جست‌وجوی استاد و پژوهشگر

Constantinos Daskalakisمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Game Theory
• +۶ مورد دیگر

Constantinos Daskalakis is the Armen Avanessians (1982) Professor in the MIT Schwarzman College of Computing and the Department of Electrical Engineering and Computer Science (EECS). He joined MIT in 2009 and is a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Operations Research Center (ORC). His research focuses on theoretical computer science, with emphasis on game theory, machine learning, and high-dimensional statistics. Education: Ph.D. in Computer Science (not explicitly stated, but implied by tenure and awards). Research interests include computational complexity of Nash equilibria, multi-item auctions, machine learning algorithms, and causal inference. His work bridges game theory, economics, probability, and statistics, with applications in AI and healthcare. Key contributions include resolving long-standing problems in computational game theory and developing efficient methods for statistical hypothesis testing. He has been recognized with the 2018 Nevanlinna Prize, ACM Grace Murray Hopper Award, and the Kalai Game Theory Prize. Affiliations: CSAIL, LIDS, ORC, and the Foundations of Data Science Institute. Active in multi-agent learning, bias mitigation in data, and generative models.

Noah J. Cowanمشاهده پروفایل

استاد

• Neuromechanics
• Robotics
• Neuroscience
• +۵ مورد دیگر

Noah J. Cowan is a Professor of Mechanical Engineering at Johns Hopkins University's Whiting School of Engineering, with secondary appointments in Computer Science, Electrical & Computer Engineering, and Neuroscience. He is the founder and director of the Locomotion in Mechanical and Biological Systems (LIMBS) Laboratory, part of the Laboratory for Computational Sensing and Robotics. His research focuses on neuromechanics, robotics, and control theory, bridging neuroscience, biomechanics, and engineering. Cowan's work investigates how organisms achieve precise locomotion and applies these insights to advance robotics, neuroprosthetics, and rehabilitation technologies. Education: B.S. Electrical Engineering (Ohio State, 1995), M.S. and Ph.D. Electrical Engineering & Computer Science (University of Michigan, 1997/2001). Postdoctoral fellowship at UC Berkeley (2001–2003) before joining Johns Hopkins. Research Interests: Neuromechanics of motion, bio-inspired robotics, multisensory integration in animals (e.g., electric fish, Drosophila), and sensorimotor control in clinical contexts like cerebellar ataxia. His lab studies how neural circuits interact with biomechanics to produce movement, with applications to robotic design and neurological disorder treatments. Awards & Recognition: Presidential Early Career Award for Scientists and Engineers (2010), IEEE Fellow, NSF CAREER Award (2009), and multiple teaching and research excellence awards at Johns Hopkins. His work has been published in top journals like Nature , Proceedings of the National Academy of Sciences , and IEEE Transactions on Robotics . Outreach & Mentorship: Longtime mentor for high school and undergraduate students in STEM, leading programs like the Baltimore Ingenuity Project and WISE. Served as team leader for the STEM Achievement in Baltimore Elementary Schools (SABES) initiative. Key Projects: Development of the LIMBS Lab’s VR systems for animal studies, bioelectric navigation technologies for medical devices, and collaborations with clinicians on upper limb movement disorders. His team’s research on electric fish and fruit flies has revealed principles of adaptive control applicable to robotics and AI.

Miyuki Hinoمشاهده پروفایل

استادیار

• Climate Change Adaptation
• Environmental Policy
• Disaster Risk Management
• +۳ مورد دیگر

Miyuki Hino is an Assistant Professor in the Department of City and Regional Planning and an Adjunct Assistant Professor in the Environment, Ecology, and Energy Program at the University of North Carolina at Chapel Hill. She holds a Ph.D. in Environment and Resources from Stanford University and a B.S. in Chemical Engineering from Yale University. Her research focuses on climate hazards, governance, and public policy , with emphasis on equitable adaptation to climate change. Key areas include sea level rise impacts, flood risk on property markets, and managed retreat strategies. She has conducted extensive work on floodplain development policies, household relocation programs, and community resilience frameworks. Dr. Hino's interdisciplinary approach integrates environmental science, urban planning, and social equity . She collaborates with academic and municipal partners, such as the Center for Urban and Regional Studies and Annapolis, MD local governments, to develop actionable solutions for climate adaptation. Her work bridges technical analyses (e.g., sensor networks, machine learning) with policy design to ensure both effectiveness and justice in climate responses. Recent projects emphasize preventing future 'trapped households' by analyzing zoning policies and market dynamics that drive risky development. She advocates for climate-smart growth strategies to balance economic needs with environmental safety, while addressing disparities in vulnerability across communities. Her research has been featured in Science Advances , Nature Climate Change , and interdisciplinary journals. She actively engages with policymakers to translate findings into practical measures, such as equitable buyout programs and floodplain management reforms.

• Condensed Matter Physics
• Materials Science
• Quantum Physics
• +۶ مورد دیگر

Anna Delin is a Full Professor at KTH Royal Institute of Technology since 2011, leading research on magnetic and quantum phenomena in materials. She heads the WISE research school (wise-materials.org) and served as Deputy Head of the School of Engineering Sciences (SCI) from 2018–2022. Her expertise spans condensed matter physics, with a focus on nanomagnetism, skyrmions, spin-lattice couplings, and topological materials. Education: PhD in Condensed Matter Physics from Uppsala University (1998). Key awards include Naturvetarpriset (1998), Royal Swedish Academy of Sciences Research Fellowship (2007), Thuréus Prize (2018), and Edlundska Prize (2024). She has held visiting roles at ICTP, Los Alamos National Lab, and the Fritz Haber Institute. Research interests include magnetic skyrmions, magnonics, spintronics, and ultrafast demagnetization. Recent publications focus on spin-lattice dynamics, topological materials, and quantum analogs of classical magnetic models. Her work bridges theory and experiment, with contributions to tools like SpinView for computational magnetism analysis. Teaching includes roles as examiner for the Degree Project in Applied Physics and teacher for Sustainable Development in Engineering Physics. She actively participates in materials design initiatives and semantic data processing for big research data. Lab affiliations include her own research group at KTH and collaborations through WISE. Current projects explore skyrmion stabilization, magnon entanglement, and quantum spin systems, with implications for next-generation spintronic devices.

Marko Hinkkanenمشاهده پروفایل

استاد

• Electric Drives
• Power Electronics
• Control Systems
• +۴ مورد دیگر

Marko Hinkkanen is a Professor at Aalto University's Department of Electrical Engineering and Automation, affiliated with the School of Electrical Engineering. His research focuses on electric drives, power electronics, and control systems, with a strong emphasis on sensorless control, grid converters, and motor drives. He has received numerous awards, including the IEEE Fellow distinction and multiple best paper awards for contributions to sensorless control and grid integration. Research interests span advanced control algorithms, power converter design, and renewable energy systems. His work addresses challenges in grid stability, motor drives under weak grid conditions, and energy-efficient control strategies. Notable achievements include innovations in bearingless motor systems and grid-forming converter control frameworks. His awards reflect impactful contributions: the Aalto ELEC Supervisor Award (2023) highlights exceptional mentorship, while the IEEE Fellow (2023) and numerous paper awards underscore technical excellence. Key publications include advancements in grid-forming control, sensorless techniques, and electromagnetic damping for aircraft systems. He has advised doctoral students such as F. M. Mahafugur Rahman and Hafiz Asad Ali Awan, whose theses won top awards. His labs and collaborations focus on cutting-edge topics like virtual air gap reactors and six-phase machine dynamics.

Zerina Kapetanovicمشاهده پروفایل

استادیار

• Low-power wireless communication
• Sensing systems
• Internet of Things (IoT)
• +۳ مورد دیگر

Zerina Kapetanovic is an Assistant Professor in the Department of Electrical Engineering at Stanford University, with courtesy appointments in Computer Science and Geophysics. She leads the S4 Lab, focusing on low-power wireless systems, IoT, and environmental/healthcare applications. Her work includes innovations in passive communication, energy-efficient sensing, and satellite connectivity. Education: PhD in Electrical Engineering (University of Washington, 2022) Postdoctoral Research: Microsoft Research (Networking and Research for Industry Groups) Research interests span wireless communication, IoT systems, and energy-efficient hardware. Notable projects include Johnson noise thermometry, satellite backscatter (SARLink), and carrier-free RFID communication. Awards include the Terman Faculty Fellowship and Yang Research Award. Advises doctoral students in IoT and wireless systems. Teaches courses on wireless sensing, engineering investigation, and special studies in EE. Active in grants and collaborations, including the Wu Tsai Human Performance Alliance. Labs/Teams: S4 Lab (Smart Sensing Systems) and involvement in FarmBeats IoT agriculture platform.

Mirko Hornungمشاهده پروفایل

استاد

• Aircraft Design
• Aviation Technology
• Aerospace Engineering
• +۳ مورد دیگر

Prof. Dr. Mirko Hornung is a Professor of Aircraft Design at the TUM School of Engineering and Design, Technische Universität München. His research focuses on conceptual aircraft design, integration of propulsion systems, and evaluation of aviation technologies in operational contexts. Education and Career: PhD in Aeronautical Engineering from the University of the Bundeswehr (2003), awarded a research prize for work on reusable space transport systems. 2003–2009: Worked at Airbus Group (EADS) on military air systems, propulsion integration, and program management. Executive Director of Research & Technology at Bauhaus Luftfahrt, a think tank for long-term aviation developments. Research Interests: Aircraft design optimization, including hybrid energy systems, electric propulsion, and UAV technologies. Environmental sustainability in aviation, such as hydrogen-powered aircraft and lifecycle assessment. Aerodynamic and structural analysis, including flutter suppression and composite materials. Key Publications Highlight Trends: Focus on hybrid-electric and hydrogen propulsion for reducing environmental impact. Advancements in UAV design, including morphing wings and autonomous systems. Integration of AI-driven tools for propulsion optimization and lifecycle analysis. Scientific Awards: EADS Promotion Award (1995) Research Prize for Thesis on Reusable Space Transport Systems (2003) Advising & Grants: Directs research at Bauhaus Luftfahrt, collaborating on future aviation concepts. Engaged in interdisciplinary projects like FLEXOP UAV demonstrator and Ce-Liner eMobility studies. Labs/Teams: Active in the Aircraft Design Professorship at TUM and leadership roles at Bauhaus Luftfahrt, focusing on next-generation aviation technologies.

María Rivera Maulucciمشاهده پروفایل

استاد

• Urban Education
• Science Education
• Science Pedagogy
• +۷ مورد دیگر

María Rivera Maulucci is the Ann Whitney Olin Professor of Education and serves as the Education Program Director/Chair at Barnard College, Columbia University. She is a proud alumna of Barnard (Class of 1988) and has been a faculty member since 2004. Her work centers on urban education, science pedagogy, and teacher development with a strong commitment to equity and social justice. Education: BS, Barnard College, Columbia University MFS, Yale School of Forestry & Environmental Studies M.Phil, Teachers College, Columbia University Ph.D., Teachers College, Columbia University Her research focuses on how teachers learn to teach for social justice, emphasizing the role of language, identity, and emotions in teacher development. She employs qualitative research and evaluation methods to explore transformative pedagogical practices in urban science education. Her scholarship bridges formal and informal learning contexts and investigates the interplay between teacher agency and structural constraints. Her recent publications and presentations highlight a sustained focus on equity, critical science inquiry, teacher identity, and professional development. She has contributed extensively to journals such as Journal of Research in Science Teaching and Cultural Studies of Science Education , and has authored chapters on social justice, identity, and assessment in science education. Scientific Awards: Barnard College Emily Gregory Teaching Award (2018) National Association for Research in Science Teaching Equity and Ethics Scholar (2007) She is the Principal Investigator of the NSF-funded Barnard College Robert Noyce Teacher Education Scholars Program, which supports future science teachers in urban schools. She advises students and collaborates with national organizations, including the National Association for Research in Science Teaching, Association for Science Teacher Education, and American Educational Research Association. Her teaching includes courses such as Science in the City , Urban School Practicum , and Performance Assessment of Teaching . She is actively engaged in professional development initiatives and has led workshops on family engineering nights, multicultural pedagogy, and social justice in science education. Her lab and programmatic work centers on the Noyce Scholars Program, which functions as a living laboratory for preparing socially conscious science educators.

Matthias Winterمشاهده پروفایل

مدرس ارشد

• Mathematical Biology
• Pattern Formation
• Reaction-Diffusion Systems
• +۷ مورد دیگر

Dr. Matthias Winter is a Senior Lecturer in the Department of Mathematics at Brunel University's College of Engineering, Design and Physical Sciences. He has been affiliated with Brunel since 2005, following academic positions at the University of Stuttgart (1996-2005) and postdoctoral fellowships at the Institute for Advanced Study in Princeton (1993-94) and Heriot-Watt University in Edinburgh (1994-96). His educational background includes a PhD from Stuttgart University in 1993 and a Habilitation from the same institution in 2003. Dr. Winter's research focuses on mathematical biology, particularly pattern formation in biological systems through reaction-diffusion equations. His work examines spike solutions, pattern formation mechanisms, and the mathematical analysis of biological phenomena. He has made significant contributions to understanding stable spike clusters in various contexts including the Gierer-Meinhardt system. His research spans Mathematical Biology, Pattern Formation, Reaction-Diffusion Systems, Nonlinear Partial Differential Equations, and several related mathematical disciplines. His recent publications (2023-2025) demonstrate continued activity across diverse applications including cancer modeling, ecological systems, climate modeling, and fundamental mathematical analysis of reaction-diffusion phenomena, showing his ability to apply sophisticated mathematical techniques to real-world biological problems. Editorial Board, ISRN Mathematical Analysis, since 2010 Academic Appeals Committee, since 2013 Level One Coordinator for Mathematics, since 2013 Course Director MSc Programme Computational Mathematics with Modelling Mathematics, 2008-2010 Dr. Winter teaches various mathematics courses including Mathematics and Statistics for Economists, Vector Calculus, and Group Projects in Mathematics, with a teaching portfolio spanning from foundational courses to specialized topics related to his research interests.

Arash Aramiمشاهده پروفایل

دانشیار

• Assistive Robotics
• Human-Robot Interaction
• Machine Learning
• +۶ مورد دیگر

Arash Arami is an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, cross-appointed in Systems Design Engineering. He directs the Neuromechanics and Assistive Robotics Laboratory and maintains affiliations with Waterloo Robohub, the Centre for Bioengineering and Biotechnology, Waterloo AI institute, and KITE institute at Toronto Rehab Institute. He earned his Doctorate in Electrical Engineering from EPFL (2014), Master of Science from University of Tehran (2009), and Bachelor of Science from University of Tabriz (2006), all in Control Engineering. His research in Assistive Robotics and Rehabilitation Engineering integrates Machine Learning with Neuromechanics to develop intelligent systems for human movement analysis. Key focus areas include exoskeleton control algorithms, wearable sensor systems, and neural control modeling for rehabilitation applications. Recent publications demonstrate interdisciplinary work spanning robotics, biomedical engineering, and materials science, with emphasis on real-time human locomotion prediction, exoskeleton-human interaction, and data-driven health monitoring solutions. Dr. Arami serves as Chair of the NSERC Scholarship Committee (2021-2023) and mentors graduate students through the Mechatronics Exchange Study program. His teaching includes core courses in control systems, robot manipulators, and biomechanical engineering. The Neuromechanics and Assistive Robotics Laboratory fosters collaborations with clinical partners at Toronto Rehab Institute, focusing on translating robotic innovations into practical rehabilitation tools through interdisciplinary teamwork.

Harri Lähdesmäkiمشاهده پروفایل

دانشیار

• Probabilistic Machine Learning
• Deep Generative Models
• Artificial Intelligence
• +۴ مورد دیگر

Harri Lähdesmäki is an Associate Professor (tenured) at the Department of Computer Science, Aalto University, where he leads the Computational Systems Biology research group. His work focuses on probabilistic machine learning and deep generative models with applications in biomedicine and molecular biology. Key Research Interests: Probabilistic machine learning, deep generative models, computational biology, bioinformatics, longitudinal data modeling Contact: harri.lahdesmaki@aalto.fi | Konemiehentie 2, 02150 Espoo, Finland His recent publications highlight advancements in: Gaussian process priors for scalable deep generative models Single-cell analysis of immune repertoires in leukemia and diabetes Probabilistic deconvolution methods for RNA-seq data Epigenetic analysis using hidden Markov and mixed models Transformer-based survival prediction and missing data handling Harri’s work integrates mechanistic modeling with Bayesian inference, particularly applied to immunology, cancer biology, and early disease prediction.

Matthias Feurerمشاهده پروفایل

استاد

• Automated Machine Learning
• Hyperparameter Optimization
• Bayesian Optimization
• +۵ مورد دیگر

Matthias Feurer is a Thomas Bayes Fellow and interim professor at the Chair of Statistical Learning and Data Science, funded by the Munich Center for Machine Learning (MCML) at Ludwig Maximilian University of Munich. He is a member of the Department of Statistics at LMU Munich, working under Prof. Dr. Bernd Bischl. His academic background includes: PhD in Computer Science from Albert-Ludwigs-Universität Freiburg, supervised by Prof. Dr. Frank Hutter M.Sc. in Computer Science from the University of Freiburg B.Sc. in Computer Science and Media from the Media University Stuttgart Feurer's research focuses on simplifying machine learning usage through Automated Machine Learning (AutoML). His work encompasses hyperparameter optimization, meta-learning, and model selection, with increasing emphasis on multi-objective AutoML that considers factors beyond predictive performance such as interpretability, deployability, and fairness. He actively develops open-source tools to advance the field. His recent publications demonstrate a strong trajectory in practical AutoML systems, with growing attention to tabular machine learning, foundation models integration, and addressing real-world constraints in optimization. His work consistently bridges theoretical advances with practical implementations through several widely-used open-source projects. Notable achievements include: 1st place in the warmstarting-friendly leaderboard of the BBO NeurIPS challenge Winner of the 2nd AutoML challenge Winner of the kdnuggets blog contest on AutoML Feurer is actively mentoring and teaching, having advertised PhD positions focused on AutoML, optimization, and benchmarking. He co-founded the Open Machine Learning Foundation supporting OpenML.org. His upcoming move to TU Dortmund as an assistant professor in AutoML and Optimization signals continued growth in his academic career while maintaining his research focus on making machine learning more accessible and rigorous.

Abbas Milaniمشاهده پروفایل

استاد

• Textile Composites
• Biocomposites
• Materials Constitutive Relations
• +۱۰ مورد دیگر

Abbas Milani is a tenured Professor of Mechanical Engineering at the University of British Columbia's Okanagan campus, where he holds the Tier 1 Principal's Research Chair in Sustainable & Smart Manufacturing and serves as Director of the Materials and Manufacturing Research Institute (MMRI). He also serves as Technical Director of the Composites Research Network (CRN), Lead of the Canadian-International Biocomposites Research Network, and leads multiple major initiatives including the UBC-Pacific Economic Development Canada-Advancing Circular Economy (ACE) program and the UBC-NRC IRAP National Circular Economy CtO Program. Dr. Milani's primary research focuses on advanced modeling, simulation, and multi-criteria design optimization of composite and biocomposite materials, structures, and manufacturing processes. His expertise spans Textile Composites/Biocomposites, Materials Constitutive Relations, Finite Element Modeling, Robust Inverse Methods, Material Selection for End-of-Life Design Strategies, Multiple Criteria Decision Making, and Industry 5.0 applications. His interdisciplinary research bridges mechanical engineering, sustainable materials science, and smart manufacturing technologies. Analysis of his recent publication record reveals a strong emphasis on sustainable materials development, with particular focus on biocomposites, life cycle assessment methodologies, and optimization of manufacturing processes. His work integrates computational modeling with experimental validation across diverse application areas including medical devices, sustainable packaging, and circular economy strategies. The publications demonstrate increasing integration of artificial intelligence and machine learning approaches with traditional engineering methods. 2015 UBC Okanagan Researcher of the Year Award Killam Faculty Research Award (2016) Inducted into Royal Society of Canada - College of New Scholars (2020) Gold Medal Service Contribution Award by Academics World Reviewer Contribution Award by ASM International Multiple teaching excellence awards from UBC Dr. Milani has successfully mentored over 100 students and postdoctoral fellows who have secured positions in both industry and academia. His research program has been supported by more than $15 million in funding from government and industrial organizations. He leads the NSERC CREATE in Immersive Technologies (CITech) program and co-leads the Advanced Materials and Fabrication Core Competency within the Survive and Thrive Applied Research (STAR) program, demonstrating his commitment to training the next generation of engineers and advancing applied research.

• Affective Computing
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Dr A. I. Shihab is a Senior Lecturer at Kingston University's Faculty of Engineering, Computing and the Environment, Department of Networks and Digital Media. He teaches programming languages (C++/Java), data structures, web development, and AI/machine learning. His research focuses on affective computing and machine learning applications including: Acoustic event detection in sports environments Audio signal analysis for tennis match modeling Multi-camera visual surveillance systems Medical imaging analysis using fuzzy clustering techniques Publications demonstrate expertise in combining audio/video modalities for sports analytics (tennis rallies, court-shots) and developing Markov models for sound event sequence analysis. Contact: a.shihab@kingston.ac.uk

Bryan H. Choiمشاهده پروفایل

دانشیار

• Software Liability
• AI Safety
• Cybersecurity Law
• +۶ مورد دیگر

Bryan H. Choi is an Associate Professor of Law at the University of Colorado Law School , where he bridges law and computer science to address software and AI safety. His work on software liability has influenced national cybersecurity strategy discussions. As an Adviser for the ALI Principles Project on Civil Liability for Artificial Intelligence , he shapes legal frameworks for emerging technologies. Education : JD and AB in Computer Science from Harvard University; clerkships with U.S. Court of Appeals judges Leonard I. Garth and William C. Bryson. Roles : Former joint appointment at Ohio State University Law School and Computer Science Department; Faculty Fellow at UPenn's CTIC; Director of Law and Media at Yale's ISP. Research Focus : Choi's scholarship examines software liability , AI accountability , and privacy law through interdisciplinary lenses. He critiques institutional approaches to software safety and advocates for empirical legal frameworks over participation-based models. Recent Articles address AI malpractice , NIST software standards , and forensic tool validation , reflecting trends in AI regulation and cyber-physical system liability . His 2021 NSF grant funded technical-legal methods for safety-critical systems. Awards & Grants : National Science Foundation (NSF) Grant (2021) Adviser, ALI Principles Project on Civil Liability for Artificial Intelligence Community Engagement : Active in Law and Computer Science communities , serving on committees for the ACM Symposium , Cybersecurity Law and Policy Scholars Conference , and co-organizing the AAAI Bridge Program on AI and Law .