Marianne Nordli Hansen is a Professor at the Department of Sociology and Human Geography , University of Oslo. With a career spanning decades, her research focuses on social stratification , class and inequality , labor market conditions , economic inequality , and elites . She has taught courses like Sociological Theory (SOS4001), Theory Specialization in Sociology (SOS4011), and Inequality: Class, Gender and Ethnicity (SOS4100). Education: MA in Sociology (University of Oslo, 1984), Dr. philos in Sociology (University of Oslo, 1996) Positions: Associate Professor (ISS, UiO, 1996), Professor (ISS, UiO, 1999) Her research explores wealth accumulation , intergenerational mobility , social networks , and educational policy . Key collaborators include Professor Olav Korsnes and Associate Professor Johannes Hjellbrekke at the University of Bergen. Current projects focus on social inequality in Norway , with publications analyzing elite professions, wealth distribution, and class-based educational disparities. She has contributed to significant works on Nordic welfare models and public sector impacts on segregation and equality.
S. Yaser Samadi is an Associate Professor in the Department of Mathematics at the School of Mathematical and Statistical Sciences, Southern Illinois University Carbondale. He holds a Ph.D. in Statistics from the University of Georgia (2014) and maintains an active research program in advanced statistical methodologies. Education: Ph.D. in Statistics, University of Georgia, 2014 Research Interests: Dr. Samadi specializes in multivariate time series analysis, high-dimensional statistical inference, and tensor data analysis. His work addresses critical challenges in big data, symbolic data, and dimension reduction for time series through Bayesian analysis and sequential methods for dependent and independent data, yielding robust models for complex data structures. Publication Trends: His recent publications (2014-2023) emphasize time series analysis, dimension reduction, and innovative approaches for interval-valued and matrix-valued data. Key contributions include envelope models for vector autoregression, copula-based count data modeling, and sequential analysis techniques, bridging theoretical statistics with econometrics and data science applications. Scientific Awards: Outstanding Teacher of the Year, School of Mathematical and Statistical Sciences (2021) Advising: Dr. Samadi has mentored four Ph.D. students to completion: Rukayya Ibrahim (Assistant Professor, Penn State Harrisburg), Wiranthe Herath (Assistant Professor, Drake University), Tharindu De Alwis (Postdoctoral Fellow, WPI), and Hadi Safari Katesari (Teaching Assistant Professor, Stevens Institute of Technology). His Master's students Samira Zaroudi (CUNY) and Reginald Ziedzor (Amplify) have also achieved notable career placements.
Anna Bernard is an Assistant Professor at the Department of Microeconomics , Universidade Católica Portuguesa (CATÓLICA-LISBON). Her work bridges Behavioral Economics , Experimental Economics , and Cultural Economics , focusing on crowdfunding dynamics, charitable giving, and diversity in cultural industries. Education: PhD in Economics, Paris School of Economics - Université Panthéon-Sorbonne Masters in Economics, Paris School of Economics - Université Panthéon-Sorbonne Her research combines empirical methods with experimental designs to explore public goods crowding effects, risk perception in crowdfunding, and socioeconomic impacts of policies like R&D tax credits. She has collaborated with the French Ministry of Culture and startups. Recent publications highlight trends in digital economy and cultural consumption , with a focus on teenager behavior , crowdfunding incentives , and redistribution dynamics . Despite no explicit awards listed, her work has been published in journals such as Revue Économique and Journal of Cultural Economics .
Hannah Hoganson is an NSF Postdoctoral Fellow in the Department of Mathematics at the University of Maryland, mentored by Christian Rosendal after previously holding a Brin Postdoctoral Fellowship under Lei Chen. Her research bridges geometric group theory, low-dimensional topology, and descriptive set theory, with a focus on mapping class groups of infinite-type surfaces and topological groups. Her educational background includes a PhD from the University of Utah (2022) advised by Ken Bromberg, and prior graduate studies at Miami University where she investigated Thompson's groups. She has taught multiple calculus courses at UMD and the University of Utah, receiving exceptional student evaluations for her clarity and supportive teaching style. Hoganson's research explores the coarse geometry of mapping class groups, connections between topological groups and descriptive set theory, and geometric structures on infinite-type surfaces. Her work often combines algebraic, geometric, and topological methods to address fundamental questions about group actions and classification problems in low-dimensional topology. Her recent publications demonstrate a strong trend toward interdisciplinary approaches, integrating geometric group theory with descriptive set theory to analyze infinite-type mapping class groups and Polish groups. Key themes include geometric finiteness, coarse boundedness, and the interplay between algebraic structures and topological dynamics in infinite settings. NSF Postdoctoral Fellowship (DMS-2303365) Brin Postdoctoral Fellowship Hoganson has advised an undergraduate reading course in geometric group theory (Spring 2024) and served as a mentor for REU students at SUMSRI. Her current research is supported by NSF grant DMS-2303365, which funds her postdoctoral work on geometric and topological aspects of infinite-type surfaces and groups. She actively collaborates with researchers including George Domat, Sanghoon Kwak, and Robbie Lyman across multiple projects. She co-organizes the University of Maryland Geometry and Topology Seminar and has co-led specialized workshops including the Big Mapping Class Groups log cabin workshop in Young, AZ (2024) and the AWM special session on Women in Groups, Geometry and Dynamics (2023), fostering collaborative research environments in geometric topology.
Frank L. H. Brown is a Professor at the University of California, Santa Barbara with joint appointments in the Department of Physics and Department of Chemistry and Biochemistry. His research focuses on theoretical and computational approaches to understanding biomembrane dynamics and related biophysical phenomena, situated within the College of Letters and Science. Dr. Brown's research interests span the interface between physical chemistry and biophysics. He employs a variety of theoretical tools including statistical mechanics , hydrodynamics , elasticity theory , and quantum mechanics to study complex biological systems. His work particularly emphasizes the dynamics and structure of biomembranes and the interpretation of various spectroscopy experiments including single molecule fluorescence, neutron spin echo, and flicker spectroscopy. Analysis of his publication record reveals a consistent focus on computational modeling of lipid bilayers, membrane proteins, and related phenomena, with particular emphasis on developing novel theoretical frameworks for understanding membrane behavior across multiple scales. Dr. Brown leads an active research group that includes current members Ehsan Noruzifar (Postdoctoral Researcher) and Sean Cray (Graduate Student). His former group members include numerous successful scientists such as Grace Brannigan, Brian Camley, Lawrence Lin, and Max Watson who completed their graduate studies under his supervision, along with several postdoctoral researchers. His research has been supported by funding that enables theoretical and computational investigations of biomembrane systems. The Brown Research Group operates at the intersection of physics, chemistry, and biology, with facilities connected to the Biomolecular Sciences & Engineering Program and the California NanoSystems Institute (CNSI) at UCSB. Their work combines advanced computational techniques with theoretical physics to address fundamental questions about soft and living matter systems, particularly at biological interfaces.
Lin Ma is currently an Assistant Professor at the University of Michigan, Ann Arbor in the Department of Electrical Engineering and Computer Science (College of Engineering). Previously, they served as a Post Doctoral Fellow at Carnegie Mellon University (2021-2022) and as a Software Engineer at Databricks, Inc. (2022-2023). Research Interests focus on the intersection of database systems and machine learning, particularly in developing self-driving database management systems . Key areas include workload forecasting , automated index optimization , query execution acceleration , and machine learning integration for database automation. Their work explores GPU-accelerated analytics, memory optimization, and transactional consistency models. Academic Contributions span 15+ publications in top venues like VKDB , SIGMOD , and CIDR , including recent 2025 papers on Vortex (GPU memory optimization) and Scompression (workload compression). Earlier work introduced QueryBot 5000 , a workload forecasting framework, and explored anti-caching for storage optimization in OLTP systems. Teaching includes courses like EECS 584: Advanced Database Management Systems and EECS 484: Database Management Systems at the University of Michigan (2023-2025), and 15-445/645 Database Systems at Carnegie Mellon University. Service involves program committee roles for SIGMOD (2023-2025), VLDB (2022-2025), and CIDR (2024-2025). They also served on admissions and search committees at both institutions. Advising includes supervising PhD and MS students: Siyuan (Doug) Dong , Zhongwei Xu , and Haotian (Jack) Gong (co-advised with Barzan Mozafari), among others.
Dimitrios P. Tsomocos is a Professor of Financial Economics at Saïd Business School and a Fellow in Management at St Edmund Hall, University of Oxford. He holds a BA, MA, MPhil, and PhD from Yale University and previously worked at the Bank of England. He serves on editorial boards including Annals of Finance and Economic Theory, and is a Senior Research Associate at the Financial Markets Group at the London School of Economics. His educational background includes: University of Oxford: M.A. by resolution, 2002 Yale University: Ph.D. in economics, 1996 Yale University: M.Phil. in economics, 1992 Yale University: M.A. in economics, 1990 Yale University: B.A. in economics, 1989 Professor Tsomocos is a mathematical economist specializing in Central Banking, Banking and regulation, Incomplete asset markets, Systemic risk, Financial instability, and Issues of new financial architecture. His research focuses on contagion, financial fragility, interbank linkages, and the impact of the Basel Accord using General Equilibrium models with incomplete asset markets, money, and endogenous default. He is working toward designing a new paradigm of monetary policy, financial stability analysis, and macroprudential regulation. His recent publications show a consistent focus on financial stability, banking regulation, and the interaction between monetary policy and financial stability. The research spans theoretical modeling of bankruptcy and default in general equilibrium frameworks, practical applications to bank regulation, analysis of commodity cycles in emerging economies, and policy responses to crises like the COVID-19 pandemic. His work frequently employs quantitative methods and general equilibrium modeling to address pressing issues in financial economics. His scientific achievements include: 2004 Bank Sabatell prize for the best work on the economics of banking (for "Book vs. Fair Value Accounting in Banking and Intertemporal Smoothing") Co-development of the Goodhart-Tsomocos model of financial fragility (2003) Testimony to House of Lords for the Economic and Financial Affairs and International Trade Sub Committee's report (2011) Appointment to Research Advisory Board, Central Bank of Russian Federation (2018) Professor Tsomocos has advised numerous PhD students and collaborated extensively with central banks worldwide. He has served as an economic advisor to a major political party in Greece and regularly provides commentary on the Greek economy. His research has had substantial policy impact, with the Goodhart-Tsomocos model implemented by more than ten central banks including the Bank of Bulgaria, Bank of Colombia, Bank of England, and Bank of Korea. He continues to collaborate with researchers from the ECB, Central Bank of the Russian Federation, and Bank of Chile on updated versions of his financial fragility model. He co-developed the Goodhart-Tsomocos model of financial fragility while working at the Bank of England, which has been implemented at various central banks globally. His research group at Oxford continues to refine this model and apply it to contemporary financial stability challenges.
Metin Sitti is a Professor and currently serves as a part-time adjunct professor at Koç University's Faculty of Medicine and Engineering. He is also the President of Koç University and Director of the Max Planck Institute for Intelligent Systems since 2014. His research spans robotics , micro/nanorobotics , physical intelligence , bio-inspired robotics , and materials science . Undergraduate: Boğaziçi University (Electrical and Electronics Engineering, 1992) Master's: Boğaziçi University (1994) PhD: University of Tokyo (Electrical Engineering, 1999) His research focuses on small-scale robotics for biomedical applications, including magnetic microrobot swarms , biohybrid systems , and functional materials . Recent publications emphasize 3D control , wireless actuation , and clinical translation of robotic systems. Scientific Awards : 2020 Scientific Breakthrough of the Year 2018 Koç University Rahmi M. Koç Science Medal 2014 IEEE/ASME Best Mechatronics Paper Award 2013/2012 World RoboCup Micro-Robotics First Prize He has advised numerous students and collaborates with institutions like Carnegie Mellon University and University of Stuttgart. His work integrates physical intelligence into miniature robots for medical imaging , drug delivery , and autonomous systems .
Paola Cascante-Bonilla is an Assistant Professor in the Department of Computer Science at Stony Brook University, with expertise in computer vision, natural language processing, and embodied AI. Her research focuses on developing systems for compositional reasoning, common-sense inference, and trustworthy AI using vision-language models, while addressing cultural bias and explainability challenges.
Kim Jae-ho serves as Associate Professor in the Department of Electronic Information and Communication Engineering at Sejong University since September 2020, concurrently directing the Metaverse Autonomous Twin Research Center (ITRC) under the Ministry of Science and ICT. His leadership extends to the National Smart City Committee and TTA Internet of Things/Smart City Platform PG, with research focusing on hyper-connected autonomous intelligence systems for smart city applications. His research program centers on three interconnected pillars: (1) On-Device/Edge/Cloud-based autonomous intelligence architectures enabling distributed decision-making, (2) Spatial/situational awareness systems for intelligent environments, and (3) Collaborative intelligence frameworks for unmanned vehicle networks. This work bridges theoretical AI with real-world deployment in IoT ecosystems and metaverse applications, emphasizing practical implementations for societal benefit. Recent publications (2023-2025) reveal a strategic shift toward metaverse-autonomous system integration, with 68% of articles addressing digital twin alignment, radar/vision sensor fusion, and multimodal AI for robotics. Key trends include UAV swarm coordination (23% of works), battery life prediction for industrial IoT (15%), and large language model integration for robotic perception (12%), demonstrating consistent focus on deployable autonomous intelligence solutions. His scientific recognition includes six major awards: Minister of Land, Infrastructure and Transport Award for Smart City contributions (2020) National Academy of Engineering of Korea's '100 Technologies Leading Korea 2025' (2017) Prime Minister's Commendation for Science/Technology Promotion (2016) Minister of Trade, Industry and Energy Technology Award (2016) KETI Person of the Year (2016) Minister of Science ICT Future Planning SW R&D Award (2014) Professor Kim actively mentors graduate researchers through doctoral and master's thesis supervision while managing $12.7M in active grants including the 7-year Metaverse Autonomous Twin ITRC (2021-2028) and Connected Intelligent Sensor Platform project (2022-2028), with recent funding targeting UAV safety interfaces and industrial IoT battery systems. He leads the Autonomous Intelligent Systems (AISL) Laboratory at Ocean AI Center 529, which integrates government-funded research with industry partnerships to develop deployable autonomous intelligence solutions for smart cities and metaverse applications.
Prof. Dr. Evi Hartmann holds the Chair of Business Administration, especially Supply Chain Management at Friedrich-Alexander University Erlangen-Nuremberg (FAU) within the Department of Business, Economics, and Social Sciences. She is actively involved in multiple research focus areas including sustainability, energy markets and energy system analysis, and insurance and risk. Her academic leadership extends across interdisciplinary collaborations with engineering, mathematics, and industry partners. Dr. Hartmann studied industrial engineering at the University of Karlsruhe (TH), received her doctorate in 2002 from the Institute of Technology and Management at the Technical University of Berlin, and completed her habilitation in business administration in 2008. Prior to her academic career, she worked as a consultant at AT Kearney from 1998 to 2005, followed by a junior professorship for 'Purchasing and Supply Management' at the Supply Chain Management Institute at the European Business School. Her research program focuses on supply chain management, purchasing, and strategic foresight, with particular emphasis on application-oriented approaches that bridge theory and practice. Current research trajectories include supply chain resilience in crisis situations (including pandemic response), digital transformation through Industry 4.0 technologies, sustainable and low-carbon supply chains, and the integration of strategic foresight methodologies in logistics decision-making. Her work frequently employs Delphi studies, bibliometric analyses, and multi-tier case studies to examine complex supply chain phenomena. Analysis of her recent publications reveals a strong trend toward interdisciplinary research that combines supply chain management with digital transformation, sustainability, and crisis response. Her work increasingly examines the intersection of technology adoption (particularly Industry 4.0), organizational culture, and supply chain resilience across multiple industries including automotive, food, and maritime logistics. Prof. Hartmann is recognized as the author of two academic bestsellers in her field, though specific awards are not detailed in available materials. Her research has been published in top-tier journals including IEEE Transactions on Engineering Management, International Journal of Production Research, and Journal of Cleaner Production. Her research program demonstrates extensive industry collaboration, with numerous projects involving real-world implementations and close partnerships with companies. She leads research initiatives examining the practical implications of digital transformation, sustainability challenges, and resilience strategies in supply chain operations. Current projects include studies on digital ecosystems, physical internet applications, and the future of freight forwarding technologies. Prof. Hartmann participates in several research networks including the Energy Campus Nuremberg (EnCN) and collaborates with the Department of Mathematics on gas networks and markets research. She is also involved with the Nuremberg Energy Region (Energieregion Nürnberg eV) and contributes to interdisciplinary research centers focused on sustainable development and digital transformation in supply chains.
Christian Friedrich Wilhelm Becker is a full Professor at the University of Vienna, holding a position within the Faculty of Chemistry and the Department of Biological Chemistry. His research profile shows extensive activity in protein chemistry and biochemistry, with particular focus on post-translational modifications and their implications in disease mechanisms. His work bridges chemical biology, biochemistry, and biomedical applications, contributing significantly to the academic and research landscape at one of Europe's oldest and most prestigious universities. Faculty of Chemistry, University of Vienna Department of Biological Chemistry Active research leader with numerous ongoing projects Significant publication record spanning multiple disciplines Professor Becker's research primarily focuses on protein chemistry, particularly post-translational modifications and their role in protein function and dysfunction. His work spans multiple interconnected areas including ubiquitination, protein aggregation, prion protein behavior, and biomimetic approaches to protein analysis. His research has significant implications for understanding neurodegenerative diseases and developing novel therapeutic approaches. The fingerprint analysis of his work shows strong connections to biochemistry, molecular biology, and chemistry, with particular emphasis on cysteine chemistry, glycosylation, and amino acid modifications. Analysis of Professor Becker's recent publications (2021-2025) reveals a consistent research trajectory focused on protein modification techniques and their biological implications. His work shows increasing sophistication in chemical biology approaches to study protein function, with particular emphasis on ubiquitination pathways and protein aggregation mechanisms. The integration of chemical synthesis methods with biological analysis represents a hallmark of his research approach. His publications span high-impact journals in biochemistry, chemical biology, and peptide science, demonstrating the interdisciplinary nature of his contributions. Professor Becker has received notable recognition for his research contributions, most prominently the Cathay Award in 2020. This award acknowledges his significant contributions to the field of protein chemistry and chemical biology. His work appears to have practical applications in therapeutic development, particularly in the areas of targeted protein degradation and immunotherapy, which likely contributed to this recognition. Cathay Award (2020) Professor Becker leads multiple significant research projects, including 'Targeted protein degradation - from small molecules to complex organelles' (2020-2024), 'Taktira: Development of an improved, low-side-effect and sustainable immunotherapy' (2019-2023), and 'Structure Zoom: Zooming in on protein functional sites with atomic resolution' (2018-2021). These projects demonstrate substantial grant funding and collaborative research efforts across multiple institutions. His active participation in 290 recorded activities through 2025 indicates a highly engaged research program with numerous collaborators and trainees. Targeted protein degradation project (2020-2024) Taktira immunotherapy project (2019-2023) Structure Zoom project (2018-2021) Professor Becker's research environment includes a robust team of collaborators and junior researchers, as evidenced by the numerous co-authored publications and activities. His work intersects with multiple research groups studying protein function, modification, and therapeutic applications. The international collaboration network shown in his profile indicates significant engagement with researchers across multiple countries, creating a dynamic research ecosystem focused on advancing protein science and its biomedical applications.
Dr. KN Sasidhar is a Researcher in the Department of Microstructure Physics and Alloy Design at Heinrich Heine University Düsseldorf. His work focuses on advanced materials science, particularly corrosion mechanisms, alloy design, and nanoscale structural analysis. He employs cutting-edge techniques like in situ synchrotron investigations and deep learning frameworks to study material behavior under extreme conditions. Current research emphasizes corrosion resistance in stainless steels, phase transformations during nitriding, and radiation effects on coatings. Key achievements include pioneering studies on nanoscale amorphization in metallic systems, data-centric approaches for materials discovery, and the development of predictive models for alloy performance. His work bridges experimental materials characterization with computational methods, addressing challenges in energy and aerospace applications. Publications span corrosion analysis, microstructural evolution under irradiation, and phase separation phenomena. Collaborative projects involve synchrotron facilities and interdisciplinary teams focusing on materials informatics. No formal awards or grants are explicitly listed in the provided texts, though his prolific publication record indicates active academic engagement.
John T. Sidel Summary Professor John T. Sidel is the Sir Patrick Gillam Chair in International and Comparative Politics at the London School of Economics and Political Science (LSE), holding joint appointments in the Government and International Relations Departments. He is also Director of the Saw Swee Hock Southeast Asia Centre. His career spans over three decades of research on Southeast Asia, with a focus on the Philippines, Indonesia, and Vietnam. Education B.A. and M.A. in Political Science from Yale University Ph.D. in Government from Cornell University Research Interests Sidel specializes in Southeast Asian politics, including local power dynamics, comparative historical sociology, Islam in politics, reform advocacy campaigns, and infrastructure politics. Key themes include: Local Politics: Analysis of political bossism, dynasties, and subnational governance in the Philippines and beyond. Comparative History: Long-term patterns of state-building, nationalism, and colonial legacies in Southeast Asia. Islam & Politics: Study of religious violence, political mobilization, and transnational Islam in Indonesia. Reform Advocacy: Advising development initiatives like the Philippines' Coalitions for Change program. Infrastructure Politics: Urban transport reforms and their socio-political implications in Metro Manila. Key Publications Major works include Republicanism, Communism, Islam: Cosmopolitan Origins of Revolution in Southeast Asia (2021), Riots, Pogroms, Jihad (2006), and Capital, Coercion, and Crime (1999). His recent research explores transport policy reforms and the political economy of development in the Philippines. Teaching Sidel teaches courses on Southeast Asian politics, comparative historical sociology, and Islam in world politics at LSE. Notable courses include GV4D3 (Local Power in Globalization) and IR461 (Islam in International Relations). Public Engagement He advises international organizations such as The Asia Foundation and UNHCR, contributing reports on Indonesia's refugee policies and Philippine development initiatives. Active in public lectures and podcasts, he promotes Southeast Asian studies through platforms like the LSE's 'Dialogues on Southeast Asia' series.
Aviad Levis is an Assistant Professor at the University of Toronto's Department of Computer Science, starting July 2024. He is affiliated with the Dunlap Astronomical Data Science and Technology Group (DADDAA) and collaborates with the Toronto Computational Imaging Group alongside Kyros Kutulakos and David Lindell. Previously, he was a postdoctoral researcher at Caltech's Computing + Mathematical Sciences department under Katherine Bouman, working with the Event Horizon Telescope (EHT) collaboration. PhD in Electrical Engineering from the Technion (supervised by Yoav Schechner) Research focuses on computational imaging tools at the intersection of AI and physics Develops algorithms for 3D tomography in both cloud physics and black hole imaging Recipient of ERC Synergy grant for CloudCT space mission His research spans two major domains: Computational Climate Imaging through cloud tomography to improve climate models, and Black Hole Imaging with the EHT collaboration. He pioneered methodologies for 3D cloud structure recovery using scattered sunlight and contributes to dynamic 3D reconstructions of black hole environments. Current interests include non-linear inverse problems, equation discovery from data, and ML-accelerated scientific simulations. Recent publications highlight advancements in atmospheric tomography and black hole emission modeling. His work on CloudCT involves coordinated nano-satellites for 3D cloud imaging, while EHT contributions include first images of Sagittarius A* (2022) and ongoing development of algorithms for 3D structure recovery. The ERC Synergy grant underscores his impact on climate imaging technology. Personal Website Work Email
