Dr Tracy Qu is a Lecturer in the School of Accountancy at Queensland University of Technology (QUT), within the Faculty of Business & Law. She holds a PhD in Accounting from Griffith University (2018) and is a CPA Australia member (since 2021). Her research focuses on executive remuneration, corporate governance, financial reporting, and environmental accounting. Tracy teaches undergraduate and postgraduate courses in accounting fundamentals, financial analysis, and business valuation. She has also served as a referee for journals like Accounting and Finance and Australian Journal of Management . Tracy’s research explores intersections between governance structures and executive compensation design, particularly in mitigating agency conflicts. Her work examines topics such as carbon emissions policy impacts on corporate behavior, labeling effects in financial disclosures, and CEO celebrity influence on investment decisions. She actively contributes to academic debates on environmental accounting and sustainability reporting. Tracy is currently accepting research students for Honours, Masters, and PhD programs, focusing on topics like executive compensation efficiency, board interlocks, and compensation consultants’ roles.
Samuel Jean Bassetto is an Associate Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. He serves as Director of the Continuous Improvement Laboratory (LABAC) and holds membership in multiple prestigious research groups including the Research Group on Globalisation and Management of Technology (GMT), Poly-Industries 4.0 Laboratory, Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), and Institute for Data Valorization (IVADO). Dr. Bassetto's research spans multiple disciplines, focusing on continuous improvement through the integration of engineering, artificial intelligence, cognitive science, psychology, and design. His primary sphere of excellence is in New Frontiers in Information and Communication Technologies, with secondary expertise in Modeling and Artificial Intelligence and Human Health. He develops tools that place humans at the center of technology to enhance organizational performance while respecting human rhythms and cognitive limitations. His recent publication portfolio reveals a strong interdisciplinary approach, with research bridging industrial engineering, cognitive neuroscience, and AI ethics. His work addresses practical challenges in lean manufacturing assessment, racial bias in medical AI systems, cognitive data collection in natural environments, and condition monitoring for industrial machinery. The research consistently demonstrates a commitment to developing practical solutions that integrate human factors with technological innovation. NSERC Synergy Prize for Innovation recipient Principal investigator on multiple research grants from NSERC, FRQ, and MITACS Collaborations with over a dozen institutions across multiple countries Supervision of over 150 highly qualified personnel throughout his career Dr. Bassetto teaches specialized courses including CAP7011 (Creativity in Research), IND8444 (Continuous Improvement), IND8203 (Industrial Launch), and previously taught IND8178 (Production). His teaching philosophy emphasizes practical application, with courses featuring hands-on exercises, real-world scenarios, and gamification techniques to enhance learning. His supervision portfolio includes numerous Ph.D. and Master's students working on topics ranging from human-technology collaboration to reinforcement learning for production management. Through LABAC, Dr. Bassetto leads research initiatives focused on developing human-centered tools for continuous improvement in organizational settings. The laboratory conducts projects related to industrial IoT applications, cognitive aspects of process improvement, and the development of practical frameworks for organizations to enhance performance while maintaining respect for human rhythms and cognitive capabilities.
Thomas Le Goff is an Assistant Professor of Law & Technology at Télécom Paris – Institut Polytechnique de Paris, affiliated with the Interdisciplinary Institute of Innovation (i3) and the Digital, Organization and Society (DTOS) research team. His work bridges legal frameworks and technological advancements, focusing on AI regulation, environmental sustainability, data protection, and cybersecurity. Education: PhD in Private Law, Université Paris Cité Master’s in Law, Université Paris Cité LLM, University of Exeter (UK) Licence and Magistère, Université de Rennes 1 His research explores the intersection of AI and sustainability, emphasizing how legal principles can guide environmentally responsible technology. Key themes include the AI Act’s implications, data center energy demands, and regulatory strategies for balancing digital growth with net-zero targets. His work has been presented at international forums like BILETA and contributes to EU think tanks such as CERRE. Recent publications address AI’s environmental footprint, nuclear energy’s role in powering AI, and legal frameworks for sustainable digital infrastructure. Collaborations with institutions like the Center on Regulation in Europe (CERRE) highlight his focus on comparative analyses of global regulatory practices.
Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.
Dr. Justin Gerlach is a Fellow at Peterhouse College and an Academic Associate at the University Museum of Zoology, University of Cambridge. He specializes in broad-spectrum ecology, integrating conservation biology, evolutionary studies, and biodiversity analysis with a focus on island ecosystems in the Indian and Pacific Oceans. His research has pioneered invertebrate reintroduction programs and revealed groundbreaking insights into giant tortoise behavior. Education: DPhil in Zoology from Oxford University Current projects: Biodiversity assessment across Cambridge colleges, Partula snail reintroduction, tortoise aging studies Research interests center on preventing species extinction through conservation, studying species interactions, and evolutionary dynamics. Key initiatives include saving island invertebrates, investigating tortoise predation, and environmental DNA applications for ecosystem reconstruction. Recent publications highlight island conservation challenges, evolutionary patterns, and ecological innovations. Themes include biodiversity preservation, species reintroduction, and interdisciplinary approaches to conservation biology.
Thomas Hansen is a Research Professor at the Department of Mental Health within the Norwegian Institute of Public Health . His work focuses on subjective well-being , loneliness , aging , informal caregiving , and active aging , combining quantitative research and systematic reviews to address critical public health challenges. Key research areas: Loneliness trajectories, caregiving impacts, digital interventions for social connection Active in longitudinal studies (e.g., HUNT, SHARE) and cross-sectional analyses Collaborates with institutions in Norway and internationally His recent publications span gerontology , mental health interventions , and social epidemiology , emphasizing population-level well-being and policy recommendations . No scientific awards are explicitly mentioned. Thomas Hansen actively contributes to understanding social determinants of health in aging populations, advocating for evidence-based strategies to improve psychosocial outcomes through interventions targeting loneliness and caregiver support .
Alessia Ferrari is a fixed-term researcher in the Department of Engineering and Architecture at the University of Parma, Italy. She lectures on Hydrology within the Bachelor’s degree programme in Civil and Environmental Engineering and serves as the reference teacher for the same programme across multiple academic years (2020/2021 – 2025/2026). Research Focus Ferrari’s research integrates advanced numerical modelling with real-world flood-risk management. Key themes include: High-resolution 2-D shallow-water simulations using GPU-parallel codes. Porosity-based approaches for large-scale urban flood modelling. Levee-breach hydraulics and emergency-action planning. Calibration of hydraulic models using tools such as PEST. Integration of machine-learning techniques with physics-based flood forecasting. Publication Trends Across more than 25 peer-reviewed works (2015-2025), Ferrari has concentrated on computational hydraulics applied to extreme flood events in Northern Italy (e.g., Parma 2014, Lamone 2024). Her papers consistently advance numerical schemes (ADER, HLLEM Riemann solvers) and GPU acceleration while validating models against field data, thereby bridging theoretical development and practical flood-mitigation strategies. Contact & Office E-mail: alessia.ferrari@unipr.it Office: Science and Technology Campus – Pavilion 10, Engineering Scientific Headquarters, Parco Area delle Scienze 181/A, 43124 Parma, Italy.
Dr. June Cao is an Associate Professor at the University of Southampton . Her research focuses on Environmental, Social, and Governance (ESG) Accounting , Corporate Social Responsibility (CSR) , and Sustainability Reporting , with a particular emphasis on Greenwashing , Carbon Emission Trading , and Accounting Education . Key research areas include ESG, CSR, and sustainability frameworks. Prominent publications analyze environmental regulation, green revenues, and digital transformation in sustainability. Her recent work explores greenwashing behaviors, peer benchmarking, and labor investment dynamics. Scientific Awards : None explicitly mentioned in the data. Notable collaborations include co-authoring papers with scholars from Curtin University , Satya Wacana Christian University , and Xiamen University . Her contributions to Systematic Literature Reviews and Bibliometric Analysis highlight her methodological expertise.
Sudin Bhattacharya is an Associate Professor at the BioMolecular Science Gateway, Michigan State University, with affiliations in the Genetics & Genome Sciences Program and Cell & Molecular Biology Program. His research bridges computational biology and toxicology to understand complex biological systems. Email: sbhattac@msu.edu Research Interests Dr. Bhattacharya specializes in systems toxicology, focusing on computational modeling of gene regulatory networks, single-cell transcriptomics, and molecular dynamics in response to environmental toxicants. His work examines how chemical exposures disrupt cellular pathways and contribute to disease mechanisms. Article Trends His recent publications emphasize: Single-cell and single-nucleus RNA sequencing for toxicological profiling Computational models of circadian rhythms and intercellular communication Dose-dependent responses to environmental chemicals like TCDD and heavy metals Mechanistic studies of adipose tissue remodeling and hypertension Applications of machine learning in chemical risk assessment Integrative approaches to liver metabolism and disease modeling Scientific Contributions Dr. Bhattacharya has pioneered multiscale modeling of biological systems, particularly in hepatic and vascular contexts. His work on the aryl hydrocarbon receptor and PPARα signaling networks has advanced predictive toxicology frameworks.
Bruno Basso serves as the Hannah Distinguished Professor in the Department of Earth & Environmental Sciences at Michigan State University, based in 307A Natural Science Building. He teaches GLG 446: Water and Food and maintains active research in sustainable agricultural systems, with contact via 517-353-9009 or basso@msu.edu. His work bridges academic research with practical farm applications across the US Midwest. His core research interests include: Food Security and Plant Resilience mechanisms Soil Science with emphasis on organic carbon dynamics Precision Agriculture technologies (drones, remote sensing) Climate-Smart Agriculture practices Nitrogen and phosphorus use efficiency Yield stability analysis through spatial-temporal modeling Regenerative agriculture impacts on greenhouse gas emissions Ecosystem services valuation in crop-livestock systems Analysis of his 2023-2025 publications reveals a dominant focus on quantifying climate benefits from regenerative practices using multi-model ensembles. His work consistently addresses scalability for farmer adoption, with strong emphasis on N₂O emissions mapping, soil carbon durability, and yield stability zones. Key methodological innovations include hybrid SAR-remote sensing integration and AI-driven nutrient prescription systems, primarily applied across Midwest corn-soybean systems. No scientific awards were documented in the provided materials. While specific advising details are absent, his leadership in the LTAR cropland common experiment and Soil Inventory Project indicates active mentorship of graduate researchers. His research likely attracts significant USDA and NSF funding given the scale of field experiments and modeling initiatives focused on decarbonizing agriculture. Dr. Basso co-leads the Soil Inventory Project at Kellogg Biological Station, developing integrated sampling, data repository, and modeling frameworks for regenerative agriculture. His team combines ground observations, remote sensing, and biophysical modeling to quantify soil carbon and greenhouse gas fluxes, collaborating with farmers, industry partners, and international researchers to translate science into on-farm practices.
Michael Pyrcz is a Professor in the Hildebrand Department of Petroleum and Geosystems Engineering and holds the rank of Associate Professor in the Jackson School of Geosciences at the University of Texas at Austin. He is the recipient of the B. J. Lancaster Professorship in Petroleum Engineering and the George H. Fancher Centennial Teaching Fellowship in Petroleum Engineering. His research focuses on subsurface data analytics, geostatistics, and machine learning applications in energy systems and CO2 sequestration. Pyrcz teaches widely, including through online lectures and GitHub workflows, and has authored over 50 peer-reviewed publications and a textbook on spatial data analytics. His work integrates machine learning with geoscience challenges, such as uncertainty quantification in reservoir modeling and CO2 storage site evaluation. He leads initiatives in energy data analytics through the Freshman Research Initiative and collaborates with industry on workflow development. Key research areas include generative AI for subsurface models, stochastic methods for fracture networks, and anomaly detection in geologic monitoring. Education: Background in petroleum engineering and geosciences (details not explicitly provided). Grants/Advising: Extensive industry collaboration and mentorship roles at Chevron prior to UT Austin. Labs/Teams: Maintains active GitHub repositories (GeostatsGuy), YouTube lecture series (GeostatsGuyLectures), and social media outreach (X/GeostatsGuy).
James D. Long is a Professor of Political Science at the University of Washington and co-founder of the Political Economy Forum. He holds affiliations with multiple institutions including the Center for Statistics and the Social Sciences (CSSS) and the Technology and Social Change Group (TASCHA). His research focuses on electoral integrity, political violence, and ICT applications in development, particularly in sub-Saharan Africa and South Asia. He has observed elections in over a dozen countries and led field experiments on voter behavior and anti-corruption strategies. Long’s work is funded by USAID, NSF, and others. Education: PhD in Political Science, UC San Diego (2012) MSc in African Politics (Merit), SOAS, University of London (2004) BA in International Relations & History, College of William & Mary (2003) Research Interests: Elections in developing democracies, electoral fraud, technology for governance, insurgency impacts, and poverty reduction. His methods combine field experiments, ethnography, and election forensics. Recent Work: Examines ICT-driven citizen engagement platforms to improve governance and service delivery in developing nations. His 2020 ACM award-winning research addresses wildlife conservancy community relations via technology. Awards: ACM Best Paper Award (2020) Fulbright Scholar (2008-2009) Harvard Academy Fellowship (2012-2016) Advising & Grants: Supervises PhD students in comparative politics and development. Secured grants totaling over $1.5M for projects on electoral integrity and anti-corruption. Hosts the podcast 'Neither Free Nor Fair?' on global election security. Teaching: Courses include Global Crime/Corruption, African Political Economy, and Comparative Politics. Served as Associate Chair of the Department of Political Science.
Scott L. Stephens is a Professor in the Department of Environmental Science, Policy, and Management (ESPM) at the University of California, Berkeley. He holds a Ph.D. in Wildland Resource Science from UC Berkeley (1995) and a B.S. in Electrical Engineering from Sacramento State University (1985). His research focuses on wildland fire science, fire ecology, and forest management, with an emphasis on how climate change and policy influence fire regimes. He leads the Stephens Lab, which conducts interdisciplinary studies on fire behavior, ecosystem resilience, and policy reform. Key contributions include advocating for prescribed burning and Indigenous stewardship practices to mitigate wildfire risks. Stephens has testified before congressional committees on forest health and has been recognized as a Clarivate Highly Cited Researcher (2024). His work integrates ecological, policy, and management perspectives to address contemporary fire challenges. Education: Ph.D., Wildland Resource Science, UC Berkeley, 1995 B.S., Electrical Engineering, Sacramento State University, 1985 Research Interests: Wildland fire behavior and effects Fire ecology and ecosystem interactions Climate change impacts on fire regimes Policy and management of fire-adapted landscapes Scientific Contributions: Stephens has authored or co-authored over 150 peer-reviewed articles, including seminal works on prescribed fire efficacy, forest restoration, and policy reform. His lab’s research has been featured in BioScience , Ecological Applications , and policy briefs for federal agencies. Lab and Collaborations: The Stephens Lab collaborates with Indigenous communities, federal agencies, and international researchers to advance fire science. Notable projects include the Fire and Fire Surrogate Study (FFS) and the Stewardship Project, which advocate for integrating Indigenous burning practices into federal policies.
Samuel W.K. Wong is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a Ph.D. in Statistics from Harvard University (2013) under Prof. Samuel Kou. His research focuses on statistical methodology for complex data science challenges in protein structure modeling, dynamic systems inference, and reliability engineering of wood-based products. He has held academic positions at the University of Florida (2013–2018) and has been at Waterloo since 2018. His research interests include Bayesian computation, statistical inference for dynamic systems, and spatial-temporal data analysis. Notable contributions include the development of manifold-constrained Gaussian processes (MAGI package) and sequential Monte Carlo methods for protein folding studies. He has advised over 15 graduate students and researchers, many of whom are now in academic or industry roles worldwide. Wong has received teaching distinctions at Harvard and holds awards including the Nash Medal (2008) for academic excellence. His work bridges computational statistics with applications in bioinformatics, structural engineering, and environmental science. He has published extensively in top-tier journals like Journal of Computational and Graphical Statistics and Biometrics , and collaborates with wood scientists to improve real-time lumber quality assessment using laser imaging data. His teaching portfolio includes courses on probability theory, statistical inference, and spatial data analysis at both undergraduate and graduate levels. Beyond academia, he maintains an active passion for classical piano performance, having performed recitals combining music with his statistical research interests.
Owen Price is an Associate Professor and Director in Bushfire Risk Management at the School of Earth, Atmospheric and Life Sciences (SEALS), University of Wollongong. His roles include leading research on wildfire impacts on ecosystems, human health, and infrastructure. He holds a PhD from the Australian National University (1998), an MSc from the University of Strathclyde (1986), and a BSc (hons) from the University of York (1985). Director, Centre for Environmental Risk Management of Bushfire (since 2020) Principal Fellow, SEALS (2019–2021) His research integrates fieldwork, GIS/remote sensing, and statistical modeling to address landscape-scale wildfire risks. Key interests include fire severity effects on biodiversity, smoke pollution impacts, and cost-effective fire management strategies. He supervises postgraduate students in topics like coastal wetland vulnerability and fire regime analysis. Recent grants include studies on coastal wetlands' fire resilience (2023–2026), Bayesian fire spread modeling (2023–2026), and evaluating aerial firefighting efficacy (2023). His work bridges ecological, social, and technical dimensions of wildfire risk. Notable awards and recognitions are not explicitly listed in the provided materials. His contributions to fire policy and community adaptation are highlighted through collaborative projects with government and environmental agencies.
