruglioni, and ten others. Former students like Damien Ackerer and Lotfi Boudabsa now lead research in risk management. Labs & Programs: Directs EPFL's Finance and Technology Programme, leads the Computational Finance Group (CSF) at EPFL, and contributes to Swiss Finance Institute initiatives. Scientific Leadership: Served on EPFL Committee of Academic Evaluation and Doctoral Program Finance committee.

• Quantitative Finance
• Risk Management
• Machine Learning
• +7 more