جست‌وجوی استاد و پژوهشگر

Iva Tolicمشاهده پروفایل

استاد

• Mitotic spindle
• Mitosis
• Biophysics
• +۷ مورد دیگر

Iva Tolic is a Full Professor and Senior Research Group Leader at the Ruđer Bošković Institute in Zagreb, Croatia, with tenure since 2019. She is an elected associate member of the Croatian Academy of Sciences and Arts (2020) and an EMBO member (2018). Her work bridges molecular biology and biophysics to study mitotic spindle mechanics. Education: PhD in Biology (2002, University of Zagreb); Diploma in Molecular Biology (1996, University of Zagreb) Her research focuses on mitotic spindle dynamics, including microtubule sliding, kinetochore forces, and spindle chirality. She employs optogenetics, theoretical modeling, and advanced microscopy to uncover mechanisms preventing aneuploidy in human cells. Recent publications highlight her contributions to understanding spindle mechanics, including microtubule-sliding modules and biomechanics of chromosome alignment. She has secured major grants like the ERC Synergy Grant (2020) and ERC Consolidator Grant (2014). Scientific awards: ERC Synergy Grant (2020), Ignaz L. Lieben Award (2017), National Science Award of Croatia (2015), etc. With over 91 peer-reviewed papers and a Google Scholar h-index of 36, Tolic has delivered more than 150 invited talks globally. She leads interdisciplinary projects integrating microscopy protocols for biomedical research and investigates molecular origins of aneuploidies.

Wenwu Zhuمشاهده پروفایل

استاد

• Big data analysis
• Multimedia communication and networking
• Multimedia computing
• +۵ مورد دیگر

Wenwu Zhu is a Professor and Vice Chair of the Department of Computer Science and Technology at Tsinghua University. He has held prominent positions at Microsoft Research Asia, Intel Research China, and Bell Labs, establishing himself as a leading figure in multimedia computing and networking with international recognition as a FOREIGN member of the Academy of Europe (elected 2018). His educational background includes: Ph.D. in Electrical and Computer Engineering from New York University (1996) Professor Zhu's research focuses on the intersection of multimedia systems, networking, and big data. His work has pioneered advancements in internet video streaming, multimedia cloud computing, and social-aware content distribution. He has made significant contributions to understanding how multimedia content can be efficiently delivered across diverse network environments, from traditional wired networks to modern mobile and social platforms. His research bridges theoretical computer science with practical applications, with his work on social-aware video content distribution being transferred to Tencent company. His publication record shows a clear evolution from foundational work on internet video streaming in the early 2000s, through multimedia cloud computing in the early 2010s, to more recent work on social-aware multimedia and network embedding using deep learning approaches. This progression reflects the changing landscape of multimedia computing from infrastructure-focused to socially-aware and AI-driven systems. Professor Zhu has received numerous prestigious honors: AAAS Fellow (2016) SPIE Fellow (2013) IEEE Fellow (2010) Minister of Education's Natural Science Award, 1st prize (2017) Chinese Institution of Electronics's Natural Science Award, 1st prize (2015, 2012) National Natural Science Award, 2nd prize (2012) Chief Scientist for NSFC Major Project (2016) Chief Scientist for Ministry of Science and Technology's 973 Project (2014) Multiple Best Paper Awards including ACM Multimedia 2012 As Editor-in-Chief of IEEE Transactions on Multimedia since 2017 and through leadership roles as General Co-Chair for ACM CIKM 2019 and ACM Multimedia 2018, Professor Zhu has significantly shaped the multimedia research community. His research has been supported by major grants including NSFC Major Projects and Ministry of Science and Technology's 973 Projects, demonstrating both academic and national strategic importance. He has published over 300 referred papers with an H-Index of 55, including 6 Best Paper Awards and 7 books or book chapters. Professor Zhu leads a research group at Tsinghua University focused on multimedia big data computing, with strong industry connections. His team has made pioneering contributions to structural network embedding using deep learning and social contextual recommendation systems, bridging theoretical advances with practical applications in social media platforms.

Zoran Obradovicمشاهده پروفایل

استاد

• Bioinformatics
• Healthcare informatics
• Data mining
• +۱۲ مورد دیگر

Zoran Obradovic holds the prestigious L.H. Carnell Professorship of Data Analytics at Temple University where he serves as Professor in the Computer and Information Sciences Department and the Statistics Department. He also directs the Center for Data Analytics and Biomedical Informatics and maintains secondary appointments at Temple's Fox School of Business. Internationally, he serves as Research Professor at The Mathematical Institute of the Serbian Academy of Sciences and Arts, and as Visiting Professor at both the School of Medicine and School of Management at the University of Belgrade. His research spans multiple cutting-edge domains of data science: Bioinformatics and protein disorder prediction Healthcare informatics and clinical decision support systems Machine learning for complex networks and big data Spatial and temporal data analytics Applications in healthcare management, social networks, and earth science Dr. Obradovic pioneered research on intrinsically disordered proteins, earning multiple CASP awards. His work addresses challenges related to heterogeneous, spatial, and temporal data analytics with applications across healthcare, power systems, earth science, and social sciences. His research has been funded by prestigious organizations including NIH, NSF, DARPA, DOE, and industry partners. With approximately 450 publications and an H-index of 68 (over 33,000 citations), his scholarly impact is substantial. He serves as editor-in-chief of the Big Data journal and chairs the SIAM Data Mining conference steering committee, reflecting his leadership in the field. Scientific Recognition Elected Member of Academia Europaea (2015) Foreign Member of Serbian Academy of Sciences and Arts (2015) Asia-Pacific Artificial Intelligence Association Fellow (2021) Multiple best paper awards at international conferences Temple University's President's Outstanding Faculty Research Award (2009) Three consecutive CASP awards for protein structure prediction (2002-2006) Dr. Obradovic has mentored approximately 50 postdoctoral fellows and Ph.D. students, many of whom now hold positions at leading academic institutions and tech companies including Amazon, Facebook, IBM, Microsoft, and Uber. He has served on editorial boards for 13 journals and organized numerous international conferences in data mining and bioinformatics. His Center for Data Analytics and Biomedical Informatics develops advanced data science methods addressing real-world challenges in healthcare, science, engineering, and business applications, with active recruitment for Ph.D. students and postdoctoral researchers.

Bernd Witzigmannمشاهده پروفایل

استاد

• Optoelectronic Devices
• III-Nitride Semiconductors
• Quantum Well Simulations
• +۷ مورد دیگر

Prof. Dr. Bernd Witzigmann serves as Chair Holder at the Friedrich-Alexander University Erlangen-Nürnberg (FAU) within the Department of Electrical-Electronic-Communication Engineering and the Institute of Optoelectronics. His research focuses on advanced optoelectronic device modeling, particularly III-nitride semiconductors for ultraviolet applications, THz sensing, and photonic crystal technologies. Research Areas: Optoelectronic Device Physics, III-Nitride Semiconductors, THz Sensing, Quantum Well Modeling Key Projects: DUV AlGaN LEDs, InP/InAsP Nanowire Photodetectors, Germanium Fano-Resonators His work emphasizes computational simulation of carrier transport, polarization-induced doping effects, and optical gain mechanisms, particularly in ultraviolet light-emitting diodes and quantum disc structures. Collaborative studies span CMOS-compatible sensor fabrication and biofunctionalized THz antenna systems. Recent publications highlight advancements in aluminum nitride trenchFETs, multi-color DUV LEDs, and superparamagnetic label detection using micromagnetic models. His team explores subwavelength field effects in photonic crystal cavities and bandwidth optimization for photogated nanowire photodetectors. Located in Raum 01.045 at Konrad-Zuse-Strasse 3/5, Erlangen, Prof. Witzigmann leads research at the intersection of semiconductor physics and nanophotonic applications through both theoretical and experimental approaches.

Henning Bruhn-Fujimotoمشاهده پروفایل

استاد

• Optimization
• Graph Theory
• Operations Research
• +۳ مورد دیگر

Prof. Henning Bruhn-Fujimoto is a faculty member at the Institute for Optimization and Operations Research at Ulm University. His research focuses on graph theory, combinatorial optimization, and discrete mathematics , with notable contributions to Erdős-Pósa properties, cycle packing, and algorithmic graph theory. He teaches courses in mathematical foundations of machine learning and combinatorics. Academic Background: - Habilitationsschrift : Graphs and their Circuits (2009) - PhD Thesis: Infinite circuits in locally finite graphs (2005) - Diploma Thesis: Generating the cycle space by induced non-separating cycles (2001) Research Interests: - Structural graph theory and algorithm design - Optimization in discrete systems - Applications of combinatorial mathematics Thesis Supervision: He regularly oversees bachelor's and master's theses in optimization, graph theory, and related fields. Notable past thesis topics include elevator system optimization, Erdős-Posa properties in graphs, and container ship unloading algorithms. Labs/Teams: His work is centered within the Institute's optimization group, collaborating with researchers on projects involving graph algorithms and combinatorial optimization.

Partha Lahiriمشاهده پروفایل

استاد

• Survey Sampling
• Small-Area Estimation
• Bayesian Inference
• +۳ مورد دیگر

Partha Lahiri is a Professor at the University of Maryland, College Park, holding dual appointments in the Joint Program in Survey Methodology (JPSM) and the Department of Mathematics . He also serves as an Adjunct Research Professor at the Institute of Social Research, University of Michigan, Ann Arbor. Previously, he was the Milton Mohr Distinguished Professor of Statistics at the University of Nebraska-Lincoln. His expertise spans Survey Sampling , Small-Area Estimation , Bayesian and Empirical Bayes Inference , and Resampling Methods . He has advised organizations such as the United Nations Development Program, World Bank, and Gallup, and contributed to panels like the U.S. Census Advisory Committee. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and an elected member of the International Statistical Institute. Research interests include methodological advancements in small area estimation, survey data integration, and statistical linkage. His work emphasizes practical applications in policy and public health, including poverty measurement and pandemic-related studies (e.g., mask effectiveness perception during the pandemic). He has authored influential papers on topics like multi-goal prior selection, probabilistic record linkage, and resampling techniques for uncertainty quantification. His leadership roles, including directing JPSM, highlight his commitment to training future survey methodologists. Awards: ASA and IMS Fellowships, ISI Elected Membership Advisory Roles: U.S. Census Advisory Committee, National Academy of Sciences panels Publications Trends: Focus on small area estimation, Bayesian methods, and policy-relevant applications Grants/Projects: Collaborations with international organizations and academic institutions on statistical methodologies Lahiri’s research bridges theoretical statistics and practical survey challenges, with a strong emphasis on data integration and uncertainty estimation in complex systems.

• Public Health
• Climate Change
• Risk Communication
• +۷ مورد دیگر

Dr. Scott Hanson-Easey is a Senior Lecturer in the School of Public Health at The University of Adelaide, within the Faculty of Health and Medical Sciences. He specializes in social psychology and health risk communication, focusing on how communities perceive and respond to anthropogenic climate change-related health risks. His research emphasizes participatory action research to address inequities in public health practices by centering underserved communities' voices. His expertise spans qualitative and quantitative methods, collaborating with agencies like the Country Fire Authority and SA State Emergency Service. He has published over 65 peer-reviewed articles, focusing on topics such as climate change communication, disaster risk reduction, and migrant/refugee health. His work often intersects with emergency management, cultural competency, and structural factors influencing health outcomes. Key research themes include risk perception, health equity, and community-based participatory approaches. He actively engages with policymakers and stakeholders to translate research into actionable strategies for disaster resilience and public health adaptation. His articles highlight interdisciplinary collaboration across epidemiology, geography, and social policy.

Maria Basterraمشاهده پروفایل

استاد

• Algebraic Topology
• Category Theory
• Homological Algebra
• +۶ مورد دیگر

Maria Basterra is a Professor in the Department of Mathematics and Statistics at the University of New Hampshire (UNH), where she is a core faculty member in Women's Studies. She is actively contributing to both research and teaching in advanced mathematics. Education: Ph.D. in Mathematics, University of Chicago M.S. in Mathematics, University of Chicago B.S. in Mathematics, University of Texas at Austin Her research centers on Algebraic Topology, Category Theory, and Homological Algebra , with deep investigations into E-infinity ring spectra, operads, and topological Hochschild homology. She has made foundational contributions to the homology and cohomology of structured ring spectra and the calculus of functors. A strong advocate for diversity in mathematics, she actively supports the retention and advancement of women in the field, notably through leadership in the Women in Topology (WIT) collaborations. Her recent publications (2015–2018) reflect a sustained focus on homotopy theory, particularly through collaborative projects that explore operads, infinite loop spaces, and stabilization. These works often emerge from interdisciplinary workshops, highlighting her role in fostering research communities. She has been a co-principal investigator on research projects including the MSRI WIT Open Problems Workshop (awarded by the Clay Institute, 2017) and Women in Topology (awarded by BIRS, 2013), and has participated in the Homotopy Harnessing Higher Structures program. Maria Basterra teaches a wide range of courses, including Calculus II, Mathematical Proof, Abstract Algebra, and multiple advanced topics in Topology (MATH 784, 884, 955, 966). Her teaching record extends through 2025, confirming her active status. She advises and mentors students and early-career researchers, particularly through collaborative research initiatives.

• Meteorology
• Atmospheric Science
• Climate Change
• +۴ مورد دیگر

Luiz AT Machado is a researcher affiliated with the Department of Atmospheric Sciences at the Institute of Astronomy, Geophysics and Atmospheric Sciences, University of São Paulo. His work focuses on multiphase chemistry, gas-aerosol-cloud-precipitation interactions, and tropical convection, with extensive experience in meteorology, remote sensing, and field campaigns in the Amazonas region. Education: Undergraduate and Master's degrees from the University of São Paulo (1978-1984); Advanced Studies Diploma in Oceanology and Meteorology from Pierre and Marie Curie University/CNRS, France (1988); Doctor of Life Sciences from Pierre and Marie Curie University/CNRS, France (1989-1992); Post-Doctoral at CNRS, Paris, France (1996-1997). His research spans the structural analysis of cloud clusters, diurnal cycle studies in the ITCZ, and climate change impacts on tropical atmospheric systems. He has supervised 20 Master's students, 21 PhD students, and 10 Post-Docs, with 112 publications in Web of Science and an H-index of 32.

Jeremiah Ben Hellerمشاهده پروفایل

دانشیار

• Homotopy Theory
• Algebraic Geometry
• Algebraic K-Theory
• +۳ مورد دیگر

Jeremiah Ben Heller serves as an Associate Professor in the Department of Mathematics at the University of Illinois at Urbana-Champaign, maintaining an active research program with office location at 362 Altgeld Hall, 1409 W. Green Street, Urbana, IL 61801. He completed his PhD at Northwestern University in 2006, establishing his academic foundation in advanced mathematical research. Dr. Heller's research centers on homotopy theory—spanning classical, equivariant, and motivic frameworks—and its applications to algebraic geometry, particularly algebraic cycles and algebraic K-theory. His work pioneers connections between topological methods and geometric structures, with significant contributions to motivic cohomology and equivariant homotopy theory. Key investigations include cohomological properties of algebraic varieties and K-theoretic constraints on categorical structures. Recent publications demonstrate consistent focus on motivic cohomology over complex numbers, equivariant motivic homotopy theory, and K-theoretic obstructions. These works reveal a trajectory toward unifying homotopy-theoretic techniques with deep geometric problems, particularly through equivariant and motivic lenses. His international collaborations span multiple countries, reflecting broad engagement with the mathematical community. Citation metrics indicate substantial impact, notably 33 citation indexes for his 2019 work on t-structures. Dr. Heller actively advances mathematical knowledge through rigorous publication in top-tier journals, professional networking, and sustained exploration of homotopy-geometry intersections.

Jing Chenمشاهده پروفایل

استاد

• Vegetation Remote Sensing
• Hydrology
• Carbon Cycle
• +۲ مورد دیگر

Jing Chen is a Professor in the Department of Geography at the University of Toronto, with expertise in Physical Geography, Vegetation Remote Sensing, Hydrology, Carbon Cycle, Ecosystem Modelling, and Climate Change. He works at the St. George campus and has published over 400 refereed papers with an H index of 73. Education: PhD from Reading University, UK Research Interests: His work focuses on remote sensing of vegetation traits and quantifying carbon/water cycles in terrestrial ecosystems. Key areas include Vegetation Remote Sensing, Hydrology, Carbon Cycle, Ecosystem Modelling, and Climate Change. His publications address topics like global CO2 fertilization effects, leaf nitrogen allocation, and environmental impacts on pandemics. Article Trends: Recent publications span Ecology, Remote Sensing, and Hydrology, with subfields covering Carbon Cycle dynamics, vegetation modelling, and climate change impacts. He collaborates on global biogeochemical cycles and environmental stressor interactions. Editorial Roles: He serves as Editor-in-Chief of Remote Sensing of Environment and Associate Editor for multiple journals, including Journal of Geophysical Research-Biogeosciences . He also participates in scientific advisory panels in China and the U.S. Administrative Contributions: Previously held roles as Graduate Coordinator at the Centre for Environment (2009-10) and Associate Chair Graduate in the Department of Geography (2012-14).

Johannes Stroebelمشاهده پروفایل

استاد

• Climate Finance
• Household Finance
• Social Network Analysis
• +۷ مورد دیگر

Johannes Stroebel is the David S. Loeb Professor of Finance at the New York University Stern School of Business, where he conducts research in climate finance, household finance, social network analysis, macroeconomics, and real estate economics. He teaches climate finance at undergraduate, MBA, and executive education levels and leads the Climate Finance Initiative. He is also a Research Associate at the NBER, a CEPR Research Affiliate, and a CESifo Research Fellow. He previously served on advisory bodies including the CFTC’s Climate-Related Market Risk Subcommittee and PCAST’s Working Group on Extreme Weather and Financial Risks, and chairs the Academic Advisory Council at the Brookings Institution’s Center on Regulation and Markets. Education: B.A. in Philosophy, Politics, and Economics, Merton College, Oxford Ph.D. in Economics, Stanford University Professor Stroebel's research focuses on how climate risks affect financial markets, the role of social networks in economic behavior, and household financial decision-making. His interdisciplinary work combines big data—especially from Facebook—with economic modeling to explore topics such as social integration of migrants, peer effects in product adoption, and the impact of social capital on economic mobility. He has developed novel measures like the Social Connectedness Index and has published extensively on climate stress testing, biodiversity risk, and long-run discount rates. His recent publications show a strong trend toward integrating environmental and social risks into financial economics, with a particular emphasis on climate transition risks, carbon pricing uncertainty, and biodiversity loss. He frequently collaborates with leading scholars such as Stefano Giglio, Theresa Kuchler, and Raj Chetty. His work is highly policy-relevant, influencing financial regulation and climate risk management. Scientific Awards: 2023 Fischer Black Prize Alfred P. Sloan Research Fellowship Andrew Carnegie Fellowship Multiple best paper and research prizes from AFA, SFS, WFA, and others Professor Stroebel advises governments and firms on managing climate-related financial risks. He has led major research initiatives on climate finance and social connectedness, including large-scale data projects with Facebook. His work with the NBER and Brookings Institution underscores his role at the intersection of academic research and public policy.

David Todemمشاهده پروفایل

استاد

• Biostatistics
• Epidemiology
• Longitudinal Data Analysis
• +۶ مورد دیگر

David Todem is a Professor in the Department of Epidemiology and Biostatistics at Michigan State University. His work focuses on statistical methodology for longitudinal and clustered data, particularly in applications to cancer research and public health. He holds a Ph.D. in Statistics from the University of Wisconsin-Madison, an M.S. in Biostatistics from Hasselt University (Belgium), and an M.S. in Population Health from the University of Wisconsin-Madison. Dr. Todem's research interests include joint models for time-to-event and longitudinal outcomes, non-identifiable models with informative nonresponse, and testing heterogeneity in mixture models. His applied work addresses critical questions in cancer treatment efficacy, maternal-child health, and chronic disease surveillance. He has developed innovative methods for analyzing quality-of-life outcomes in cancer patients and spatial epidemiology of co-infections. Key contributions include the Validation of geospatial health indices Advancements in zero-inflated model testing Development of nonparametric scanning techniques Statistical frameworks for pediatric intervention evaluation He received a prestigious National Cancer Institute K01 award and has collaborated on federally-funded programs improving cardiovascular care in underserved populations. His work spans multiple domains including maternal-fetal medicine, environmental health, and global health equity. Methodological strengths include: Handling non-random missing data High-dimensional feature selection Weakly identifiable model sensitivity analysis Current research emphasizes translating statistical innovations into clinical practice through partnerships with healthcare systems and public health agencies.

• Polymer Chemistry
• Energy Storage
• Organic Electronics
• +۴ مورد دیگر

Kenichi Oyaizu is a Professor in the Department of Applied Chemistry at the Faculty of Science and Engineering, Waseda University, Tokyo. His research spans polymer chemistry, energy storage, and materials science, with a focus on functional polymers for batteries, hydrogen storage, and high refractive index applications. He maintains active collaborations across academia and industry. Professor Oyaizu's research centers on designing polymers with tailored redox properties for energy storage systems, including organic radical batteries and hydrogen carriers. He pioneers high refractive index materials through molecular engineering of hydrogen-bonded networks and sulfur-rich frameworks. His group integrates machine learning with experimental synthesis, utilizing lossless data platforms for materials discovery and optimization in electrochemistry and optical applications. Analysis of his 15 most recent publications (2020-2025) reveals three dominant research trajectories: (1) High-refractive-index polymers leveraging hydrogen bonding and sulfur incorporation for optical devices, (2) Energy storage systems using redox-active polymers for batteries and hydrogen carriers, and (3) Materials informatics approaches applying generative models and quantum-inspired algorithms to accelerate polymer design. These streams demonstrate consistent innovation in structure-property relationships for functional materials. No scientific awards or major honors are documented in the provided materials. Professor Oyaizu leads an active research group mentoring graduate students and postdoctoral researchers in polymer synthesis and characterization. His work receives funding from Japanese national agencies supporting sustainable energy materials and advanced polymer research, though specific grant details are not disclosed in the source text. Current projects emphasize machine learning-driven development of solid-state electrolytes and hydrogen storage polymers. His laboratory operates within Waseda University's advanced materials infrastructure, utilizing specialized facilities for polymer synthesis, electrochemical testing, and optical characterization. The team collaborates with international researchers on battery technologies and participates in university-industry consortia focused on sustainable materials development, with recent projects highlighted in Waseda University News and EurekAlert!.

• Database Systems
• Distributed Data Management
• Concurrency Control
• +۵ مورد دیگر

Alan D. Fekete is a Professor at the University of Sydney's Department of Computer Science, specializing in database systems, distributed data management, and consistency models. His work spans transaction processing, cloud computing, and query optimization, with recent focus on enhancing database concurrency and serializable execution. Key Research Areas: Database Concurrency & Transaction Isolation Multicore Scalability & Distributed Systems Cloud Data Consistency & Replication Query Optimization & NoSQL Performance Recent publications (2023-2025) explore transactional frameworks for analytical interfaces, DB-OS co-design for data ingestion, and mixed isolation levels for serializable execution. Earlier works (2018-2014) address scalable lock managers, coordination avoidance in databases, and consistency properties in cloud storage. He has contributed to educational initiatives, including a data-centric computing curriculum (2021) and teaching threading concepts (2008). Collaborations include co-authors like Nancy Lynch, Uwe Röhm, and Joseph Hellerstein.