Susan Anenberg is a Professor and Chair of the Environmental and Occupational Health department at the George Washington University Milken Institute School of Public Health. She directs the GW Climate and Health Institute and serves as President of the AGU GeoHealth Section (2023-2024). Her research integrates epidemiology, atmospheric modeling, and policy analysis to quantify health impacts of air pollution and climate change. PhD in Environmental Science and Engineering from UNC (2011) Former EPA environmental scientist and U.S. Chemical Safety Board deputy director Key research themes include: Global air pollution burden of disease estimation Climate change health co-benefits analysis Satellite remote sensing for exposure assessment Environmental justice and exposure disparities GeoHealth policy frameworks Her recent work leverages geospatial datasets to reveal racial/ethnic disparities in NO2 exposure and develops decision-support tools for urban climate action plans. She has contributed to major publications in Lancet Planetary Health , Science , and Nature , and serves on advisory boards for EPA, WHO, and the U.S. National Academy of Sciences. Scientific engagement includes: Co-founding Environmental Health Analytics, LLC Technical advisory roles for Clean Air Act and climate policy Development of multi-modal vehicle electrification health impact models
Bhuvan Urgaonkar is a Professor in the Department of Computer Science and Engineering at Penn State University's College of Engineering. His research centers on optimizing cloud computing systems through innovative approaches to resource allocation, cost efficiency, and energy management. Current research focuses on Burstable Instance Scaling Serverless Computing Optimization Distributed Storage Systems Multi-resource Fair Allocation Cloud Economics Recent publications highlight advancements in autoscaling techniques, serverless architecture design, and trace modeling for high-load scenarios. These works emphasize practical solutions for cost-effective resource utilization in public cloud environments. Scientific Awards: CNS: Core: Small: Consistent, Geo-Distributed Data Stores on the Public Cloud (NSF, 2022-2025) CNS Core: Small: Principled Methodologies for Automated Cost-Effective Service Blending (NSF, 2021-2024) PPoSS: Cross-Layer Design for HPC in the Cloud (NSF, 2020-2022) CSR: Burstable Instances for Cost-Efficacy (NSF, 2017-2020) CSR: Student Travel Support for SIGMETRICS (NSF, 2016-2017)
John Breslin is a Personal Professor in Electronic Engineering at the College of Science and Engineering, University of Galway, serving as Director of the TechInnovate and AgInnovate programmes. Associated with two Taighde Éireann – Research Ireland Centres, he is a Principal Investigator at Insight Centre for Data Analytics (specializing in data analytics) and a Funded Investigator at VistaMilk (Agri-Technology), while also leading the EDIH Data2Sustain project. With an h-index of 50, over 12,000 citations, and 300+ peer-reviewed publications including seminal books on the Social Semantic Web, he ranks among Ireland's most influential researchers in digital technologies. Breslin's research fundamentally bridges Semantic Web technologies, AI-driven data analytics, and practical innovation. His co-creation of the SIOC framework—implemented across 65,000+ websites by entities like Yahoo and Boeing—demonstrates real-world impact in social data interoperability. Current work leverages blockchain and federated learning for sustainable Agri-Technology through VistaMilk, while his TechInnovate programmes translate academic research into commercial ventures across healthcare, smart manufacturing, and energy systems. Analysis of his 15 most recent publications reveals dominant themes in AI-enhanced security (35% of works), blockchain applications for sustainability (27%), and multimodal AI for healthcare (20%). His team pioneers privacy-preserving techniques for IoT and medical devices, neurosymbolic visual reasoning frameworks, and federated learning architectures addressing data heterogeneity—directly supporting his roles in national research infrastructures like Insight and VistaMilk. John has received several prestigious awards: IIA Net Visionary Award (twice) ITAG Outstanding Contribution to the ICT Sector Award Galway Chamber President’s Award Best Irish-Published Book Award (2020 for Old Ireland in Colour) Multiple Best Paper Awards He leads major research initiatives funded by Taighde Éireann – Research Ireland: Insight Centre for Data Analytics (as Principal Investigator) VistaMilk SFI Research Centre (as Funded Investigator) EDIH Data2Sustain (as Principal Investigator) His entrepreneurial programs TechInnovate and AgInnovate have mentored 200+ startups, securing €50M+ in follow-on funding. Breslin co-founded PorterShed (Galway City Innovation District) and serves on Scale Ireland's Steering Group, creating Ireland's most active regional innovation ecosystem outside Dublin. He maintains active industry partnerships with Vodafone, Boeing, and agricultural cooperatives through VistaMilk's testbed facilities.
Cynthia D. Rudin is the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science at Duke University, with joint appointments in the Departments of Electrical and Computer Engineering, Statistical Science, Mathematics, and Biostatistics & Bioinformatics. She directs the Interpretable Machine Learning Lab and has held previous positions at MIT, Columbia, and NYU. Her educational background includes: Undergraduate degree from the University at Buffalo PhD from Princeton University (2004) Research Interests: Dr. Rudin's research focuses on interpretable machine learning and its applications across multiple domains. Her work emphasizes creating machine learning models whose reasoning processes people can understand, which includes algorithms for extremely sparse models, interpretable neural networks, interpretable matching methods for causal inference, and dimension reduction for data visualization. She applies these techniques to critical societal problems in healthcare, criminal justice, materials science, and other domains. Her lab has developed practical code for sparse models such as decision lists, decision trees, and additive models that provably optimize accuracy and sparsity. Dr. Rudin's recent publications (2024-2025) demonstrate a strong focus on interpretable AI applications across diverse fields including healthcare (mortality risk scores, breast cancer prediction), materials science (metamaterials design), and environmental justice (location-based health analysis). Her work consistently emphasizes practical implementations with real-world impact, particularly in high-stakes decision-making domains where model transparency is critical. Scientific Awards: Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity (2022) - often described as the "Nobel Prize of AI" INFORMS Society on Data Mining Prize (2024) Guggenheim Fellowship (2022) Three-time winner of the INFORMS Innovative Applications in Analytics Award (2013, 2016, 2019) Winner of the 2023 John M. Chambers Statistical Software Award for PaCMAP Winner of the 2024 Award for Innovation in Statistical Programming and Analytics Dr. Rudin has advised numerous PhD students and postdocs who have co-authored significant publications with her. Her lab has received substantial funding for projects applying interpretable machine learning to healthcare (seizure prediction in ICU patients), criminal justice (crime series analysis), and energy infrastructure (underground electrical distribution networks). Her work on the Series Finder algorithm has been adapted by the NYPD and has been running live in NYC since 2016. She directs the Interpretable Machine Learning Lab at Duke, which includes the Almost-Matching-Exactly Lab focused on interpretable causal inference. Her team develops practical code implementations for all their research, emphasizing usability and real-world application in critical domains.
Stefan Gössling is a Professor and Research Coordinator specializing in sustainable tourism and climate change research with dual appointments at Lund University and Kalmar University. He currently serves as Research Coordinator at the Research Centre for Sustainable Tourism, affiliated with Vestforsk (Western Norway Research Institute), where he has been employed since 2007. Gössling earned his BSc in biology and MSc in geography from Westfälische Wilhelms-Universität, Münster, followed by a doctoral degree in Human Ecology from Lund University in 2001. After completing a postdoc at Freiburg University (2002-2003), he became Associate Professor at Lund University in 2005 and was promoted to full Professor in Human Ecology in 2008. He also holds a Professorship in Tourism Research at Kalmar University since 2009. His research focuses on tourism and climate change , sustainable tourism development , mobility studies , and low-carbon tourism systems . His fieldwork spans the Western Indian Ocean region (Mauritius, Seychelles, Zanzibar, Madagascar, Sri Lanka) and Jordan, with significant contributions to understanding tourism's environmental impacts, particularly in aviation and transport systems. Analysis of his recent publications reveals a strong trajectory toward policy-relevant research on carbon management in tourism, with increasing focus on net-zero aviation, economic leakage in digital platforms, and climate risk modeling for tourism destinations. His work bridges academic research with practical policy applications across multiple European contexts. Contributing author of IPCC AR4 Gössling has led numerous significant research projects including TourRisk (modeling climate risk for Norwegian tourism), ECOVET (effects of COVID-19 on cruise tourism in Western Norway), NTRANS (Norwegian Centre for Energy Transition Strategies), and sustainable cruise research examining social, environmental and economic effects. His influential books include Tourism and Global Environmental Change (2006), Sustainable Tourism Futures (2009), and Climate Change and Aviation (2009).
Professor Clinton Fookes is a faculty member at the Queensland University of Technology (QUT) within the School of Electrical Engineering & Robotics . His research focuses on leveraging computer vision and artificial intelligence to develop automated systems that understand, anticipate, and interact with human behaviors, with applications in medical diagnostics, autonomous vehicles, defense, and industrial efficiency . Research areas include AI adaptability, multimodal biosignal analysis, and human-machine interaction Collaborates with CSIRO Data61, Defence Science and Technology Group, Orica, Airbus, and Sentient Vision Systems Develops systems for human action detection, infrastructure monitoring, and stress response prediction His work addresses critical challenges in AI deployment, such as environmental adaptability and reducing diagnostic errors in medical and autonomous systems. Recent publications highlight trends in self-supervised learning, zero-shot knowledge transfer, multimodal integration , and 3D reconstruction for healthcare , while exploring ethical AI use in sectors like mining and defense . Professor Fookes emphasizes interdisciplinary collaboration, bridging engineering, medicine, and social sciences to advance AI systems capable of real-world impact. His research agenda includes improving AI memory capabilities and explainability for safer, more reliable automation.
Christos Makris is an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece. His academic career spans over two decades with significant contributions to computer science, particularly in data structures, algorithms, and information systems. He maintains active research collaborations and supervises graduate students in his areas of expertise. Dr. Makris's research spans several key areas in computer science with a strong focus on efficient data organization and processing. His work encompasses Data Structures , Information Retrieval , Data Mining , String Management and Processing Algorithms , Computational Geometry , Internet Technologies , Bioinformatics , and Multimedia Databases . His interdisciplinary approach bridges theoretical computer science with practical applications across various domains including web technologies, bioinformatics, and emergency response systems. Analysis of Dr. Makris's publication record reveals a consistent research trajectory focused on efficient algorithms for information management. His work demonstrates evolution from foundational data structure research in the 1990s to more applied work in web technologies, social media analysis, and machine learning applications in recent years. A notable pattern is his ability to adapt core algorithmic techniques to emerging application domains while maintaining theoretical rigor. Dr. Makris maintains an impressive scholarly record with over 3,000 citations, an h-index of 29, and an i10-index of 71 according to Google Scholar metrics. These indicators reflect the significant impact of his research within the computer science community. As an active faculty member, Dr. Makris maintains regular office hours on Tuesdays from 18:00-20:00 and Thursdays from 12:00-14:00. He is accessible via email at makri@ceid.upatras.gr or makri@upatras.gr for academic inquiries and student supervision.
Graham Ormondroyd is a Professor at the School of Environmental and Natural Sciences , Bangor University , specializing in the Biocompounds department. His research focuses on innovative wood modification techniques, sustainable biomaterials, and environmental impact assessments. Current projects include scaling waste-based composites for infrastructure and developing Welsh wool applications. Collaborations span academia-industry partnerships like Bangor University and Zentia Ltd KTP. Research Trends: His 2025 publications emphasize multi-scale resin diffusion analysis and UK wood recycling frameworks, while 2024 work explores laser incising and phenolic resin-NMR interactions. Recent studies also address VOC emissions from formaldehyde-free composites. Professional Activities: He chairs academic panels (e.g., International Panel Products Symposium) and reviews publications. Projects focus on net-zero construction and climate resilience.
Imraan Faruque is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University (OSU), part of the College of Engineering, Architecture and Technology (CEAT). His research focuses on biologically-inspired flight control systems, engineered autonomy for unmanned aerial vehicles (UAVs), and the integration of sensory feedback mechanisms in autonomous systems. Education: Faruque holds a Ph.D. and M.S. in Aerospace Engineering from the University of Maryland (2011 and 2010) and a B.S. in Aerospace Engineering from Virginia Tech (2006). Research Interests: His work emphasizes bio-inspired solutions for aerial autonomy, including swarm coordination, gust-aware flight control, and human-autonomy interaction. Key areas include unmanned systems design, visual feedback algorithms, and adaptive control strategies derived from insect flight dynamics. Awards: He has received notable accolades such as the ONR Young Investigator Award (2019), AIAA Hal Andrews Young Engineer/Scientist Award (2017), and multiple 'Best in Session' recognitions at major conferences. His team also secured 1st Place in the International Aerial Robotics Championship (2005). Publications: Faruque’s research spans topics like orbital debris management, swarm intelligence, and tornado sensing with UAVs. His work bridges biological principles and engineering, with applications in aerospace, robotics, and environmental monitoring.
Dr. Albert Koulman is a Principal Research Associate at the University of Cambridge, affiliated with the Metabolic Research Laboratories (MRL) within the Institute of Metabolic Science. His work focuses on developing advanced analytical methods for metabolomics and lipidomics to understand metabolic processes in diseases. Department: Department of Clinical Biochemistry, University of Cambridge Key Roles: Scientific Director of the NIHR BRC Metabolomics and Lipidomics facility Research Interests 1. Metabolism in Pregnancy & Early Life: Collaborates with international teams to study lipid metabolism during pregnancy and infancy, developing biomarkers for gestational diabetes, infant nutrition, and childhood obesity risks. 2. Technological Innovations: Leads development of single-cell lipidomics and organelle-specific lipid profiling, establishing a full pipeline from sample preparation to bioinformatics. 3. Nutritional Biomarker Methodology: Specializes in dried blood spot applications for lipid analysis in clinical and population studies, supported by the MRC Epidemiology Unit. Article Trends Recent publications highlight his expertise in lipid metabolism across diseases (e.g., diabetes, melanoma, NAFLD). Key themes include sexual dimorphism in lipid biosynthesis, vitamin D dynamics during exercise, stromal lipid influences on cancer progression, and malnutrition recovery protocols. Methodological advancements (LC-MS/MS, single-cell analysis) and global health applications (Gambian maternal nutrition, pediatric rehabilitation) are recurring topics. Group Members & Collaborations Dr. Ben Jenkins (Analytical Chemist) Ms. Paulina Guevara Dominguez (Research Assistant) Ms. Nina van der Velde (MPhil Student) Collaborators: Sue Ozanne (Pregnancy Metabolism), MJFF (Parkinson’s research), MRC (Epidemiology Unit) Research Funding Biotechnology and Biological Sciences Research Council (BBSRC) JPI (Joint Programming Initiative) Michael J. Fox Foundation (MJFF) Medical Research Council (MRC) National Institute for Health and Care Research (NIHR)
Hailiang Chen serves as Professor in Innovation and Information Management, Assistant Dean (Taught Postgraduate), and Director of the Artificial Intelligence Research Institute at HKU Business School, The University of Hong Kong. His academic journey includes a PhD and MS from Purdue University and a BM from Tsinghua University. Doctoral Degree: Management Information Systems, Purdue University Master Degree: Economics, Purdue University Bachelor Degree: Information Management and Information Systems, Tsinghua University Professor Chen's research spans artificial intelligence, FinTech, social media analytics, and platform economics, with significant contributions to understanding how digital interactions shape financial markets and consumer behavior. His work frequently examines the intersection of technology adoption and economic outcomes, particularly in cryptocurrency markets, live-stream commerce, and venture capital decision-making. His research methodology combines large-scale data analysis with experimental designs to uncover causal relationships in digital ecosystems. His publications in elite journals like Journal of Financial Economics and Management Science demonstrate consistent impact, with multiple ESI Highly Cited Papers. Current projects include Gov-RAG for e-government services and comparative studies of AI search tools. His research has received continuous funding from Hong Kong's Research Grants Council for five consecutive years (2019-2023). Faculty Outstanding Researcher Award, HKU Business School (2022-23) INFORMS ISS Sandra A. Slaughter Early Career Award (2022) Association for Information Systems Early Career Award (2019) Three ESI Highly Cited Papers (Top 1% in field) Professor Chen actively contributes to academic service as Associate Editor for Journal of Management Information Systems and MIS Quarterly , and serves as Program Chair for the International Conference on Smart Finance. His industry collaborations include Alibaba, HSBC, and China Construction Bank, bridging academic research with real-world business applications in AI implementation and digital transformation.
Prof. Markus Axer is a Professor and Deputy Head of the Structural and Functional Organisation of the Brain (INM-1) at the Institute of Neuroscience and Medicine (INM) within Forschungszentrum Jülich. His research focuses on connectomics, neuroimaging technologies (e.g., 3D-Polarized Light Imaging), and high-performance computing applications in brain architecture analysis. He leads the 'Fiber Architecture' working group, advancing microscopy techniques like scattered light imaging and MRI-histology correlation for studying brain microstructure. His work bridges experimental neuroscience with computational methods, aiming to decode brain organization at meso- and macroscales. Key achievements include developing the HippoMaps atlas of the human hippocampus and improving fiber orientation mapping in brain tissue. Awards include Fellowship in the Royal Netherlands Academy of Arts and Sciences (2024). Research emphasizes cross-modal data integration, with applications in Alzheimer’s disease biomarker validation and primate brain evolution studies. He collaborates with academic institutions like the University of Wuppertal and contributes to international initiatives like the BigBrain Analytics Learning Laboratory.
Professor Ashish Sinha is a leading academic in Marketing at the UQ Business School, holding concurrent roles as Visiting Professor at the Indian School of Business and Research Fellow at the Hong Kong Polytechnic University. His career spans senior leadership in academia (e.g., Academic Dean of Executive Education at ISB, Interim Dean at UTS Business School) and industry (Vice President at IRI, Chicago). His research bridges theory and practice, focusing on digital transformation, AI-driven strategies, ESG impact analysis, and marketing analytics. He has pioneered frameworks for retail optimization, category management, and B2B innovation adoption, with over 30 journal articles in top-tier outlets like Journal of Marketing and Marketing Science . Research Impacts: Sinha’s work has transformed executive education programs (e.g., ISB’s #38-ranked custom programs) and driven research excellence at UTS. He is a serial entrepreneur, having founded two analytics firms acquired for their practical impact. His $240M Food Agility CRC participation highlights his role in agribusiness innovation. Awards include the Davidson Award and twice runner-up for the Gary Lilien Practice Award for applied marketing science. Key Research Themes: AI in Marketing, Digital Transformation, ESG Strategies, Consumer Sentiment Analysis Leadership Roles: Academic Dean (ISB), ADR (UTS), Head of Marketing (UNSW) Industry Experience: Analytics leadership at IRI, strategic consulting across sectors Grants/Partnerships: CI in Food Agility CRC ($240M), multiple ERA-recognized research collaborations. Advises on AI ethics, sustainable marketing, and global business strategy.
Li Yang is an Assistant Professor in the Department of Information Technology , part of the Faculty of Business and Information Technology at Ontario Tech University. His research focuses on applying AI and machine learning to cybersecurity, particularly in intrusion detection and anomaly detection for 5G/6G networks and IoT systems. He holds a PhD in Electrical and Computer Engineering from Western University (2022), and has held roles such as Vice Chair of IEEE Computer Society, London Section (2022–2023). Education: PhD in Electrical and Computer Engineering, Western University (2022) Master of Science, University of Guelph (2018) Bachelor of Engineering, Wuhan University of Science and Technology (2016) Research Interests: His work spans cybersecurity, machine learning, deep learning, AutoML, model optimization, network automation, IoT security, intrusion detection, and adversarial machine learning. He develops frameworks for concept drift adaptation and online learning to enhance cybersecurity measures, with a focus on trustworthy AI and defense strategies against adversarial attacks. Awards: Graduate Student Award for Excellence in Research (2022) Graduate Symposium Award for Best Presentation (2022) Mitacs Accelerate Fellowship (2021) OC2 Lab Industrial Research Excellence Award (2020) Ranked in Stanford/Elsevier's Top 2% Scientists (2024) Grants & Involvement: Li Yang has contributed to conferences like IEEE GlobeCom and IEEE CCECE, and authored patents such as 'Convenient primary-secondary barrels' (2009). His work has garnered thousands of citations and GitHub stars, emphasizing practical applications of AI in cybersecurity.
Samir Elhedhli is a Professor in the Department of Management Sciences at the University of Waterloo, within the Faculty of Engineering. His research focuses on Large-scale Optimization, Logistics, Supply Chain Design, Healthcare Operations, Airline Scheduling, and Data Analytics. He has held grants from NSERC, CFI, OCE, and MITACS, collaborating with industries in aircraft manufacturing, airline scheduling, and warehouse management. Education: PhD in Management Science, McGill University (2001) Master's in Industrial Engineering, Bilkent University (1996) Bachelor's in Industrial Engineering, Bilkent University (1994) Research Interests: Data Analytics & Data Science Large-scale Optimization (Interior-point methods, decomposition, column generation) Supply-chain Analytics (Logistics, warehousing, routing, scheduling) Environmental Sustainability in Supply Chains Key Awards: CORS Service Award (2013) University of Waterloo Distinguished and Outstanding Performance Awards (2005–2019) Grants & Advising: Active grants from NSERC, CFI, OCE, and MITACS Currently accepting graduate student applications Administration & Service: Chair, Department of Management Sciences (2014–2018) President, Canadian Operational Research Society (2011–2012) Co-Editor-in-Chief, INFOR Journal (2014–present) Labs & Teams: Leads the WanOpt research group focused on optimization methodologies and applications.
