Josh Pasek is a Professor of Communication & Media and Political Science at the University of Michigan, with additional affiliations as a Research Professor at the Center for Political Studies (Institute for Social Research) and Core Faculty at the Michigan Institute for Data Science. His research focuses on the intersection of political communication, survey methodology, and data science, particularly examining how new media and psychological processes shape political attitudes, public opinion, and measurement accuracy. Co-author of Words That Matter and Democracy Amid Crises Maintainer of R packages anesrake and weights Key research areas include: Political Communication Survey Methodology Media Psychology Social Media Data Electoral Behavior Ballot Design His recent publications address topics such as: Vaccine hesitancy and information environments Phubbing and trust dynamics Supreme Court legitimacy post-Dobbs Partisan polarization during the pandemic Climate change perception and partisanship Measurement error in surveys He has collaborated with institutions like the Annenberg Public Policy Center, Georgetown University, and the Pew Research Center, and serves on the AAPOR Task Force for 2024 Pre-Election Polls.
Professor Daniel Catchpoole serves as Deputy Head of School (Research) at the School of Computer Science, University of Technology Sydney (UTS), holding dual appointments at UTS and The Children's Hospital at Westmead. With over 20 years of research experience, he bridges computational sciences and pediatric cancer research through the Biomedical Data Science Lab in the Australian Artificial Intelligence Institute. His work integrates data analytics, artificial intelligence, and software development with molecular cancer biology to transform pediatric cancer treatment pathways. PhD in Cancer Cell Biology, University of New South Wales (1991-1995) Founding Fellow, Royal College of Pathologists Australasia (2010-present) Head, Children's Hospital at Westmead Tumour Bank (2001-present) Professor Catchpoole's research focuses on translational applications of genomics in childhood cancers, particularly acute lymphoblastic leukemia and neuroblastoma. His work combines high-throughput genomic technologies with advanced computational analysis to develop systems biology approaches for cancer patient assessment. Recent projects explore virtual reality applications for complex genomic data visualization and copper chelation therapies to enhance neuroblastoma immunotherapy. His research has received significant funding from Cancer Institute NSW, Sony Foundation, ARC, and NHMRC. His publication record spans biomedical data science, cancer genomics, and virtual reality applications in oncology. Recent work demonstrates leadership in 3D latent diffusion models for tumor segmentation, biobank economics, and innovative immunotherapies. His research consistently addresses the critical need for actionable knowledge from complex multidimensional biomedical data. Editorial Board Member, Cancers (2023) Associate Editor, Innovations in Digital Health, Diagnostics and Biomarkers (2019) Founding member and first President, Australasian Biospecimens Network Association Professor Catchpoole has supervised 17 Honours students (including 6 First Class Honours), 3 MSc students, and 12 PhD candidates across multiple institutions, with 6 current PhD students. His collaborative research bridges UTS's Faculty of Engineering and IT with The Children's Cancer Research Unit at The Children's Hospital at Westmead. Significant research funding includes Cancer Institute NSW grants, Sony Foundation VR projects, and ARC Discovery Projects focused on genomic data analysis and clinical decision support systems. His leadership extends to building frameworks for translational research, managing biobanks and clinical data linkages, and navigating governance requirements for cancer research. The Tumour Bank at Kids Research, CCRU, represents his long-standing commitment to pediatric cancer infrastructure development.
Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.
Dr. Matteo Montecchi is a Senior Lecturer (Associate Professor) in Marketing at King’s Business School, King’s College London, where he also serves as Theme Lead for Sustainable Consumption at the Centre for Sustainable Business and Programme Director for the Strategic Marketing (Open Executive) programme. He teaches core modules such as Consumer Behaviour, Digital Marketing, and Research Methods, and leads executive education initiatives. Previously, he was a Senior Lecturer at the London College of Fashion, University of the Arts London, and has held visiting positions at Milan Politecnico, Università Cattolica del Sacro Cuore, and Università Federico II. Montecchi earned his PhD in Marketing from King’s College London, an MRes in Marketing from Birkbeck College, an Executive Master in Marketing and Sales from SDA Bocconi and ESADE, and a Bachelor’s in Business Economics from the University of Modena and Reggio Emilia. He also holds a PgCert in Academic Practice and is a Fellow of the Higher Education Academy (FHEA). His research focuses on the digital transformation of marketing, particularly the role of artificial intelligence and blockchain in enhancing transparency and trust. He investigates ethical engagement with diverse consumer groups, inclusion, and corporate responsibility, with a special interest in marginalized communities. His work integrates consumer behavior, digital interactions, and decision-making with technological innovation, offering actionable insights for sustainable and responsible business strategies. The most recent 15 publications reflect a strong trend in AI in retail, brand transparency, consumer trust, ethical data use, voice technologies, and social sustainability. His research spans journals in marketing, psychology, interactive marketing, and business ethics, demonstrating interdisciplinary impact. Scientific Awards: KingsCAT: Capture and Analysis Tool for Social Media Research at King’s College London (2024) – Recognized as part of a collaborative team for advancing digital research infrastructure and media analysis. Montecchi is actively involved in PhD supervision and is accepting new students. He has led research projects using social media analytics (KingsCAT) and has contributed to strategic debates on grand challenges in marketing. His work connects academic research with real-world managerial applications, particularly in digital strategy and ethical innovation. He is a key contributor to interdisciplinary research through tools like KingsCAT, which supports collaborative social media analysis, and his publications often involve co-authorship with experts in data science, psychology, and organizational behavior.
Professor Robert Eason is a leading academic at the University of Southampton, specializing in photonics and laser technology. His research spans interdisciplinary areas combining Machine Learning , Medical Diagnostics , and Microfluidics . Research Interests : Eason focuses on AI-driven laser applications, including deep learning for phototherapy , autonomous laser machining , and low-cost paper-based diagnostic devices . His work bridges photonics with biomedicine and advanced manufacturing. Recent Publications : His 2025 article in Scientific Reports explores AI simulations for psoriasis treatment, while 2024-2022 works address laser-controlled microfluidics, deep learning in microscopy, and reinforcement learning for laser machining. Supervision : He supervises PhD student Georgia Mourkioti in laser-based research projects. External Roles : Eason has served as a speaker at international conferences including the International Symposium on Laser Precision Microfabrication (2018), LAISER (2019), and Deep Learning for Control of Light-Matter Interactions (2022).
Overview Prof. Harris Kyriakou is an Associate Professor and Chair Holder of the Media & Digital Chair at ESSEC Business School. His research focuses on leveraging artificial and collective intelligence to enhance organizational value creation, digital strategy, and data-driven decision-making. He has advised multinational firms like Airbnb, Facebook, and Yelp, and his work is supported by grants from NSF and the Spanish government. Education Ph.D. in Management Sciences (Stevens Institute of Technology, 2016) M.S. in Engineering & Technology Innovation Management (Carnegie Mellon University, 2010) B.Sc. in Digital Systems (University of Piraeus, 2007) Research Focus His research explores intersections between AI/collective intelligence, blockchain, sharing economy regulations, and platform governance. Key themes include data network effects, algorithmic regulation, and digital transformation. Recent work on ChatGPT vs. Google examines AI-driven competitive dynamics in search markets. Recognition Awarded the 2024 Case Centre Triple Award, 2022 Early Career Award (AIS), and multiple best paper awards (AoM, INFORMS). Recognized as a 40-Under-40 MBA Professor by Poets & Quants. Teaching & Leadership Co-leads the 'Algorithmic Governance in Platform Economy' thesis Teaches courses on AI, digital strategy, and IT management at ESSEC and IESE Former Assistant Professor at IESE Business School (2016–2021) Professional Contributions Serves as a European Commission advisor on digitalization, reviewer for top journals (MIS Quarterly, Academy of Management Review), and mentor for doctoral candidates.
Timothy Harris is an Affiliated Lecturer at the University of Cambridge's Department of Computer Science and Technology, where he jointly teaches courses on multicore semantics and programming. Currently, he works at OpenAI, focusing on performance optimization for GPU inference of large language models, including the Azure OpenAI Service. Previously, he held roles at Microsoft, AWS, Oracle Labs, and was a faculty member at the University of Cambridge (2000–2004). His research spans distributed systems, runtime systems, operating systems, and high-performance computing, with an emphasis on scalability and performance. He contributed to projects like the Xen hypervisor and the Barrelfish research OS. Key research interests include distributed training of PyTorch models in the ONNX runtime, large-scale storage performance with Amazon S3, and runtime systems for in-memory graph analytics. His work often bridges 'big data' and high-performance computing techniques. Notable contributions include the book Transactional Memory (2010) and the Barrelfish OS, alongside numerous publications in top-tier conferences like SOSP, ASPLOS, and EuroSys. He has served as PC chair for ISMM 2025, VEE 2017, and EuroSys 2015, reflecting his leadership in the systems research community. His awards include a Best Paper Award at PACT 2010. Beyond academia, Harris is an avid hiker, aiming to complete the UK coastline, and maintains a photography portfolio at tlhphotography.uk .
Dr. Sheng Yang is an Assistant Professor in the School of Engineering at the University of Guelph. He leads the Design Innovation and Intelligent Manufacturing (DIIM) lab, focusing on advancing additive manufacturing, generative design, and smart manufacturing technologies. His research integrates IoT, big data analytics, and bio-inspired design to address challenges in aerospace, green energy, and healthcare. Key areas include computational design for additive manufacturing, data-driven mass customization, and digital twin-based optimization. Education: Ph.D. in Mechanical Engineering from McGill University (2019), followed by a Postdoctoral Fellowship at McGill (2019–2020). Joined University of Guelph in 2020. Research interests span energy efficiency, complex system optimization, and personalized healthcare products. Recent work emphasizes digital twin synchronization in robotics, machine learning for quality prediction, and sustainable additive manufacturing processes. Notable awards include the 2019 Association of Commonwealth Universities Blue Charter Fellowship and 2018 ASME Best Paper Award. His lab actively seeks partnerships in personalized healthcare, product design, and smart manufacturing. Grants and collaborations focus on advancing manufacturing technologies and sustainability. No formal advisees listed, but active in graduate training through lab projects. The DIIM lab explores cutting-edge solutions for industrial and societal challenges through interdisciplinary approaches.
Ulrich Tallarek serves as Professor of Analytical Chemistry in the Faculty of Chemistry at Philipps University of Marburg, where he has held a W3 professorship since 2011. He also serves on the Board of Directors for the Materials Science Center at the university, a position he has held since 2007. His research group focuses on the fundamental understanding of transport phenomena in porous media with applications spanning chromatography, battery technology, and microfluidic systems. The group maintains strong collaborations with institutions worldwide and secures substantial research funding for advanced computational and experimental work. Professor Tallarek's research interests center on functional porous solids, with specific focus on morphology-transport-performance relationships. His work bridges multiple scales from molecular dynamics simulations of solute behavior in nanopores to macroscopic transport in chromatographic columns and battery electrodes. Key research areas include diffusion in hierarchical porous media, electrokinetic phenomena in microfluidic systems, molecular simulation of chromatographic processes, and advanced characterization of porous materials using tomography and other techniques. His group has pioneered multiscale simulation approaches that connect molecular-level surface chemistry to macroscopic transport properties. The research output demonstrates consistent focus on understanding fundamental transport mechanisms in porous systems, with recent publications emphasizing multiscale simulation techniques, molecular dynamics studies of solvent effects in chromatography, advanced characterization of mesoporous structures, and applications to separation science and energy storage. The work shows strong integration of computational modeling with experimental validation across multiple length scales. 2003: Desty Memorial Prize for Innovation in Separation Science, The Royal Institution of Great Britain, London 2006: Young Scientist Award from DECHEMA e.V. 2011: Named Discussion Leader at the 2011 Gordon Research Conference on Physics & Chemistry of Microfluidics 2011–2012: Chairman of the German Chemical Society (GDCh), Marburg 2013: Finalist, World Technology Awards, for category Environment 2013: Named as one of the 100 most influential analytical scientists in the world (The Analytical Scientist Power List) 2017: Recipient of the Silver Jubilee Medal 2017, The Chromatographic Society, UK Professor Tallarek's research has been supported by numerous grants enabling high-performance computing resources, advanced instrumentation, and international collaborations. His group maintains strong ties with industry partners in separation science and analytical instrumentation. The Tallarek Research Group includes postdoctoral researchers, PhD students, and technical staff working across experimental and computational domains. Current projects focus on molecular simulation of chromatographic processes, advanced characterization of porous battery electrodes, and development of novel separation methodologies. The Tallarek Research Group operates state-of-the-art facilities for computational modeling, including access to high-performance computing resources at Forschungszentrum Jülich. The group also maintains experimental capabilities for chromatographic analysis, materials characterization, and microfluidic device development. Their work on physically reconstructed porous media has established new standards for connecting microstructure to transport properties in complex materials systems.
Chris Fuller, Ph.D., is the Samuel Langley Distinguished Professor of Engineering at the College of Engineering , Virginia Tech. He leads the Vibrations and Acoustics Laboratory (VAL) , focusing on active/passive noise control systems, metamaterials, and their application to aerospace, medical devices, and industrial machinery. Education: Ph.D. (1979) and B.E. (1974) from the University of Adelaide, Australia. Research Interests: Structural acoustics, adaptive materials, machine learning in noise prediction, and biomedical acoustics (e.g., neonatal incubators). Awards: ASME Rayleigh Award (2017), NASA Team Achievement Award (1996), and Fellow of the Acoustical Society of America. Recent Publications: Highlight advancements in drone noise reduction using neural networks, metamaterials for HVAC systems, and poro-elastic materials for low-frequency noise control.
Alberto Rodrigues da Silva is a Professor at the Institute Superior Técnico , part of the University of Lisbon . He teaches Fundamentals of Information Systems , primarily during the 1st Semester of the 2025/2026 academic year. His scientific interests revolve around Information Systems , Model-Driven Engineering (MDE), Requirements Engineering (RE), Social Computing , and Software Engineering . He has extensively contributed to the development of rigorous requirements specification languages like RSL (Requirements Specification Language) and its extensions (e.g., RSL-IL4Privacy for privacy policies). His collaborative work spans automated acceptance testing, GDPR compliance, and domain-specific languages (DSLs) for applications such as mobile development , digital twins , and legal contexts (e.g., LegalLanguage ). His research trends focus on integrating model-driven engineering with privacy policies , IoT applications , and low-code platforms . He has also explored tools like Maestro for data classification and usability testing, and RiverCure for flood simulation. Email: alberto.silva@tecnico.ulisboa.pt .
Mohan Qin is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin–Madison. Her research focuses on developing novel approaches for resource recovery from waste streams and the concentration and detection of microplastics in the Great Lakes. Dr. Qin received her educational degrees as follows: Ph.D. in Civil Engineering from Virginia Tech (2017) M.S. in Environmental Engineering from Peking University (2013) B.S. in Environmental Engineering from Shandong University (2010) Her primary research areas include: Bioelectrochemical systems for resource recovery from wastewater Environmental biotechnology for sustainable wastewater treatment Electrochemical processes for desalination and water treatment Membrane-based technology for selective ion removal Her work particularly emphasizes ammonia recovery from manure and wastewater, and the detection of microplastics in freshwater systems, contributing to sustainable water management and resource conservation. Analysis of Dr. Qin's recent publications (2022-2025) reveals a strong focus on ammonia recovery using membrane and electrochemical systems, with increasing attention to microplastics detection in lake water. Her work spans from fundamental transport mechanisms to practical applications in dairy manure treatment and Great Lakes monitoring, often integrating novel sensor technologies and renewable energy sources. Dr. Qin has received numerous awards, including: 2024 IWA Membrane Technology Specialist Group (MTSG) Rising Star Award 2024 University of Wisconsin-Madison Hilldale Undergraduate/Faculty Research Fellowship 2023 UW-Madison Media Fellow and Sustainability Fellow 2022 UW-Madison Madison Teaching and Learning Excellence (MTLE) Fellow Multiple awards during her graduate studies at Virginia Tech Dr. Qin actively mentors students through thesis and independent study courses (CIV ENGR 890, 990, 699) and has been awarded the Hilldale Fellowship for undergraduate research collaboration. Her research is supported by several fellowships including the UW-Madison Sustainability Fellow and Media Fellow, which likely fund her innovative work in resource recovery and microplastics detection. She leads a research group at UW-Madison focused on environmental biotechnology and electrochemical systems, collaborating with institutions like Yale University (where she completed her postdoc) and contributing to journals as an associate editor for Desalination and Water Treatment and on the early career editorial board of ACS ES&T Engineering.
Fabian J. Sting is a Full Professor and Director of the Department of Supply Chain Management - Strategy and Innovation at the University of Cologne since 2016. He also holds a tenured Associate Professorship in Operations Management at the Rotterdam School of Management, Erasmus University since 2014. His academic journey includes a Ph.D. in Productions Management (summa cum laude) from WHU-Otto Beisheim School of Management in 2008 and postdoctoral work at INSEAD in 2008–2010. University of Cologne : Chair of Supply Chain Strategy and Innovation (2016–present) Rotterdam School of Management : Associate Professor (2014–present), Assistant Professor (2010–2014) Education : Ph.D. (2005–2008), M.Sc. in Applied Mathematics (2005–2007), Diploma in Management Science (2002–2005) Sting’s research bridges operations management, innovation strategy, and supply chain dynamics. Key areas include: Supply chain coordination under uncertainty Employee-driven process innovation and cognitive biases Strategic capacity planning and risk hedging Industry 4.0 implementation challenges Interdisciplinary integration of behavioral and technical elements in operations Recent publications focus on dual sourcing strategies, fairness in operational decisions, and employee mobility’s impact on innovation. He contributes to high-impact journals like Management Science and Production and Operations Management . Sting participates in institutional research initiatives such as: ECONtribute: Markets & Public Policy – a Cluster of Excellence addressing digital transformation, inequality, and market failures through interdisciplinary economics, political science, and law Excellent Research Support Programme (ERSP) – supporting collaborative projects like HPDnet (improving pediatric kidney disease care via health networks)
Professor Ibrahim Khalil is a faculty member in the School of Computing Technologies at RMIT University, Melbourne, Australia. He holds a PhD in Computer Science from the University of Bern (2003) and has extensive industry experience in Silicon Valley focusing on secure network protocols. His research spans Security, Privacy, Federated Learning, Blockchain, Quantum Computing, and Distributed Systems. He leads high-impact projects funded by ARC grants (DP250100582, DP220100215, etc.) and international initiatives like the EU’s SELFY project. His work addresses challenges in secure AI data analytics, privacy-preserving systems, and critical infrastructure protection. Khalil supervises PhD/Masters students on topics ranging from federated learning security to quantum-enhanced machine learning. Education: PhD in Computer Science (University of Bern, 2003); prior roles at EPFL, Osaka University, and industry tech hubs. Research Interests: Privacy-Preserving Technologies Blockchain Applications in Healthcare and Supply Chains Quantum Computing for Machine Learning Secure Edge Computing and Federated Learning IoT Security and Critical Infrastructure Protection Grants & Collaborations: Over 10 major grants since 2017, including ARC Discovery/Linkage Projects and international partnerships (QNRF, EU). Notable projects include Privacy-Aware Digital Twins for Critical Infrastructure and Federated Learning frameworks for GenAI models. Advising & Labs: Active supervisor of 25+ research projects since 2013, focusing on anomaly detection, secure data analytics, and blockchain-based systems. Collaborates with industry partners on defense and healthcare tech.
Jim Dowling is a distributed systems researcher at KTH Royal Institute of Technology, focusing on large-scale distributed systems, machine learning, and big data. His work emphasizes improving system dependability, performance, security, and scalability through middleware, peer-to-peer systems, and cloud-native solutions. He leads courses such as Advanced Course in Large Scale Machine Learning and Deep Learning and Scalable Machine Learning and Deep Learning , demonstrating his commitment to education in AI and distributed computing. His research spans topics like feature stores, Kubernetes integration, and AI-driven environmental analytics (e.g., ANIARA project for edge infrastructure automation and ExtremeEarth for Copernicus data analysis). He has contributed to scalable ML pipelines, cloud storage systems (HopsFS-S3), and hyperparameter optimization tools like Maggy. Key projects include the Hopsworks platform for machine learning operations and the development of cloud-native tools for big data analytics. His work bridges theoretical distributed systems research with practical applications in AI, healthcare, and environmental science. He has advised on numerous collaborative initiatives but no formal students are listed. His grants and lab activities are centered around Hopsworks and the ANIARA project, reflecting his focus on scalable, self-managing systems.
