جست‌وجوی استاد و پژوهشگر

• High-Performance Buildings
• Net-Zero Energy Systems
• Building Thermal Modeling
• +۵ مورد دیگر

Yuxiang Chen is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Alberta. His research focuses on high-performance buildings, net-zero energy systems, and sustainable construction practices. He integrates advanced modeling techniques, renewable energy solutions, and intelligent design strategies to optimize building performance in cold climates. PhD, Building Engineering (2013), Concordia University MASc, Building Engineering (2008), Concordia University BEng, Building Engineering (2006), Concordia University Dr. Chen’s work emphasizes modular construction, thermal energy storage, and data-driven modeling for building systems. He explores the use of robotics in construction, thermal resistance of masonry walls, and energy-efficient community greenhouses tailored for cold regions. His recent publications highlight trends in building thermal dynamics, with a focus on resistor-capacitor (RC) models, hybrid heating systems, and snow accumulation impacts on solar panels. He also contributes to cold-climate energy management and smart home integration.

Jamie J. Bakerمشاهده پروفایل

استاد

• Artificial Intelligence in Law
• Legal Research
• Legal Education
• +۳ مورد دیگر

Jamie J. Baker serves as Associate Dean and Director of the Law Library and Dean's Distinguished Service Professor of Law at Texas Tech University School of Law. She oversees all Law Library operations while teaching Civil Trial: Practice & Litigation Materials, Academic Legal Writing, Intro to the Study of Law, and Legal Practice research workshops for first-year students through the Excellence in Legal Research Program. Her educational background includes a B.S. in Political Science & Public Administration from Central Michigan University, an M.L.I.S. from Wayne State University's School of Library & Information Science, and a J.D. from Western Michigan University Cooley Law School, where she was recognized as the most outstanding editor of the Cooley Law Review. Professor Baker's research centers on cognitive computing applications in legal research, legal research pedagogy, and the evolving role of law librarianship. She examines how artificial intelligence disrupts traditional legal research methods and addresses the duty of technology competence for legal professionals. Her work bridges library science and legal education, focusing on practical implementation in academic settings. Analysis of her 15 most recent publications reveals consistent focus on AI's impact on legal research, with recurring themes including algorithmic regulation, technology competence ethics, and future law library services. Her scholarship spans law reviews, book chapters, and conference presentations, demonstrating interdisciplinary engagement between legal academia and library science. ABA Blawg 100 recognition Top-Ten Blog for Information Professionals Best of the Legal Blogs by Internet Legal Researcher Most outstanding editor of Cooley Law Review As an educator, she mentors students through specialized research workshops and legal writing instruction. Her professional engagement includes frequent presentations at major conferences like the American Association of Law Schools and American Association of Law Libraries annual meetings. She previously served as a Law Librarian and Adjunct Professor at Western Michigan University Cooley Law School and worked at the Michigan Supreme Court's Friend of the Court Bureau. Her influential blog, The Ginger Law Librarian, serves as a hub for discussions on AI in legal research and modern law librarianship, reflecting her commitment to advancing the profession through technological innovation.

David M. Labyakمشاهده پروفایل

استادیار

• Solid Mechanics
• Finite Element Analysis
• Vibration Analysis
• +۱۳ مورد دیگر

David M. Labyak is an Assistant Professor at Michigan Technological University's College of Engineering, affiliated with both the Manufacturing and Mechanical Engineering Technology and Mechanical and Aerospace Engineering departments. He teaches courses in computer-aided engineering, finite element methods, dynamic systems control, machine design, robotics dynamics, and Industry 4.0 concepts. PhD in Mechanical Engineering-Engineering Mechanics (2003) and MS in Mechanical Engineering (2000) from Michigan Tech Over 24 years of industrial experience in automotive, aerospace, mining, and consulting sectors His research interests span solid mechanics, finite element analysis, vibration analysis, machinability of metals, biomechanics, and helmet design optimization. Collaborative work includes dynamic testing, acoustic modeling, and workforce development initiatives. Recent publications highlight interdisciplinary work in vibration testing, metalcasting, and educational frameworks. Key areas include defect detection in additive manufacturing, dynamic fixture design, and experiential learning for mechatronics.

• Geotechnical Engineering
• Earthquake Engineering
• Soil-Structure Interaction
• +۷ مورد دیگر

Ramin Motamed is a Professor in the Department of Civil & Environmental Engineering at the University of Nevada, Reno (UNR). His research focuses on geotechnical earthquake engineering, including soil-structure interaction, liquefaction mitigation, and nonlinear site response analysis. He has conducted extensive studies on deep foundations, ground motion analysis, and seismic design of structures. Motamed leads a research group involving postdocs and graduate students, and teaches advanced courses such as Geotechnical Earthquake Engineering and Foundation Engineering Design. His work integrates experimental methods (e.g., shake table tests) with numerical modeling to address challenges in seismic hazard mitigation. Key projects include evaluating helical piles for foundation settlement reduction, improving LRFD resistance factors for drilled shafts in Nevada, and analyzing site-specific ground motions using downhole array data. Motamed’s research has been published in journals like Soil Dynamics and Earthquake Engineering, and he collaborates with institutions globally, including Japan’s E-Defense facility. Current research emphasizes reducing uncertainties in ground motion prediction, optimizing mitigation measures for liquefaction-prone sites, and advancing predictive analytics for geotechnical design using machine learning. His lab facilities and field experiments enable large-scale validation of theoretical models, bridging geotechnical theory and practical engineering solutions. Teaching responsibilities include foundational and graduate courses covering geotechnical engineering principles, earthquake engineering, and advanced foundation analysis. Motamed’s advising includes over a dozen graduate students, many contributing to high-impact research in seismic resilience and geotechnical innovation.

• Discrete choice experiments
• Optimal experimental design
• Multivariate statistics
• +۷ مورد دیگر

Martina Vandebroek is Full Professor of Statistics and Operations Research at KU Leuven, Faculty of Economics and Business, where she leads methodological work within the Operations Research and Statistics Research Group (ORSTAT). She also serves as senior academic staff on the Faculty Council and the Campus Councils for Leuven and Kortrijk, and is a member of the LStat General Assembly. Research Interests Discrete choice experiments (design & analysis) Optimal and sequential experimental design Multivariate statistics and modelling of preference heterogeneity Random regret minimisation and attribute non-attendance Applications in health economics, transport, marketing, and food science Her methodological innovations enable more efficient data collection and richer behavioural insights in stated-preference surveys, while her applied projects translate patient and consumer preferences into actionable evidence for policy makers and industry. Recent Publications Overview Between 2022 and 2024 Vandebroek (co-)authored 15 key articles. These contributions advance both the statistical machinery of choice modelling—such as mixed random regret models, design-efficient sample-size rules, and consideration-set heuristics—and substantive applications in oncology patient preferences, inflammatory bowel disease treatments, meat-substitute adoption, and food-quality valuation. The work repeatedly integrates sophisticated econometric techniques with real-world stakeholder data, reflecting an overarching commitment to methodological rigour and societal impact. Scientific Awards & Recognition No specific awards are listed in the provided material; however, her sustained publication record in top journals (Journal of Choice Modelling, Food Quality and Preference, Frontiers in Oncology, Stata Journal) attests to significant scholarly recognition. Advising & Grant Activities Promotor (PI) of FWO project “Discrete choice models including screening rules: modeling and design” (2017-2021) Promotor of KU Leuven project “Efficient Online Choice Experiments” (2017-2020) Co-promotor of IWT/FWO project “Empirical and methodological challenges in choice experiments” (2017-2023) Co-promotor of VLAIO project “Development, Validation, and Valorization of a Patient Preference Platform” (2023-2026) Teaching & Service Vandebroek teaches master-level courses “Applications of Statistics” (Dutch and English iterations) and contributes to the Leuven Statistics Research Centre (LStat) educational programme.

Srikanth Rangarajanمشاهده پروفایل

استادیار

• Energy Storage Management
• Thermal Management Systems
• Electronics Packaging
• +۷ مورد دیگر

Srikanth Rangarajan is an Assistant Professor at Binghamton University's School of Systems Science and Industrial Engineering. He holds a PhD and MS from the Indian Institute of Technology Madras (2017) and a BE from Anna University Chennai (2011). His research focuses on energy storage systems, thermal management of electronics, battery optimization, and digital twinning. He previously served as an Associate Research Professor in Mechanical Engineering at Binghamton under Bahgat Sammakia. Rangarajan authored the book Phase Change Material Heat Sinks: A multi-objective Perspective and holds a patent for a rotatable heat sink design. His teaching includes optimization techniques, thermal modeling, and neural networks. Recent work explores virus spread modeling via genetic algorithms, with a preprint under review in Journal of Healthcare Informatics . He has received multiple awards including an Institute Post-Doctoral Fellowship and Research Assistantships from the Indian government. His research bridges thermal engineering with advanced manufacturing and sustainability, addressing challenges in high-power electronics and data center cooling. Education: BE in Mechanical Engineering, Anna University (2011) MS in Thermal Engineering, IIT Madras (2017) PhD in Heat Transfer, IIT Madras (2017) Research Interests: Digital twin systems for battery optimization Thermal energy storage design Advanced electronics packaging Data center cooling innovations Phase change material composites His recent articles highlight cooling solutions for high-density electronics, battery recycling challenges, and predictive models for epidemiological patterns using computational methods. Ongoing work includes embedded cooling technologies for heterogeneous integrated circuits and sustainable thermal management strategies. Awards: Patent: Rotatable Heat Sink (Government of India) Institute Post-Doctoral Fellowship (IIT Madras, 2017) Research Associate, Divecha Centre (IISc, 2017) Half-Time Research Assistantship (MHRD, 2012-2013) Advising & Grants: While no formal advisees are listed, his prior roles indicate involvement in mentorship. His research has been supported by institutional grants including those from the Indian Ministry of Human Resource Development. Labs/Teams: Active in Binghamton's Systems Science and Industrial Engineering lab, collaborating on thermal management and additive manufacturing projects.

Josh Bongardمشاهده پروفایل

استاد

• Evolutionary Robotics
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Josh Bongard is a Professor in the Department of Computer Science at the University of Vermont, within the College of Engineering and Mathematical Sciences. He holds the Cyril G. Veinott Green and Gold Professorship and directs the Morphology, Evolution & Cognition Laboratory. He earned his Ph.D. from the University of Zurich. Affiliations: University of Vermont, Department of Computer Science, College of Engineering and Mathematical Sciences. Education: Ph.D. in Computer Science from the University of Zurich. His research focuses on evolutionary robotics, embodied intelligence, and synthetic biology. Key projects include developing soft robots, Xenobots (biological machines), and exploring how morphology influences cognition. His work bridges robotics, biology, and artificial intelligence, emphasizing adaptability and resilience. Recent articles highlight advancements in shape-changing robots, self-replicating organisms, and the ethical implications of machine behavior. He has pioneered methods for co-optimizing robot morphology and control systems, enabling more efficient and adaptive designs. Awards: Presidential Early Career Award for Scientists and Engineers (PECASE, 2010) Microsoft Research New Faculty Fellowship (2007) MIT Technology Review's Top 35 Innovators Under 35 (2007) Cozzarelli Prize He advises graduate students in robotics and teaches courses like Evolutionary Robotics and Human-Computer Interaction. His lab collaborates with NASA, NSF, and DARPA, advancing robotics through biologically inspired approaches. Future work includes developing systems that integrate biological and computational principles for novel applications. His book How the Body Shapes the Way We Think explores embodied cognition, and he directs outreach programs like Twitch Plays Robotics to engage the public in robotics innovation.

• Materials Science
• Mechanical Engineering
• Grain Boundary Dynamics
• +۷ مورد دیگر

Huck Beng Chew is a Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC). His research focuses on materials science, mechanical engineering, and nanocomposite interfaces, with a particular emphasis on grain boundary dynamics, molecular dynamics simulation, and fracture mechanics. He leads studies on advanced materials such as titanium composites, boron nitride nanotubes, and magnesium alloys, investigating their deformation mechanisms, fatigue behavior, and interfacial strengthening. Chew’s work bridges experimental and computational approaches, utilizing techniques like synchrotron X-ray diffraction, molecular dynamics modeling, and physics-informed neural networks. His research addresses challenges in additive manufacturing, fracture toughness, and ion-beam interactions with materials. Collaborations span interdisciplinary fields, including aerospace engineering, plasma physics, and nanotechnology. Notable contributions include studies on cohesive zone laws for fatigue cracks, microvoiding damage modeling, and interfacial mechanics in nanolayered alloys. His work has been published in high-impact journals such as Acta Materialia , Journal of the Mechanics and Physics of Solids , and Materialia . Chew’s research is supported by grants focusing on nanocomposite mechanics and 3D-printed ceramics. His findings advance material design for high-strength applications in aerospace, energy storage systems, and thermal protection materials.

Richard Scalettarمشاهده پروفایل

استاد

• Condensed Matter Physics
• Quantum Phase Transitions
• Superconductivity
• +۵ مورد دیگر

Distinguished Professor of Physics at the University of California Davis College of Letters and Science since 1989. Primary affiliation with the Department of Physics, with significant cross-disciplinary collaborations in Applied Mathematics and Computer Science through NSF and DOE grants. Research focuses on quantum many-body phenomena in condensed matter systems and ultracold atomic gases. Expertise spans magnetism, superconductivity, metal-insulator transitions, and quantum phase transitions. Pioneers advanced Quantum Monte Carlo simulation techniques, particularly determinant quantum Monte Carlo for Hubbard and electron-phonon models. Current work investigates spatial inhomogeneities in quantum phases and strong interparticle interactions. Recent publications reveal growing integration of machine learning with quantum simulation. Research trends indicate deepening exploration of SU(N) symmetric systems, flat-band quasicrystals, photonic quantum simulators, and neural quantum states. Increasing emphasis on interdisciplinary approaches combining condensed matter theory, quantum information science, and computational mathematics. Key methodological focus remains on overcoming fermionic sign problems and developing scalable numerical algorithms. Principal investigator for major grants from the National Science Foundation (NSF), Department of Energy (DOE), Office of Naval Research (ONR), and Defense Advanced Research Projects Agency (DARPA). Significant funding through NSF Information Technology Research and DOE Scientific Discovery through Advanced Computing Programs for quantum simulation algorithm development.

• Advanced Coal Utilization
• Biomass Gasification
• Biofuels Production
• +۳ مورد دیگر

Professor Sankar Bhattacharya is a distinguished academic at Monash University's Department of Chemical & Biological Engineering within the Faculty of Engineering. His career spans industry roles in India, Thailand, Australia, and France, followed by an academic focus on advanced coal and biomass utilization, gasification, biofuels, and catalysis. He leads a research group of 16 PhD students and two research fellows, having supervised 12 PhD completions. His work contributes to UN SDGs related to affordable and clean energy, industry innovation, and climate action. Research focuses on gasification of coal/biomass/algae, liquid fuels from brown coal, and CO₂ utilization. He advises Japan's METI on clean coal and the IEA's Cleaner Fossil Fuels program. Awards include Fellow of the Australian Institute of Energy and membership in the American Chemical Society. Key projects include leadership in ARC Research Hubs for carbon waste valorization and battery recycling. His 240+ publications span catalysis, energy systems, and waste-to-value technologies. Research highlights include catalyst development for hydrogen production, critical metal recovery from coal ash, and ammonia fuel cell innovations. Teaching commitments include courses on energy-environmental systems and biorefinery processes. Collaborations span global institutions, emphasizing sustainable energy solutions and circular economies.

Maria Grazia De Angelisمشاهده پروفایل

استاد

• Polymer Science
• Gas Separation Membranes
• Medical Engineering
• +۳ مورد دیگر

Professor Maria Grazia De Angelis holds a Personal Chair in Thermodynamics of Materials and Processes at the University of Edinburgh's School of Engineering. Her research focuses on advanced materials for gas separation membranes, medical engineering innovations like wearable artificial kidneys, and environmental applications such as CO2 capture. Key projects include the development of semicrystalline polymers for hydrogen storage and nanoporous materials for dialysate regeneration. She leads interdisciplinary research teams addressing challenges in sustainable materials and biomedical technologies. Her work combines computational modeling, molecular simulations, and machine learning to design next-generation materials. Notable contributions include breakthroughs in superhydrophobic materials and CO2 capture membranes. Funded projects span EPSRC, Kidney Research UK, and industry partners like Danisco. Collaborations involve global institutions, advancing both fundamental and applied research in materials science.

• Geotechnical Engineering
• Energy Geotechnics
• Numerical Modeling
• +۶ مورد دیگر

Dr David M G Taborda serves as a Reader (equivalent to Associate Professor) in the Geotechnics section of Imperial College London's Department of Civil and Environmental Engineering within the Faculty of Engineering. His research focuses on energy geotechnics, numerical modeling of soil behavior, and offshore wind turbine foundation design, with significant contributions to thermo-active infrastructure systems. Civil Engineering, University of Coimbra, Portugal (2004) PhD in Numerical Modelling of Dynamic Soil Behaviour and Liquefaction, Imperial College London (2010) Dr Taborda's research program spans energy geotechnics , where he pioneered experimental techniques and numerical methods for thermo-active foundations including piles, retaining walls, and tunnels. His work integrates constitutive modeling of soils with applications in offshore wind turbine foundations through the PISA project, developing advanced design methodologies for monopiles in challenging soil conditions. Current investigations address soil liquefaction mechanisms, thermo-hydro-mechanical coupling in granular materials, and machine learning applications for foundation analysis. His research bridges experimental validation with computational innovation to solve complex geotechnical challenges in sustainable energy infrastructure. Analysis of Dr Taborda's 41 publications (2017-2025) reveals three dominant research trajectories: (1) thermo-active infrastructure optimization with increasing focus on thermal interference and machine learning applications; (2) cyclic behavior of offshore foundations using high-cycle accumulation frameworks; and (3) multi-physics modeling of liquefaction and soil-structure interaction. Recent work demonstrates a strong trend toward data-driven approaches and surrogate modeling for complex geotechnical systems, particularly in energy geostructures and offshore wind applications. Dr Taborda actively supports prospective PhD students through Imperial College's President's Scholarships and College funding schemes, and encourages applications for Imperial College Research Fellowships. His research has been advanced through significant industry-academic collaborations including the PISA project for offshore wind foundations, though specific grant details are not provided in the source material. He maintains strong connections with the Geotechnical Consulting Group where he previously worked, facilitating industry-relevant research translation. Affiliated with Imperial's Energy Futures Lab, Dr Taborda collaborates within the Geotechnics section on experimental and computational research. His team develops specialized equipment for thermo-hydro-mechanical testing and contributes to the department's leadership in energy geostructures research, with applications spanning urban infrastructure, renewable energy systems, and offshore engineering projects.

Alan Edelmanمشاهده پروفایل

استاد

• Julia Programming
• High Performance Computing
• Linear Algebra
• +۳ مورد دیگر

Alan Edelman is a Professor at the Massachusetts Institute of Technology (MIT), renowned for his work in high-performance computing, linear algebra, and random matrix theory. He is a co-creator of the Julia programming language, which emphasizes efficiency and versatility for scientific computing. His research integrates mathematics and computer science, focusing on numerical methods, parallel computing, and applications in fields like quantum control and climate modeling. Edelman leads projects such as Oceananigans.jl for geophysical fluid dynamics and Circuitscape for connectivity analysis in conservation biology. His academic contributions span theoretical advancements in matrix theory and practical implementations of computational tools. Edelman collaborates across disciplines, bridging scientific computing with machine learning and quantum physics. His work on differentiable programming frameworks and GPU acceleration has impacted both academic research and industry applications. Key Projects: Julia programming language, Oceananigans.jl, Circuitscape Research Themes: High-performance computing, numerical linear algebra, random matrices, scientific machine learning Affiliations: MIT’s Theory of Computation Community of Research, PI of multiple NSF-funded projects Edelman’s recent work emphasizes interdisciplinary applications, including climate policy modeling and automated materials discovery. His publications reflect a blend of foundational mathematics and cutting-edge computational techniques.

Mina Konakovic Lukovicمشاهده پروفایل

استادیار

• Computer Graphics
• Computational Fabrication
• 3D Geometry Processing
• +۴ مورد دیگر

Mina Konaković Luković is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Massachusetts Institute of Technology (MIT) , affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) . She leads the Algorithmic Design Group , focusing on computational design and fabrication, geometry processing, and robotics. Education: PhD in Computer Science (EPFL), MS & BS in Mathematics (University of Belgrade) Research Interests: Spanning computer graphics, computational fabrication, and 3D geometry processing with applications in smart materials, architectural geometry, and physics-based simulations. Her work integrates machine learning and differential geometry to optimize design algorithms for novel materials and deployable structures. Articles Trends: Recent publications emphasize multi-objective optimization for 3D printing materials, graph grammar in robot design, and computational methods for auxetic structures. Themes revolve around data-driven design, deployable shells, and terrain-adaptive robotics. Scientific Awards: Schmidt Science Fellows Additional Study Grant (2020) ACM SIGGRAPH Outstanding Doctoral Dissertation Honorable Mention (2020) Eurographics PhD Award (2020) Patrick Denantes Memorial Prize (2019) Doctoral Program Thesis Distinction from EDIC EPFL (2019) SIAM Early Career Prize (2020) Eurographics Junior Fellows (2021) Advising & Grants: Mentored by Prof. Dr. Wojciech Matusik and Prof. Dr. Mark Pauly, with funding from Swiss National Centre of Competence in Research (NCCR) Digital Fabrication. She actively participates in program committees and summer schools.

SHEN Leiمشاهده پروفایل

پژوهشگر

• Multiscale Modeling and Simulation
• Materials Informatics
• Computational Physics
• +۳ مورد دیگر

SHEN Lei is a researcher at the National University of Singapore (NUS), affiliated with the Department of Physics. With a PhD in Physics from NUS, he specializes in Multiscale Modeling and Simulation and Materials Informatics , leveraging machine learning and computational methods for advanced materials discovery. Research Focus: Density functional theory, molecular dynamics, finite element analysis, and data-driven design of materials. Teaching: Modules include Mechanics and Waves (PC1433), Applied Quantum Mechanics (PC2130B), and Mechanical Properties of Materials (ESP2109). His work spans spintronics, ferroelectricity, and energy storage materials, with recent publications on interatomic potentials, sliding heterostructures, and battery anodes. He has received the Teaching Commendation Award and declined the Lee Kuan Yew Postdoctoral Fellowship . Notable Trends: Recent articles emphasize machine learning in materials science, van der Waals heterostructures, quantum transport, and medical image analysis. Subfields include Rashba spin-orbit coupling, piezoelectric tensor modeling, and defect-informed neural networks. Scientific Awards: Teaching Commendation Award (AY15/16; AY16/17) Lee Kuan Yew Postdoctoral Fellowship (2014) (declined)