جست‌وجوی استاد و پژوهشگر

Stefan Helmreichمشاهده پروفایل

استاد

• Anthropology of Science
• Oceanography
• Sound Studies
• +۳ مورد دیگر

Stefan Helmreich is the Elting E. Morison Professor of Anthropology at MIT, where his research examines how scientists conceptualize fundamental phenomena—especially waves—across oceanography, biology, acoustics, and computing. His interdisciplinary work bridges anthropology, science studies, and media theory. Core research themes include: Cultural and scientific constructions of ocean waves Marine microbial ecologies and alien oceans Sound studies and transduction theories Multispecies ethnography Scientific visualization practices Helmreich's publications demonstrate consistent engagement with wave phenomena as both physical forces and cultural symbols, exploring how scientific representations of waves shape environmental understanding. His award-winning books trace connections between marine science, cosmology, and media technologies. He has received numerous prestigious awards including a Guggenheim Fellowship and multiple book prizes from anthropological associations. Helmreich maintains creative collaborations through projects like 'Wave Count'—a musical exploration of wave representations across genres.

Andrew Ollettمشاهده پروفایل

دانشیار

• Poetics
• History of Literature
• Intellectual History
• +۹ مورد دیگر

Andrew Ollett is an Associate Professor and Director of Graduate Studies in the Department of South Asian Languages and Civilizations at the University of Chicago , where he has taught since 2019. His research focuses on the literary and intellectual traditions of South and Southeast Asia, particularly through works in Sanskrit, Prakrit, Apabhramsha, and Kannada from the first millennium CE. Co-founder and editor of NESAR (New Explorations in South Asia Research) Director of NEH-funded edition/translation of the Kavirājamārga (earliest Kannada literary manual) Expert in Prakrit and Kannada literary traditions His work explores the 'question of language'—examining how language choice shaped cultural production and change in premodern India. Current projects include a monograph on context-sensitivity in Indian language theories and a study of manuscript technology's impact on early South Asian knowledge communities. He has authored The Mirror of Ornaments (Naples: Unior Press, 2025) and Language of the Snakes (UC Press, 2017), and co-authored Lilavai (Harvard, 2021). Recent publications include interdisciplinary studies on: Sanskrit-Prakrit campū genre reevaluation Pragmatics in Mīmāṁsā interpretive concepts Manuscript literacy's influence on literary forms Historical linguistics of Middle Indic syllable reduction Philosophy of language in Śālikanātha and Kumārila Bhaṭṭa Awarded the NEH 'Scholarly Editions and Translations' grant , he teaches classical South Asian literature courses covering Sanskrit, Prakrit, and Tamil traditions. He maintains digital resources including a Prakrit Digital Texts Project and Mīmāṁsādigdarśinī digital text repository, and actively contributes to open-access scholarship.

Jonathan A. Kelnerمشاهده پروفایل

استاد

• Algorithms
• Spectral Graph Theory
• Combinatorial Optimization
• +۷ مورد دیگر

Jonathan A. Kelner is a Professor of Applied Mathematics in the Department of Mathematics at the Massachusetts Institute of Technology (MIT) and a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on applying techniques from pure mathematics to solve fundamental problems in algorithms and complexity theory, with the goal of developing practical algorithms for real-world questions. Dr. Kelner received his undergraduate degree from Harvard University and his Ph.D. in Computer Science from MIT in 2006. Before joining the MIT faculty, he spent a year as a member of the Institute for Advanced Study. His educational background has provided a strong foundation for his interdisciplinary research spanning mathematics and computer science. His research interests include combinatorial optimization, mathematical programming, spectral graph theory, distributed computing, machine learning, computational geometry and topology, computational biology, signal processing, and random matrix theory. Kelner's work demonstrates how deep theoretical insights can lead to practical algorithmic improvements, particularly in graph algorithms and optimization problems. His approach often involves connecting seemingly disparate areas of mathematics to create novel algorithmic techniques. Analysis of his recent publications reveals a strong focus on spectral graph theory, optimization algorithms, and the Sum-of-Squares method. His work frequently addresses fundamental questions in theoretical computer science with practical implications for algorithm design. A notable trend in his research is the development of nearly-linear-time algorithms for various graph problems, which represents significant improvements over previous approaches. NSF CAREER Award Alfred P. Sloan Research Fellowship NEC Award for Research in Computers and Communication Sprowls Doctoral Dissertation Award Best Student Paper Award at STOC 2004 Best Paper Award at STOC 2011 Kokusai Denshin Denwa Junior Faculty Chair 2008 Harold E. Edgerton Faculty Achievement Award 2011 School of Science Award for Excellence in Undergraduate Education 2012 Professor Kelner has been actively involved in mentoring students and has received recognition for his teaching excellence, including the School of Science Award for Excellence in Undergraduate Education in 2012. His research has been supported by prestigious grants including the NSF CAREER Award. He has collaborated extensively with researchers across multiple institutions, often working with other leading figures in theoretical computer science to produce groundbreaking results in algorithm design. At MIT, Kelner is part of both the Mathematics Department and CSAIL, positioning him at the intersection of theoretical mathematics and practical computer science. This dual affiliation reflects the interdisciplinary nature of his work, which bridges pure mathematical theory with concrete algorithmic applications.

Jonathan P. Wongمشاهده پروفایل

استاد

• Military Strategy
• Military Acquisition and Procurement
• Military Budgets and Defense Spending
• +۱۳ مورد دیگر

Jonathan P. Wong is a Senior Policy Researcher at the RAND Corporation and Professor of Policy Analysis at the RAND School of Public Policy. His work bridges academic research and defense policy, focusing on military strategy, acquisition, force planning, and the integration of emerging technologies into military operations. Education: Ph.D. and M.Phil. in Policy Analysis (Pardee RAND Graduate School), M.A. in Security Studies (Georgetown University), B.A. in Political Science (UC San Diego) Professional Experience: U.S. Marine Corps infantry officer (2001–2011), Consultant at Boston Consulting Group, current RAND researcher and professor Wong’s research interests center on defense innovation, military logistics, artificial intelligence in warfare, space capabilities, and the human dimension of military operations. He has led studies on human-machine teaming, non-lethal weapons, defense acquisition reform, and U.S. military posture in the Indo-Pacific. His work emphasizes practical, policy-relevant insights grounded in operational experience. The trends in his recent publications reveal a deep engagement with modern defense challenges: integrating commercial technologies into military systems, improving acquisition agility, enhancing battlefield awareness, and ensuring that defense innovation serves warfighter needs. His research spans strategic, operational, and tactical levels, often focusing on the U.S. Army and Marine Corps. Wong has not received public recognition in the form of listed awards in the provided texts, but his leadership in congressionally mandated studies and high-impact policy research suggests significant influence in defense circles. Advising & Grants: Co-led major projects such as the Long Range Precision Fires study and research on integrating women into Marine Corps infantry. His work is frequently funded by the Department of Defense and other federal entities, though specific grant details are not listed. Wong is affiliated with RAND’s defense and national security research teams, contributing to strategic analysis and policy development. He is not associated with a formal lab but works within RAND’s collaborative research environment, often partnering with other veterans and defense experts to produce actionable insights for military leaders and policymakers.

Michael Woywodeمشاهده پروفایل

استاد

• SME Research
• Entrepreneurship
• Family Firms
• +۵ مورد دیگر

Professor Dr. Michael Woywode is a full professor and holds the Chair of SME Research and Entrepreneurship at the University of Mannheim , within the Business School . His research and teaching are embedded in the Institute for SME Research and Entrepreneurship (ifm Mannheim) , a central research institute of the university, and the Mannheim Center for Entrepreneurship and Innovation (MCEI) , which offers entrepreneurship courses university-wide. Research Interests: Family Firms: Succession planning, leadership transitions, and post-succession innovation. Entrepreneurship: Founder behavior, startup ecosystems, and entrepreneurial decision-making. Digitalization in SMEs: Competitiveness, digital transformation, and innovation in small and medium-sized enterprises. Self-Employment & Labor Markets: New forms of self-employment and their societal implications. Teaching: Prof. Woywode teaches across Bachelor’s, Master’s, and Doctoral levels, offering courses such as Strategic and International Management , Introduction to Entrepreneurship , and Managing the Family Business . Research Output: His recent publications span high-impact journals including Organization Science , Family Business Review , and Journal of Small Business Management , with a clear focus on entrepreneurship, family business, and institutional theory. Team & Collaboration: He leads a multidisciplinary team including postdocs, PhD candidates, and research associates, working closely with the MCEI and ifm Mannheim to foster entrepreneurship research and education.

• Human-Computer Interaction (HCI)
• Quantitative HCI
• Mixed Reality
• +۴ مورد دیگر

Jay Henderson is an Assistant Professor in the Department of Computer Science at Memorial University of Newfoundland, leading the Human-Computer Interaction (HCI) Lab. His research focuses on quantitative HCI, measuring human performance with emerging technologies such as mixed reality and generative AI. He holds a PhD from the University of Waterloo and has held roles including Postdoctoral Fellow at Carleton University and Senior Research Scientist at Huawei Technologies Canada. Education: PhD in Computer Science, University of Waterloo (2021) BSc Hons in Computer Science (minors in Mathematics and Psychology), Mount Allison University (2016) Research Interests: Henderson’s work bridges computer science with psychology and mathematics, emphasizing objective measurement of user interactions. Key areas include mixed reality productivity, generative AI interfaces, gesture-based input, and multimodal feedback systems. His quantitative approach ensures practical insights for technology design. Key Grants & Awards: NSERC Discovery Grant ($155,000 over 5 years) NSERC Discovery Launch Supplement ($12,500) David R. Cheriton Graduate Scholarship ($20,000 over 2 years) Teaching & Supervision: Teaches courses like COMP 4303 (AI for Games) and supervises multiple graduate and undergraduate researchers. Notable supervisees include Daniel Jo (MSc) and Arunav Saha (BSc Honours). Service Contributions: Served on ACM committees including Graphics Interface and CHI Late Breaking Work. Acted as Virtual Chair for ACM ASSETS 2024 and contributed to ACM’s name change policy as a transgender advocate.

• Data Analytics
• Artificial Intelligence Applications in Power Systems
• Renewable Energy Integration
• +۳ مورد دیگر

Anamitra Pal is an Associate Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His work focuses on power system resilience, renewable energy integration, and time-synchronized measurement analytics. He leads research initiatives combining artificial intelligence with grid modernization challenges. Ph.D. Electrical Engineering, Virginia Tech (2014) M.S. Electrical Engineering, Virginia Tech (2012) B.E. Electrical and Electronics Engineering, Birla Institute of Technology (2008) Prior to ASU, Pal conducted postdoctoral research at Virginia Tech's Network Dynamics and Simulation Science Laboratory (2014-2016). His research interests center on enhancing grid stability through: Advanced synchrophasor data analytics AI-driven power system security frameworks Renewable generation integration strategies Critical infrastructure protection during extreme events Recent publications demonstrate his focus on grid resilience during wildfires, deep learning-based state estimation, and innovative PMU applications. Pal has received multiple accolades including the NSF CAREER Award (2022) and IEEE Phoenix Section's Outstanding Young Professional Award (2019).

• Urban morphology
• Urban design
• Street layout and network structure
• +۵ مورد دیگر

Stephen Marshall is Professor of Urban Morphology and Urban Design at The Bartlett School of Planning, University College London. He also served as Visiting Professor at the Department of Architecture and Urban Studies, Politecnico di Milano, Italy from 2019 to 2021. With over twenty-five years of experience in the built environment fields, initially in consultancy and subsequently in academia, Professor Marshall has established himself as a leading expert in urban morphology and design. His educational background includes a Doctor of Philosophy from University College London (2001), a Postgraduate Diploma from Edinburgh College of Art (1995), a Master of Science from the University of Leeds (1989), and a Bachelor of Engineering from the University of Glasgow (1988). Professor Marshall's principal research focuses on urban morphology and street layout, examining their relationships with urban formative processes including urban design, coding and planning. His work bridges urban design theory with practical applications, exploring how cities evolve through complex interactions of physical form, social processes, and planning interventions. He has written or edited several influential books including 'Streets and Patterns' (2005), 'Cities, Design and Evolution' (2009), and 'Urban Coding and Planning' (2011). His recent publications reveal a growing interest in applying complexity science to urban morphology, with particular attention to biological analogies for understanding self-organizing cities. He has pioneered research on digital participation methods in urban planning, exploring how online platforms can enhance public engagement in urban space design. His work consistently bridges theoretical urban morphology with practical applications for contemporary urban challenges like pandemic adaptation and sustainable transport. Professor Marshall has served as Chair of the Editorial Board of Urban Design and Planning from its launch to 2012, and is now co-editor of Built Environment journal. His editorial work has significantly shaped scholarly discourse in urban planning and design. He leads several significant research initiatives including the Incubators of Public Spaces project, which explores digital platforms for co-creating urban spaces, and the Self-Organising Built Environment project, which investigates biological analogies in urbanism. These projects reflect his interdisciplinary approach to understanding and shaping urban environments, connecting with Sustainable Development Goal 11 (Sustainable Cities and Communities).

Stephan Schmidtمشاهده پروفایل

دانشیار

• Urban Spatial Patterns
• Land-Use Policy
• Regional Planning
• +۶ مورد دیگر

Stephan Schmidt is an Associate Professor at Cornell University's College of Architecture, Art and Planning, affiliated with the Department of City and Regional Planning. His research bridges urban spatial patterns, planning institutions, and sustainability outcomes across Europe, sub-Saharan Africa, and China. Education: PhD in Urban Planning from Rutgers University MS in Landscape Architecture from the University of Washington His work examines: land-use policy evolution in Europe; urbanization dynamics in African cities; and polycentricity trends in Chinese metropolises. Recent studies focus on climate risk mitigation through urban form, including urban heat island effects and air pollution in German regions. Key trends in his 2024-2022 publications: comparative analysis of polycentric urban systems; GIS-based spatial pattern evaluation; and institutional impacts on sustainable development. Awards include Cornell's Global Strategic Collaboration Award and German Academic Exchange Service grants. Scientific Awards: Cornell Global Strategic Collaboration Award (2024) Cornell Center for Social Sciences Accelerated Research Grant (2024) German Academic Exchange Service (2019) Advising includes mentoring graduate students like Juan Fernandez, Justin Peng, and Hassan Yakubu on projects analyzing urban morphology. His lab investigates intersections between spatial patterns and environmental outcomes, including climate change adaptation in Tanzanian cities and park fragmentation in German metropolises.

Frederick A. A. Kingdomمشاهده پروفایل

استاد

• Perception
• Cognition and Cognitive Neuroscience
• Spatial Vision
• +۸ مورد دیگر

Frederick A. A. Kingdom is a Professor in the Department of Ophthalmology at McGill University's Faculty of Medicine, focusing on Perception, Cognition and Cognitive Neuroscience . His research explores the interplay between early visual feature detection (edges, bars) and intermediate stages forming contours, textures, and surfaces through spatial vision, color vision, stereopsis, texture perception, brightness/lightness perception, and transparency studies . Email: fred.kingdom@mcgill.ca Key research domains include: Perceptual Mechanisms : Lateral inhibition, contrast normalization, spatial bandpass filters, and their role in brightness/lightness perception and illusions like simultaneous brightness contrast. Color Vision : Red-green vs blue-yellow system distribution, chromatic contrast requirements for stereopsis, color-based depth processing limitations, and color-shading effects that parse surfaces vs illumination. Texture Analysis : Detection thresholds for orientation/frequency/contrast modulated textures, co-circularity in texture perception, and texture statistical sensitivity (e.g., kurtosis importance). Shape Processing : Shape-frequency/shape-amplitude aftereffects, global vs local shape coding, and contour inflection adaptation. His work combines psychophysics , fMRI , image processing , and computational modeling to dissect visual system architecture, particularly how color and luminance signals are integrated/separated in early cortical processing.

• Voltage instability prediction
• Electricity markets
• Stochastic optimization
• +۵ مورد دیگر

Professor Gregor Verbic is a faculty member at the University of Sydney in the School of Electrical and Computer Engineering , where he serves as Director of the Centre for Future Energy Networks . Previously, he held an assistant professor position at the University of Ljubljana and was a NATO-NSERC Postdoctoral Fellow at the University of Waterloo. His career spans academic research, industry leadership as Head of Interenergo's Investment Department, and extensive collaboration with IEEE. PhD in Electrical Engineering (University of Ljubljana) Senior IEEE Member Research Interests focus on transforming power systems to zero-carbon grids through: Aggregation and control of distributed energy resources (DERs) Frequency control with wind generation and electric vehicles Stochastic optimization for multi-energy systems Smart home energy management with phase change materials Notable Contributions include: 2006 IEEE prize paper for voltage instability prediction 2010-2024: 15 recent publications on DER coordination, network tariffs, and low-inertia grid stability Teaching includes courses on: ELEC3203/ELEC9203: Electricity Networks ELEC5213: Engineering Optimisation ELEC5206: Sustainable Energy Systems Labs & Initiatives Centre for Future Energy Networks The Net Zero Institute

Bryon Aragamمشاهده پروفایل

دانشیار

• Causality
• Statistical Machine Learning
• Probabilistic Modeling
• +۶ مورد دیگر

Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.

• Dynamical systems
• Ergodic theory
• Homogeneous spaces
• +۴ مورد دیگر

Manfred Einsiedler is a Professor in the Department of Mathematics at ETH Zurich, Switzerland, with office HG G 64.2 at Rämistrasse 101, 8092 Zurich. He teaches undergraduate and graduate courses including Linear Algebra (HS 2019), Analysis I/II, and Functional Analysis I/II, using his co-authored textbook Functional Analysis, Spectral Theory, and Applications . His research centers on dynamical and equidistribution problems in homogeneous spaces, with focus on closed horocycle orbits, geodesic orbits on the modular surface, and measure rigidity. Key contributions include work on effective equidistribution, entropy methods, and connections between ergodic theory and number theory. He has co-authored foundational texts: Ergodic Theory with a view towards Number Theory and Functional Analysis, Spectral Theory, and Applications in Springer's Graduate Texts in Mathematics series, alongside multiple in-progress volumes on entropy, homogeneous dynamics, and unitary representations. Recent publications explore integer points on spheres, rigidity of invariant measures, and Diophantine approximation on fractals, emphasizing collaborations with Lindenstrauss, Ward, Margulis, and Venkatesh. His work demonstrates consistent focus on homogeneous dynamics with applications to arithmetic problems, particularly through effective methods and measure classification theorems. While no specific awards or student lists are documented in the source, his extensive publication record and textbook authorship establish significant scholarly impact.

• Materials Science
• Chemical Engineering
• Energy Storage
• +۳ مورد دیگر

Mo Jiang is a Researcher in the Department of Chemical & Life Science Engineering at Virginia Commonwealth University's College of Engineering. His research focuses on advanced crystallization processes for energy storage materials and pharmaceutical manufacturing. He specializes in continuous manufacturing techniques such as slug-flow reactors, aiming to improve material uniformity, scalability, and process efficiency. His work bridges chemical engineering principles with practical applications in battery technology and drug substance development. Research Interests: Continuous crystallization and manufacturing systems Slug-flow synthesis of battery cathode materials Process optimization for pharmaceuticals and energy storage Scalable synthesis of uniform microcrystals His recent articles highlight advancements in low-cobalt/cobalt-free lithium-ion battery cathodes, pharmaceutical crystallization methods, and the application of computational fluid dynamics to enhance manufacturing processes. These studies emphasize improving material performance, reducing costs, and achieving sustainable production methods. While no formal academic awards are listed, his prolific publication record demonstrates expertise in interdisciplinary engineering solutions. He collaborates on projects involving process design, real-time monitoring, and the integration of advanced manufacturing technologies.

Ardalan Vahidiمشاهده پروفایل

استاد

• Optimal Control and Estimation
• Energy Efficient Mobility
• Connected and Automated Vehicles
• +۲ مورد دیگر

Ardalan Vahidi is a Professor of Mechanical Engineering at Clemson University, joining in 2005 after receiving his Ph.D. from the University of Michigan. His research focuses on optimal control, energy-efficient mobility, connected and automated vehicles, and human bioenergetics during exercise. Education: Ph.D. Mechanical Engineering, University of Michigan, Ann Arbor, 2005 M.Sc. Transportation Safety, George Washington University, 2001 M.Sc. Structural Engineering, Sharif University of Technology, 1998 B.Sc. Civil Engineering, Sharif University of Technology, 1996 Research Interests: His work integrates control theory with transportation systems to reduce energy use and emissions. He explores eco-driving algorithms, vehicle connectivity, and human factors in cycling performance, leveraging both modeling and extensive vehicle-in-the-loop experimentation. Publications Trend: Recent articles emphasize validated experiments on energy-efficient automated driving, cyclist fatigue modeling, and cooperative control strategies, demonstrating a shift toward cyber-physical validation and interdisciplinary sports science applications. Scientific Awards: Best Paper Award, Road User Measurement and Evaluation Committee, TRB 2024 2nd Best Paper Award, IEEE International Automated Vehicle Validation Conference 2023 ASME Automotive and Transportation Systems Best Paper Award 2020 & 2018 IFAC Young Author Award 2019 Advising & Grants: He mentors numerous graduate researchers and postdocs; prospective students are directed to an online form for open positions. His research has been supported by NSF, DOE, DOT, and industry partners, although specific grant details are not listed here. Labs & Teams: He leads the Clemson Vehicle & Energy Systems Laboratory, conducting vehicle-in-the-loop experiments and collaborating with interdisciplinary teams across mechanical engineering, transportation, and sports science.