Mahvish Ahmad is an Assistant Professor in Human Rights and Politics at the London School of Economics and Political Science (LSE) , affiliated with the Department of Sociology. She previously held a Mellon Postdoctoral Fellowship at the University of the Western Cape's Centre for Humanities Research. Her PhD in Sociology from Cambridge University focuses on state violence in Balochistan, Pakistan. Research Interests: Her work critically examines state violence, militarism, decolonial theory, and anti-imperial thought. Core themes include: State destruction mechanisms in Balochistan Archiving marginalized resistance movements Leftist periodicals as counterhegemonic tools Transnational solidarity networks Teaching: Convenes courses on Lawful Violence and Contemporary Politics of Human Rights . Integrates anti-colonial perspectives into curricula. Key Projects: Sovereign Destruction : Explores state demolition of alternative social orders in Balochistan. Thought Under Siege : Recovers grassroots movement thought from banned materials. Co-convenes Archives of the Disappeared (with scholars at UWCape and SA). Publications: Over 20 peer-reviewed articles and edited volumes, including works in Radical History Review , Surveillance & Society , and South Asian History and Culture . Recent focus on Balochistan's conflict dynamics and global South periodicals.
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.
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.
Yuri Levin is a Professor at the Smith School of Business, Queen’s University, where he holds the Stephen J.R. Smith Chair of Analytics and serves as Founding Executive Director of the Smith School of Business Analytics and AI. He also leads the Scotiabank Centre for Customer Analytics. His research focuses on Analytics & AI, with expertise in revenue management, dynamic pricing, and strategic consumer behavior. Levin holds a Ph.D. in Operations Research from Rutgers University and degrees in Economics and Applied Mathematics from Belarus State University. Levin’s academic contributions include co-winning the 2013 INFORMS Revenue Management and Pricing Practice Prize and the 2009 INFORMS COIN-OR Cup. He has advised companies like Scotiabank, Loblaws, and McDonald’s on pricing strategies and consumer analytics. As an Associate Editor of Operations Research , he shapes academic discourse in operations research and pricing strategies. Education: Ph.D. in Operations Research, RUTCOR, Rutgers University (2001) B.S. in Economics, Belarus State University (1998) M.S. (Honours) in Applied Mathematics, Belarus State University (1998) His research explores dynamic pricing models under social influence, strategic consumer behavior, and revenue management in hospitality and retail industries. He has pioneered methodologies for optimizing pricing strategies in networked markets and developed algorithms for cargo capacity management. Awards: 2010 Queen’s School of Business Award for Research Achievement 2003 New Researcher Achievement Award Levin’s teaching spans MBA, Master of Management Analytics (MMA), and executive education programs, covering analytical decision-making and pricing optimization. His advisory work includes roles as a Visiting Professor at the Skolkovo Moscow School of Management and the University of Cambridge’s Judge School of Business.
Professor Luke Prendergast is the Deputy Dean of the School of Computing, Engineering & Mathematical Sciences (SCEMS) at La Trobe University (LTU) and holds a Professorship in the Department of Mathematics and Statistics. He previously served as Head of Department (2014–2020) and led LTU's Statistics Consulting Platform. His research focuses on robust statistics, meta-analysis, dimension reduction, and applied statistics, leading the DRAMA research group. Collaborations span fields like endocrinology, disability studies, and respiratory health. He actively contributes to research grants, including projects on Prader-Willi syndrome and exercise for disability populations. Professor Prendergast's recent work emphasizes statistical software development (e.g., the rquest package) and applications in biostatistics, such as metabolomics analysis and health intervention fidelity. His articles address topics like quantile-based hypothesis testing, geospatial accessibility for disability care, and motivational interviewing efficacy. Professional roles include NHMRC grant review panels, editorial boards for Nutrients and Respirology , and leadership in the Statistical Society of Australia (SSA Vic). His teaching includes courses in meta-analysis, linear models, and data-based critical thinking. Grants funded projects on exercise programs for cerebral palsy populations and community-university partnerships for disability inclusion. Luke's work bridges statistical theory with real-world health challenges, emphasizing robust methodologies and interdisciplinary collaboration.
Yves Wautelet serves as an Associate Professor at the Faculty of Economics and Business at KU Leuven, where he conducts research in conceptual modeling, business process management, and digital transformation. His work addresses critical challenges at the intersection of information systems engineering and business strategy, with particular focus on sustainability-driven modeling approaches and IT governance frameworks. His primary research interests include: Conceptual modeling methodologies and frameworks Business process management and information systems design Digital transformation strategies and implementation IT governance and business-IT alignment Sustainability-driven modeling for circular economy Agile software development practices and methods Requirements engineering with user stories Wautelet's recent publication record demonstrates significant scholarly productivity with numerous 2024-2025 publications spanning conceptual modeling frameworks for sustainability (Circulise), tools for identifying ambiguity in user stories (AmbiTRUS), and approaches to align strategic and operational agility. His work bridges theoretical foundations with practical applications across diverse domains including healthcare, circular economy, software development, and organizational transformation. His research consistently applies model-driven approaches to solve complex real-world problems, often integrating sustainability considerations into information systems engineering. As a promotor and co-promotor, Wautelet currently supervises multiple doctoral research projects including: Automatic generation of conceptual models from textual descriptions (2024-2028) Sustainability-Driven Modeling Assistant for Twin Transition in Vietnam (2024-2028) Home Care Business Process Management using Distributed Ledger Technologies (2024-2028) Teaching Modeling Skills in BPMN formalism (2021-2025) His research is conducted through the Information Systems Engineering Research Group (LIRIS) at KU Leuven's Brussels campus, where he contributes to advancing model-driven approaches for addressing contemporary business and technological challenges.
Filip Biljecki is an Assistant Professor jointly appointed at the Department of Architecture within the College of Design and Engineering and the Department of Real Estate at the NUS Business School, National University of Singapore. He is the founder and principal investigator of the NUS Urban Analytics Lab and was awarded the prestigious NUS Presidential Young Professorship in 2020. With over 150 peer-reviewed publications, his research bridges geomatic engineering, geospatial technologies, and urban data science to advance digital twins and data-driven urban planning. Dr. Biljecki's educational background includes: PhD in 3D GIS (cum laude), Delft University of Technology, Netherlands (2017) MSc in Geomatics, Delft University of Technology, Netherlands (2010) BSc in Geodesy and Geoinformatics, University of Zagreb, Croatia (2008) His research interests focus on emerging urban data sources, particularly urban imagery, and their application in 3D city modeling, digital twins, and GeoAI. He explores how crowdsourcing and open science can inform cutting-edge techniques for urban sensing and analytics at city-scale. His work significantly contributes to establishing smart cities through innovative methods that integrate recent advancements in computer science, geomatics, and urban data science. Analysis of his recent publications reveals a strong focus on street view imagery applications for urban analytics, digital twin development, and geospatial AI. His research spans multiple domains including urban morphology, environmental assessment, public health applications, and urban comfort analysis. The interdisciplinary nature of his work is evident in collaborations with researchers from diverse fields, producing impactful studies that address complex urban challenges through innovative methodological approaches. His notable scientific achievements include: Annual Teaching Excellence Award (ATEA), 2025 College Educator Award AY2023/2024, 2025 Urban Informatics Paper of the Year Award, 2023 Top 2% scientists worldwide (Stanford University), 2021 Presidential Young Professorship (NUS), 2020 As an educator, Dr. Biljecki has supervised dozens of students leading to publications in leading journals and placements at top universities and organizations. He has delivered talks at over 120 universities and organizations worldwide including MIT, Stanford, Harvard, and ETH Zurich. His research is supported through various grants and affiliations including his role as Principal Investigator at the Future Cities Lab Global at the Singapore-ETH Centre. The NUS Urban Analytics Lab, which he established, brings together scholars from diverse disciplines to drive research on making cities smarter and more data-driven. The lab has developed innovative tools like ZenSVI for street view imagery analysis and has produced influential research on urban digital twins, urban morphology, and GeoAI applications. Through his leadership, the lab continues to pioneer methods that advance data-driven urban planning and smart city development.
Prof. Mathias Drton holds the Chair of Mathematical Statistics at the Technical University of Munich (TUM), within the Department of Mathematics and School of Computation, Information and Technology. His research focuses on graphical models, algebraic statistics, causal inference, and multivariate data analysis. He has authored numerous publications in top-tier journals and conferences, including work on conditional independence, sparse factor analysis, and causal discovery in linear models. Drton has supervised a large number of theses, mentoring students in areas like high-dimensional statistics, graphical models, and causal inference. He is actively involved in teaching advanced courses such as 'Graphical Models in Statistics' and 'Fundamentals of Mathematical Statistics.' His academic contributions span theoretical developments in statistical methodology and computational tools, including R packages like SEMID and symRC . Drton collaborates internationally, contributing to projects like the TUM-ICL Mathematical Sciences Hub and Exzellenzcluster MCQST. His work bridges algebraic methods with statistical challenges, addressing identifiability in latent variable models and robust graphical modeling under non-Gaussian assumptions. Recent research emphasizes causal structure learning under partial homoscedasticity, distribution-free independence tests, and multi-domain causal representation learning. Drton’s lab actively explores applications in genomics, epidemiology, and machine learning, leveraging both theoretical rigor and practical computational methods.
Summary Clotilde Coron is a Full Professor of Management Sciences at the Faculté Jean Monnet, Université Paris-Saclay. She previously held an Associate Professor position at IAE Paris (2017–2022). Her research focuses on gender equality, gender stereotypes, and the role of quantification in HR management. She earned a PhD in Management Sciences (Université Paris-Est, 2015) and a HDR (Université de Poitiers, 2021). She is also a graduate of ENSAE (2012) and Sciences Po (2013). Academic Roles: Full Professor, Université Paris-Saclay Vice-President for Equality, Diversity, and Inclusion (since 2024) Elected member of the Research Committee (since 2024) Co-responsible for the M1 Master in Management (since 2023) Research Interests: Dr. Coron’s work critically examines gender equality policies, the societal impact of gender stereotypes, and the ethical implications of algorithmic HR practices. She emphasizes the need for organizations to adopt intersectional frameworks to address systemic inequalities. Grants and Projects: ANR funding for lesbian workplace inclusion (2024–2025) Research on gender in health innovation (2023–2024) Studies on chatGPT in education and LGBTQ+ mental health (2023–2024) Awards: EFMD-FNEGE Best Research Book Award (2023, 2019) FNEGE Label for multiple academic contributions Teaching: She teaches advanced courses in quantitative methods, HR analytics, and gender studies at undergraduate and graduate levels. Recent courses include Data Analysis Tools (M1), Quantitative Methods (M2), and distance-learning modules on HR management.
Javier Franco Aixelá **Roles and Affiliations**: Full Professor of Translation and Interpreting at the University of Alicante, Director of the Department of Translation and Interpretation (2017–2021). Coordinates the Master's in Institutional Translation (Legal and Economic). Active in teaching Translation Theory, Professional Ethics, and Advanced Literary Translation. **Education**: PhD in English Philology (University of Alicante, 1996), Licenciatura in English Philology (Complutense University of Madrid, 1986), Expert in Translation (Complutense University of Madrid, 1991). **Research**: Specializes in translation theory, cultural aspects of translation, and bibliometrics. Founded the BITRA database (70,000 entries by 2017), a comprehensive online bibliography on translation and interpreting. Recent focus on bibliometric analysis of translation studies, including advertising translation, open access in academia, and cognitive approaches. **Teaching**: Taught courses like Professional Ethics, Advanced Literary Translation, and Translation of Research Genres. Supervised over 125 theses in the last five years, including high-impact works on medical neologisms (Habiba Chbab El Fakhi) and gender-neutral translation (María López Medel). **Awards**: Coordinator of the University of Alicante's Translation Doctoral Program, which received a quality distinction from the Ministry of Education. His theses have been awarded "Excellent Cum Laude" by the university. **Projects**: Led competitive research projects such as the 2021–2025 bibliometric study on economic translation and the BITRA database expansion (2007–2010). Collaborated on international initiatives like the 5th ICEBFIT Conference (2023). **Publications**: Authored 40+ books (e.g., *La traducción condicionada de los nombres propios*), co-edited *ENTI: Encyclopedia of Translation and Interpreting*, and published widely in journals like *META* and *Translation & Interpreting*.
Rong Pan is a Professor at the School of Computing and Augmented Intelligence, Arizona State University (ASU). He holds a Ph.D. in Industrial Engineering from Pennsylvania State University (2002), an M.S. from Florida A&M University (1999), and a B.S. in Materials Science from Shanghai Jiao Tong University (1995). His research focuses on quality and reliability engineering, design of experiments, time series analysis, and statistical learning theory. Key projects involve NSF-funded research on reliability prediction, accelerated life testing, and degradation modeling. He serves as an Associate Editor for the Journal of Quality Technology and has authored over 80 publications. Courses taught include Reliability Engineering, Design of Experiments, and Statistics for Data Analysts. His academic service includes roles as a referee for IEEE Transactions and IIE journals. Research interests emphasize statistical methods for reliability improvement, with recent work on Bayesian inference models, optimal experimental design, and machine learning applications in industrial systems. Grants include collaborations with the NSF, Arizona Department of Transportation, and Science Foundation Arizona. His work bridges theoretical advancements and practical applications in manufacturing, energy systems, and semiconductor reliability. Education: Ph.D. (2002), M.S. (1999), B.S. (1995) Key Research Areas: Reliability Engineering, Bayesian Methods, Time Series, DOE Active Grants: NSF CMMI, SUNY IT Visiting Scholar Program Teaching: IEE 573 Reliability Engineering, DSE 501 Statistics Service: Journal of Quality Technology (Associate Editor), IEEE Transactions (Referee)
Dr. Basak Tas is a Research Fellow at King's College London, based in the Institute of Psychiatry, Psychology & Neuroscience within the Department of Addictions Sciences. She has been working at King's since 2014, initially as a PhD student and then as a Post-doctoral Research Associate, before taking up her current role in 2021. Her work focuses on opioid overdose and related interventions, collaborating with Professor Sir John Strang and Dr. Will Lawn. Her educational background includes an undergraduate degree in Neuroscience from King's College London and an MSc in Neuroscience from the University of Edinburgh. She completed her PhD at King's College London under the supervision of Professor Sir John Strang, Dr. Caroline Jolley, and Dr. James Bell. Her PhD thesis was titled "Clinical and Laboratory Investigation into Heroin and Opioid Overdose Risk". Dr. Tas's research centers on opioid overdose mechanisms, opioid use disorder treatments, and health interventions to reduce drug-related deaths. She investigates experimental drug studies and develops wearable technologies for overdose detection. Her work aims to understand the physiological underpinnings of overdose and create practical tools for real-world overdose prevention, particularly in high-risk populations. Her recent publications (2020-2025) focus on innovative approaches to prevent opioid overdose deaths, including wearable biosensors (e.g., PneumoWave) and mHealth technologies. She explores risk factors for respiratory depression and the acceptability of detection devices among people who use opioids. Her work bridges laboratory models of overdose with clinical applications in supervised injecting facilities and community settings. Dr. Tas was awarded the following scientific award: Addictions Clinical Academic Group (CAG) Early Career Research Prize (2022) She contributes to teaching by supervising MSc Addiction Studies projects and teaching in the BSc Psychology "Addictions" and "Choices" modules. Additionally, she has been involved in public engagement, including school workshops and the art-science project "Heroin Bodies". Dr. Tas is part of the Drugs Research Group within the Addictions Department at King's, led by Professors John Strang and John Marsden. Her current work involves collaboration on projects related to opioid overdose and wearable technologies.
Amanda Giang serves as Assistant Professor at the University of British Columbia's Faculty of Applied Science, Department of Mechanical Engineering, holding a Canada Research Chair in Environmental Modelling for Policy. She maintains a joint appointment with the Institute for Resources, Environment and Sustainability (IRES). Her educational background includes a B.A.Sc. from the University of Toronto, followed by M.S. and Ph.D. degrees from MIT, with postdoctoral training at MIT and Harvard. Dr. Giang's research employs interdisciplinary approaches to develop modeling tools for environmental policy analysis, focusing on pollution assessment, environmental injustice, and the intersection of air quality, decarbonization, and equity. Her work emphasizes action-oriented partnerships with community organizations and government health/environment agencies. Current projects address freight transport decarbonization equity, cumulative impact assessment methodologies for overburdened communities, and holistic environmental impact evaluation in technology design. Her recent publications demonstrate expertise across environmental modeling, policy analysis, and justice frameworks, with significant contributions to understanding spatial inequities in environmental risk distribution and developing community-engaged research methodologies. UBC Killam Research Prize, 2023 Dr. Giang actively collaborates with community groups and government authorities through her LEAP (Learning, Environmental Assessment, and Policy) research group. Her work integrates technical modeling with real-world policy applications, particularly in urban environmental planning contexts where equity considerations are paramount. She has developed innovative frameworks for cumulative impact assessment and environmental justice analysis that directly inform regulatory decision-making processes. Her research laboratory focuses on developing open-source modeling tools for environmental policy analysis while maintaining strong community partnerships that ensure research addresses pressing local environmental justice concerns.
Aysha Hidayatullah is an Associate Professor in the Department of Theology and Religious Studies at the University of San Francisco's College of Arts & Sciences. She teaches undergraduate courses focusing on gender, sexuality, race, ethics, and religious studies within Islamic traditions. PhD, Religious Studies, University of California, Santa Barbara, 2009 MA, Religious Studies, University of California, Santa Barbara, 2005 BA, Women's Studies and English, Emory University, 2001 Her research explores feminist exegesis of the Qur'an , constructions of gender and sexuality in Islamic traditions , and the body in Islamic ritual practices . She also examines literary representations of Muslims, particularly through feminist theological frameworks and methodologies in Islamic studies. Key themes in her publications include interfaith collaboration , Qur'anic hermeneutics , and gendered narratives in Islamic history . Her work addresses intersections of religion, gender, and race in both historical and contemporary contexts. 2023, Collective Achievement Award, University of San Francisco 2019, James Catiggay Changemaker Award, University of San Francisco 2017, Distinguished Teaching Award, University of San Francisco & Faculty Association 2016-2017, Dean's Scholar Award, College of Arts and Sciences 2015, Ignatian Service Award, University of San Francisco
Andreas Winkler is an Assistant Professor in the Department of Near & Middle Eastern Civilizations at the University of Toronto's Faculty of Arts and Science. Prior to his current appointment, he held teaching and research positions at the University of California, Berkeley; Freie Universität Berlin; University of Oxford; and University of Warsaw. His office is located at 4 Bancroft Avenue, Room 421, Toronto, ON, M5S 1C1, with contact email andreas.winkler@utoronto.ca and phone 416-865-2513. Education: PhD, Uppsala University Winkler specializes in the history and philology of Greco-Roman and Late Antique Egypt, with expertise in Demotic and Coptic manuscripts. His research examines the history of science—particularly astral sciences—alongside social history, religious practices, and onomastics across Egyptian history. He integrates written evidence with material culture and art, focusing on interdisciplinary analysis of ancient texts and artifacts. His methodological approach combines philological rigor with historical contextualization to explore cultural transitions in ancient Egypt. Analysis of Winkler's 13 publications from 2022-2025 reveals dominant themes in ancient Egyptian astronomy, astrology, and magic, with recurring focus on Demotic/Coptic manuscripts. His work bridges philology and social history, examining topics like horoscopes, zodiacs, marriage practices, and temple economies. Publications span major academic presses including Brill, De Gruyter, and University of Chicago Press, demonstrating consistent contributions to understanding scientific traditions and daily life in Roman and Late Antique Egypt.
