Kate Garbers serves as a Rights Lab Visiting Fellow within the Health and Communities Programme at the University of Nottingham, focusing on evidence generation for anti-slavery policy frameworks through collaborations with the Office of the Independent Anti-Slavery Commissioner and the Anti-Slavery Commissioner's office. Her research critically examines modern slavery survivor rehabilitation , emphasizing the socio-economic impact of employment access for victims and re-trafficking risks in the UK. Key projects include Access to Work for Victims of Slavery and Trafficking and Hope at Home , which analyze systemic barriers to survivor recovery and policy-driven solutions for victim support services. As Founder and former Director of the anti-slavery NGO Unseen, she spearheaded operational strategy for survivor support services while liaising with law enforcement and governmental bodies to advance trafficking intervention protocols. Her work bridges academic research with frontline anti-slavery practice through the Rights Lab’s interdisciplinary framework.
Arkadi Nemirovski is the John P. Hunter, Jr. Chair and Professor at the H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech. He holds a Ph.D. in Mathematics (1974) from Moscow State University, a Doctor of Sciences in Mathematics (1990) from the USSR Supreme Attestation Board, and an honorary Doctor of Mathematics from the University of Waterloo (2009). Ph.D. in Mathematics, Moscow State University (1974) Doctor of Sciences in Mathematics, USSR Supreme Attestation Board (1990) Doctor of Mathematics (Honoris Causa), University of Waterloo (2009) His research focuses on Optimization Theory and Algorithms , with emphasis on complexity analysis, efficient methods for nonlinear convex programs, robust optimization, optimization under uncertainty, and applications in engineering and nonparametric statistics. He has pioneered advancements in interior-point methods, semidefinite programming, and stochastic approximation, shaping modern convex optimization. His article trends highlight a trajectory from foundational interior-point algorithms (1990s) to robust optimization (2000s) and recent works on first-order methods, polyhedral estimates, and applications in machine learning, signal processing, and tomography. Key subfields include matrix norms , large-scale optimization , and stochastic uncertainty handling . Scientific awards include: 1982 Fulkerson Prize (joint with L. Khachiyan and D. Yudin) 1991 Dantzig Prize (joint with M. Grotschel) 2003 John von Neumann Theory Prize (joint with M. Todd) 2017 Member, National Academy of Engineering 2018 Fellow, American Academy of Arts and Sciences 2020 Norbert Wiener Prize (joint with M. Berger) He has supervised students like Dmitry Gabelev (polynomial-time cutting plane algorithms), Daureen Steinberg (matrix norms in robust optimization), and Eitan Rubinstein (SVMs via advanced optimization), with their works later formalized in academic journals.
Vasileios Mavroeidis is an Associate Professor in Digital Security at the Department of Informatics, University of Oslo (UiO). He specializes in security automation and orchestration (SOAR) and cyber threat intelligence (CTI) representation, reasoning, and sharing. He actively contributes to European cybersecurity initiatives, including Horizon Europe, Connecting Europe Facility, and the European Defense Fund, and serves as the primary representative of UiO at the OASIS standards development organization since 2017. Role : Associate Professor Department : Digital Security (SEC), University of Oslo Standardization Involvement : Chairman of OASIS Threat Actor Context (TAC), Leading Contributor to CACAO and OpenC2 Projects : Concordia, CyberHunt, JCOP (Joint Cyber Security Operations Platform), Oslo Analytics, P4C (Partnership for Cybersecurity) His research focuses on cyber threat intelligence (CTI), exploring its taxonomies, sharing standards (STIX, CACAO), and ontologies, with contributions to the European Union Agency for Cybersecurity (ENISA) Cybersecurity Playbooks task force. He analyzes quantum computing's impact on cryptography, develops automated threat detection systems using machine learning (e.g., recurrent neural networks for malware-generated domains), and investigates privacy issues under GDPR. Recent publications highlight his work on LLMs for code stylometry , neurosymbolic AI for cyber defense , and knowledge management systems for CACAO playbooks . His articles span 2017–2025, emphasizing formal verification, biometric data protection, and incident response automation. He collaborates with organizations like OASIS (Threat Actor Context, CACAO, OpenC2) and FIRST (Traffic Light Protocol), and participates in European research projects. His work includes standardization efforts in cybersecurity playbooks , MITRE ATT&CK representation, and quantum-resistant cryptography .
Jim Thatcher is an Assistant Professor at the College of Earth, Ocean, and Atmospheric Sciences (CEOAS) at Oregon State University. He serves as editor of Cartographic Perspectives , a leading journal in cartography. His research focuses on the intersection of technology, society, and environment, particularly examining how data and spatial technologies operate within capitalist systems. Key areas include Critical GIS, Critical Cartography, and Digital Political Ecology. Thatcher's current projects explore equitable coastal flood risk modeling using topological data analysis, mapping infrastructural legacies of slavery in the Pacific Northwest, and creating accessible disaster response maps for non-English speakers in Oregon. He also investigates spectral governance for rural internet access, cartography's societal role, climate education through board games, and geographic influences on electoral districting. His research emphasizes critical approaches to spatial data, questioning representational practices and power dynamics embedded in geospatial technologies. Recent work includes analyzing Bitcoin mining's environmental impacts on hydropower systems and examining the World Bank's renewable energy mapping through Critical Data Studies. Thatcher actively mentors graduate students and encourages interdisciplinary inquiries blending critical social theory with computational methods. Thatcher has authored numerous articles and co-authored Data Power (Pluto Press, 2022), an open-access exploration of data's role in societal control and resistance. His scholarship bridges critical geography with emerging technologies, advocating for ethical and equitable spatial practices in an increasingly data-driven world.
Associate Professor Marcus Cattani is a faculty member at Edith Cowan University (ECU), affiliated with the School of Medical and Health Sciences and the Department of Occupational Health and Safety. He serves as Deputy Director of the WA Government-funded MARS Centre, focusing on Mental Awareness, Respect, and Safety initiatives. Since joining ECU in 2015, he has developed risk management and leadership programs for undergraduate/postgraduate programs and supervises PhD/Master's research. His research emphasizes injury risk reduction in industries like mining, oil/gas, and construction, with recent focus on agriculture safety and radiation exposure in Western Australian mining. Education: Doctor of Philosophy (Occupational Health and Safety), Murdoch University (2004) Master of Science, United Kingdom (1995) Research interests include occupational safety frameworks, real-time exposure assessment, fatigue management, and safety leadership tools. Current projects address critical controls for construction fatalities, radiation exposure in mining, and OHS systems for remote work. Over 30 years of industry experience as an occupational hygienist and HSE consultant informs his academic and applied work. Key collaborations involve government agencies (DMIRS, Water Corporation) and industry partners (Rio Tinto, Lifeline WA). Recent grants include MARS Centre initiatives and NORM exposure studies. His 2025 focus includes translating injury prevention techniques into agriculture contexts. Professional memberships include Australian Institute of Health and Safety (Chartered OHS Professional) and the Australian Institute of Occupational Hygienists.
Dr. Michael Kleeberger is a Researcher at the Chair of Materials Handling, Material Flow, Logistics (FML) at the Technical University of Munich, based at Boltzmannstr. 15 in Garching. He collaborates closely with Prof. Johannes Fottner and maintains an active research profile in crane dynamics and mechanical systems simulation. His research specializes in Materials Handling and Logistics with emphasis on Crane Dynamics, Flexible Multibody Systems, and Control Systems. He develops advanced models for hydraulic actuated cranes, focusing on dynamic behavior during hoisting, slewing, and trajectory operations using port-Hamiltonian formulations and geometrically exact beam theory. His work bridges theoretical mechanics with industrial applications in heavy machinery. Analysis of his 15 most recent publications reveals consistent focus on numerical methods for flexible crane structures, with growing emphasis on optimal control strategies (2020-2025). Key trends include port-Hamiltonian system applications, lunar crane feasibility studies, and vibration mitigation techniques for lattice boom and knuckle boom configurations across diverse operational scenarios. As part of FML, Dr. Kleeberger contributes to TUM's leadership in logistics engineering through industry-collaborative projects and fundamental research in material flow systems, maintaining the chair's reputation for excellence in mechanical dynamics and practical engineering solutions.
Prof. Dr. Raphael Sznitman serves as Director of the ARTORG Center for Biomedical Engineering Research and Head of the Artificial Intelligence in Medical Imaging group at the University of Bern, Switzerland, holding a Full Professor position in AI for Medical Imaging since 2015. Education: PhD in Computer Science, Johns Hopkins University (2011) MSc in Computer Science, Johns Hopkins University (2009) BSc in Cognitive Systems, University of British Columbia (2007) Research Interests: Sznitman's work centers on computational vision , probabilistic methods , and statistical learning applied to medical imaging challenges. His group develops AI algorithms for ophthalmic diagnostics, surgical robotics, and medical image analysis, with emphasis on OCT, surgical phase recognition, and domain adaptation techniques. Key application areas include retinal disease detection and cataract surgery automation. Publication Trends: His 2021-2025 publications reveal concentrated efforts in deep learning for medical imaging , particularly in ophthalmology (OCT analysis) and surgical video understanding. Emerging themes include LLM applications for clinical monitoring, unsupervised out-of-distribution detection for surgical safety, and physics-informed AI for multimodal medical data fusion. Research Leadership: As ARTORG Center Director, Sznitman oversees interdisciplinary research bridging computer science and clinical medicine. His group collaborates extensively with Bern University Hospital clinicians on translational projects, securing funding for AI-driven diagnostic tools and surgical assistance systems. Current initiatives focus on real-time intraoperative guidance and spaceflight ophthalmology applications. Laboratory: The Artificial Intelligence in Medical Imaging group operates within ARTORG's dedicated facilities, maintaining partnerships with surgical robotics labs and ophthalmology departments for clinical validation of AI systems. Their work integrates multimodal data streams including OCT, VR perimetry, and surgical video feeds.
Professor Tolga Akçura is a distinguished faculty member at Özyeğin University's Faculty of Business, Department of Business Administration. With over 25 years of academic experience, he has developed and taught courses on marketing strategy, marketing analytics, and marketing research at prestigious institutions including Carnegie Mellon University, Purdue University, and Long Island University. At Özyeğin University, he teaches Marketing Strategy, Integrated Marketing Communication Strategies, Innovation, Business Model Development, and Advanced Topics in Marketing for undergraduate, graduate, and executive students. Professor Akçura holds a B.Sc. in Industrial Engineering from Boğaziçi University (1990), an MA in Business Administration from Boğaziçi University (1996), an MBA from Carnegie Mellon University (1998), and a Ph.D. in Quantitative Marketing from Carnegie Mellon University (2000). Before joining academia, he worked for Procter & Gamble across multiple European locations including Brussels, London, Manchester, and Istanbul. His research focuses on the intersection of Information Technology and Marketing, Brand Valuation, Consumer Learning Behavior, Structural Choice Models, Brand Equity dynamics, and Competitive Pricing Strategies. Professor Akçura has made significant contributions to marketing science through his extensive publication record in top-tier journals. His recent scholarly work demonstrates a strong trend toward digital marketing, AI applications in marketing analytics, healthcare marketing, and the strategic implications of data-driven decision making. His publications span from foundational work on brand equity to cutting-edge research on patient-generated health data and deep learning applications in campaign participation prediction. William W. Cooper Award (awarded twice for publications in Management Science and Marketing Science) Professor Akçura has successfully bridged academic research with practical business applications through his role as founder of eBrandValue A.Ş. and as a Y-Combinator alum (YCW15). He is an active member of professional organizations including the Institute for Operations Research and Management Science, American Marketing Association, and Direct Marketing Institute. His industry experience complements his academic work, providing students with valuable real-world insights into marketing strategy and implementation.
Jan de Gier is a Professor at the School of Mathematics and Statistics, The University of Melbourne . He is also the Founding Director of MATRIX , Australia’s residential research institute in the mathematical sciences, and a former Deputy Director and Chief Investigator in the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) . Additionally, he co-founded the Australian and New Zealand Association for Mathematical Physics (ANZAMP) in 2011 and served as its inaugural Chair. His research focuses on solvable lattice models at the intersection of mathematical physics and statistical mechanics . Key areas include the application of quantum integrability , algebraic structures like the Yang-Baxter equation, Hecke algebras, and quantum groups, as well as analytical methods such as complex analysis and elliptic curves. His work bridges pure and applied mathematics through connections between enumerative combinatorics , representation theory , and real-world phenomena like traffic flow modeling via exclusion processes . The 15 most recent articles reflect his expertise in integrable systems , non-equilibrium statistical mechanics , and algebraic combinatorics . Topics span Macdonald polynomials , stochastic duality , quantum spin chains , and traffic modeling , with methodologies involving matrix product forms , exact solutions , and critical phenomena analysis. He has contributed to editorial efforts through the AustMS Gazette and MATRIX Annals, and has been involved in public science communication via opinion pieces on mathematics funding and applications. His work emphasizes the importance of fundamental research in driving technological innovation, as highlighted in media articles discussing pi calculation , zero-knowledge proofs , and mathematics education .
Golnoosh Farnadi is an Assistant Professor at McGill University's School of Computer Science and an Adjunct Professor at the University of Montréal. She serves as a Visiting Faculty Researcher at Google, a Core Academic Member at MILA (Quebec Institute for Learning Algorithms), and holds a prestigious Canada CIFAR AI Chair. Farnadi co-directs McGill's Collaborative for AI & Society (McCAIS) and founded the EQUAL Lab (EQuity & EQuality Using AI and Learning algorithms), which focuses on advancing algorithmic fairness and responsible AI. Her educational background includes a Ph.D. in Computer Science from KU Leuven and Ghent University (2017), with postdoctoral research at the University of Montreal/MILA (2018-2020) and the University of California, Santa Cruz (2017-2018). During her doctoral studies, she was a visiting scholar at UCLA, University of Washington, Tsinghua University, and Microsoft Research. Dr. Farnadi's research centers on developing mathematical tools and algorithms for fairness-aware machine learning systems. Her work addresses bias and discrimination in AI decision-making across critical domains including healthcare, criminal justice, financial services, and social media. She has pioneered approaches to ensure fairness in deep learning models, particularly in sequential decision-making under uncertainty. Her research bridges theoretical foundations with practical applications, examining how AI systems can be designed to promote equity while maintaining performance. Analysis of her recent publications reveals a strong focus on practical implementations of fairness mechanisms across diverse AI applications. Her work spans technical domains from generative models and large language models to recommender systems and healthcare optimization. A unifying theme is the development of mathematically rigorous frameworks that balance performance with fairness considerations, with increasing attention to cultural diversity in multilingual AI systems and privacy-preserving fairness approaches. Google Scholar Award (2021) Facebook Research Award (2021) Rising Stars in AI Ethics (2021) Google Award for Inclusion Research (2023) WAI Responsible AI Leader of the Year Finalist (2023) 100 Brilliant Women in AI Ethics (2023) Canada CIFAR AI Chair Dr. Farnadi advises numerous doctoral and master's students across McGill University, University of Montréal, and MILA, with research focusing on fairness, privacy, and responsible AI. Her EQUAL Lab brings together researchers from computer science, social sciences, and policy domains to address systemic challenges in AI ethics. She has secured significant research funding from Google and other major organizations to support her work on fairness-aware AI systems, with applications spanning healthcare, social media safety, and public policy. The EQUAL Lab serves as a hub for interdisciplinary research on algorithmic fairness, bringing together computer scientists, social scientists, and policy experts. The lab's work spans theoretical foundations of fairness metrics, practical implementations in real-world systems, and policy recommendations for responsible AI deployment. Current projects include developing frameworks for fair kidney exchange programs, mitigating cultural stereotypes in multilingual language models, and creating privacy-preserving approaches for detecting online harms while protecting user data.
Jan Skaloud serves as an Adjunct Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC). He holds positions across multiple departments including SSIE (Institute of Earth Surface Dynamics), EDCE (Doctoral Program in Environmental Sciences and Engineering), and leads the Earth Sensing and Observation (ESO) Lab. His office is located at GC C2 397 in the EPFL campus in Lausanne, Switzerland. Dr. Skaloud's research expertise spans satellite positioning, inertial and integrated navigation systems, sensor orientation and calibration, attitude determination, mobile mapping, airborne laser scanning, and Kalman filtering techniques. His work bridges theoretical development with practical applications in UAV navigation, photogrammetry, and remote sensing. He teaches across three EPFL sections and two faculties, demonstrating his interdisciplinary approach to education. His publication record shows consistent contributions to the field, with recent work (2023-2025) focusing on vehicle dynamic model-based navigation for various UAV platforms, including delta-wing and fixed-wing drones. His research demonstrates a clear trajectory toward increasingly sophisticated navigation systems that integrate aerodynamic modeling with traditional sensor fusion approaches. This trend reflects the growing importance of model-based navigation in achieving higher precision and autonomy in UAV operations. 2021: Samuel Gamble Award for career contribution in photogrammetry & sensing (ISPRS) 2020: U.V. Helava Award for best paper in ISPRS Journal (2016-2019) 2017: Best Demo Award at IEEE International Workshop on Metrology & Aerospace 2014: Hansa Luftbild Award for best paper in PFG journal 2012: Karl Kraus Medal for best textbook in Photogrammetry 2009: GNSS Leader to Watch Innovation Award (GPS World) Dr. Skaloud has supervised numerous PhD students whose work focuses on advanced navigation systems, sensor calibration, and UAV applications. His research has received funding for projects involving direct georeferencing, mobile mapping systems, and UAV-based search and rescue operations. The ESO lab he directs serves as a hub for cutting-edge research in Earth observation technologies. The Earth Sensing and Observation Lab under Dr. Skaloud's direction brings together researchers working on navigation systems, sensor integration, and data processing techniques for geospatial applications. The lab maintains strong connections with industry partners and international research organizations, facilitating technology transfer and collaborative research projects.
Aaron Smith is an Associate Professor in the Department of Mathematics and Statistics at the University of Ottawa, affiliated with the Faculty of Science. He holds a PhD from Stanford University. His research focuses on applied probability, computational statistics, Monte Carlo methods, and Markov chains, with an emphasis on advancing theoretical understanding and practical applications of these methodologies. Dr. Smith's work includes contributions to community detection algorithms, Markov chain mixing times, and synthetic health data generation. His recent publications explore topics such as nonstandard Dirichlet form representations, perturbation analysis of MCMC algorithms, and sparse Bayesian multidimensional scaling. He advises students in applied probability and has supervised postdoctoral researchers in related fields. His research interests span a wide range of topics, including stochastic processes, statistical inference, and algorithm design. He is particularly known for his analysis of convergence rates in Markov chains and the development of efficient sampling techniques for complex models. His interdisciplinary work bridges theoretical mathematics and practical computational challenges in data science and healthcare. Dr. Smith collaborates on projects involving synthetic data frameworks for privacy-preserving applications and has contributed to foundational work on mixing times and perturbation effects in stochastic systems.
David Sivak is a Professor and Canada Research Chair Tier 2 in the Department of Physics at Simon Fraser University (SFU). His research focuses on theoretical and computational biophysics, exploring the physical limits of energy and information transduction in molecular machines. He investigates how biological systems operate efficiently under fluctuating conditions, with emphasis on molecular motors, free-energy transduction, and nonequilibrium thermodynamics. Education: Ph.D. in Biophysics, University of California, Berkeley B.A. in Philosophy, Politics & Economics, University of Oxford A.B. with Honors in Applied Mathematics, Harvard University Research Interests: Sivak's work integrates statistical mechanics, information theory, and molecular biophysics to understand how microscopic systems achieve functional efficiency. Key areas include: Optimal control strategies for nonequilibrium systems Energy-information trade-offs in molecular machines Stochastic thermodynamics of biochemical processes Design principles of ATP synthase and similar rotary motors Publications & Awards: Sivak has authored over 60 peer-reviewed articles, including foundational work on nonequilibrium fluctuation theorems and optimal control in stochastic systems. His awards include the Canada Research Chair and the Young Investigator Award from the Biophysical Society of Canada. Grants & Collaborations: He leads projects funded by the Simons Foundation and collaborates with experimental groups globally. His lab actively mentors graduate students and postdocs, emphasizing interdisciplinary approaches to biophysical problems. Labs & Teams: The Sivak Group at SFU develops theoretical models and numerical simulations to analyze molecular-scale processes. Current projects explore information engines, microbiome dynamics, and the thermodynamics of cellular processes.
Elias Passerini is a Researcher at the Institute of Electromagnetic Fields (IEF), ETH Zürich, part of the Department of Information Technology and Electrical Engineering. His work focuses on memristive devices and their applications in neuromorphic computing, photonics, and nanoelectronics. He completed his doctoral thesis on 'Memristors for Neuromorphic Computing' in 2025, exploring volatility control and synaptic response tuning. His research emphasizes atomic-scale memristive systems, three-terminal architectures, and material innovations like Sn alloying for improved device stability. Key contributions include developing versatile nanoscale memristive switches with gate tuning capabilities and demonstrating metamaterial graphene photodetectors with record-breaking bandwidth. Passerini collaborates with the Center for Single-Atom Electronics and Photonics, advancing low-power neuromorphic hardware and optoelectronic integration. His publications span conferences like MEMRISYS and journals such as ACS Nano and Light: Science & Applications .
Constantine (Costa) Samaras is the Trustee Professor of Civil and Environmental Engineering and Director of the Wilton E. Scott Institute for Energy Innovation at Carnegie Mellon University. He is also affiliated with the Department of Engineering and Public Policy and holds a courtesy appointment in the Heinz College of Information Systems and Public Policy. Director, Scott Institute for Energy Innovation Trustee Professor, Civil and Environmental Engineering Affiliated Faculty, Engineering and Public Policy Courtesy Faculty, Heinz College of Information Systems and Public Policy His research focuses on systems engineering approaches to climate resilience , clean energy transitions , and infrastructure security . Key areas include: Transportation electrification and automation Climate adaptation for infrastructure Energy policy under uncertainty AI impacts on energy systems Equity in decarbonization National security implications of energy Costa Samaras co-authored 15 recent studies spanning energy burden analysis, climate hazard indices, AI training energy optimization, and nature-based infrastructure solutions. His work emphasizes transdisciplinary collaboration between engineering, policy, and climate science. Notable scientific recognition includes being named Professor of the Year by the Pittsburgh Section of the American Society of Civil Engineers in 2018. He has led significant policy engagements including White House service (2021-2024) as Principal Assistant Director for Energy and Chief Advisor for Clean Energy Transition. Current affiliations include: Founder/Director, Center for Engineering and Resilience for Climate Adaptation Founder/Director, Power Sector Carbon Index Former Senior Researcher, RAND Corporation (2009-2014) Former Adjunct Senior Analyst, RAND Corporation (2014-2021)
