جست‌وجوی استاد و پژوهشگر

Misa Faezipourمشاهده پروفایل

دانشیار

• System Dynamics Modeling
• Healthcare Systems Engineering
• Complex Systems Modeling
• +۳ مورد دیگر

Dr. Misa Faezipour is an Associate Professor in the Department of Engineering Technology at Middle Tennessee State University (MTSU) and director of the Systems Engineering Lab (SEL). She holds a Ph.D. and M.Sc. in Industrial Engineering and Engineering Management from the University of Texas at Arlington and a B.Sc. in Software Engineering from Islamic Azad University North Tehran Branch. Her research focuses on system dynamics modeling, healthcare systems engineering, complex systems, and sustainability optimization. Dr. Faezipour has advised numerous graduate students in M.S. and Ph.D. programs, focusing on topics such as healthcare disparities, AI robustness, and policy impact analysis. She teaches courses including Engineering Economy, Operations Management, and Engineering Management Systems. Her work spans collaborations with institutions like NASA, the Systems Engineering Research Center, and healthcare organizations. Her recent publications emphasize AI-driven healthcare solutions, system dynamics applications in policy analysis, and optimizing healthcare delivery through data-driven models. She actively contributes to professional organizations such as INCOSE, IEEE, and the System Dynamics Society. Dr. Faezipour’s lab, SEL, develops innovative tools for healthcare informatics, including diagnostic recommenders and policy simulation frameworks. Her research bridges systems engineering with healthcare challenges, addressing issues like racial health inequities and pandemic response strategies.

Weichao Wangمشاهده پروفایل

استاد

• Cybersecurity
• Wireless Networks Security
• Cloud Computing Security
• +۷ مورد دیگر

Weichao Wang is a Professor and Chair of the Department of Software and Information Systems at the University of North Carolina at Charlotte (UNC Charlotte). He holds a Ph.D. in Computer Science from Purdue University (2005), with earlier degrees from Tsinghua University. His research focuses on securing pervasive systems, wireless networks, cloud computing, and critical infrastructures, integrating multi-disciplinary approaches like information theory and visualization. He leads efforts in cybersecurity education for K-12 and higher education. Key roles include organizing IEEE conferences (e.g., IPCCC) and editorial roles in journals like ITU Intelligent and Converged Networks. His awards include the 2024 AECT Crystal Award and multiple Distinguished TPC recognitions. Students under his advisement have contributed to areas like mobile cloud computing and network security. Professional contributions include service on over 50 conference committees and journal reviewing. Current research emphasizes cybersecurity in education, IoT defense, and AI-driven security systems. His lab explores immersive visualization for cybersecurity training and augmented reality applications.

Jonathan Weinsteinمشاهده پروفایل

استاد

• Microeconomic Theory
• Game Theory
• Economic Theory
• +۳ مورد دیگر

Jonathan Weinstein is a Professor of Economics and Director of Graduate Studies in the Department of Economics at Washington University in St. Louis. He holds a PhD from the Massachusetts Institute of Technology (MIT). His research focuses on microeconomic theory and game theory, with particular emphasis on strategic behavior, incomplete information, and Bayesian inference. Notable recent contributions include works on 'Direct Complementarity' and 'Reputation without Commitment.' He serves on committees such as the Master Program Management Committee and the PhD Committee. His research explores topics like rationalizability in infinite games, the impact of risk attitudes on strategic interactions, and the integration of Bayesian methods with classical hypothesis testing. His work bridges theoretical rigor and practical applications in economic decision-making under uncertainty. Education: PhD in Economics from MIT Committees: Master Program Management Committee, PhD Committee Recent Papers: 'On a Mistranslation of a Mistake about Minimax' (2022), 'The Effect of Changes in Risk Attitude on Strategic Behavior' (2016) Contact: j.weinstein@wustl.edu | Office: Seigle Hall 382

Nan Marie Jokerstمشاهده پروفایل

استاد

• Photonics
• Optoelectronic Devices
• Integrated Optoelectronics
• +۷ مورد دیگر

Nan Marie Jokerst is the J. A. Jones Distinguished Professor of Electrical and Computer Engineering at Duke University's Pratt School of Engineering and Executive Director of the Duke Shared Materials Instrumentation Facility. She previously served as Chair of the Duke Academic Council (2014-2015) and Associate Dean for six years. B.S. in Physics, Creighton University (1982) M.S.E.E., University of Southern California (1984) Ph.D. in Electrical Engineering, University of Southern California (1989) Her research spans chip-scale photonic sensing systems , III-V thin-film lasers on silicon , metamaterials , and heterogeneous integration . She develops optical systems for medical diagnostics, environmental monitoring, and security applications through the Jokerst Laboratory, which combines optical system design, optoelectronic device development, and semiconductor fabrication expertise. Her recent publications show strong focus on terahertz strain mapping using metamaterials, multi-pixel tissue characterization for cancer margin detection, and microfluidic sensing platforms with embedded photodetectors. Key trends include advancing non-destructive structural monitoring and miniaturized biomedical diagnostics through novel photonic integration techniques. IEEE Fellow (2003) Optica Fellow (2001) NSF Presidential Young Investigator Award IEEE Third Millennium Medal IEEE/HP Harriet B. Rigas Medal USC Viterbi School Alumni Award She has advised numerous graduate students in photonic device research and secured major grants including the NSF National Nanotechnology Coordinated Infrastructure ($6M, 2015-2021) and NNCI: North Carolina Research Triangle Nanotechnology Network ($20M, 2020-2026). Her leadership extends to co-founding Triangle Women in STEM and serving on the National Academies Board on Global Science and Technology. The Duke Shared Materials Instrumentation Facility under her direction provides critical cleanroom and characterization resources for interdisciplinary research.

Shahriar Afkhamiمشاهده پروفایل

پژوهشگر

• Materials Science
• Welding Engineering
• Additive Manufacturing
• +۳ مورد دیگر

Shahriar Afkhami is a Researcher in the Department of Mechanical Engineering at LUT School of Energy Systems, LUT University. His research focuses on advanced materials science, additive manufacturing processes, and mechanical properties of high-strength steels and dissimilar joints. He specializes in fatigue analysis, welding technologies, and the optimization of structural components for industrial applications. His work integrates experimental methods with computational modeling to address challenges in material behavior under extreme conditions. Key research areas include: Welding of ultra-high strength steels and dissimilar materials Mechanical performance of additively manufactured components Fatigue life assessment of welded joints and cut edges Thermomechanical behavior of heat-affected zones Material characterization of laser powder bed fusion (LPBF) steels Publications highlight trends in additive manufacturing for industrial applications, particularly in optimizing 3D-printed metal structures and analyzing their mechanical integrity. His work on notch-load interactions and fatigue strength has advanced methodologies for predicting component failure under complex loading conditions. Notable contributions include the VERKOTA project exploring 3D printing networks for enhanced industrial adoption. No scientific awards are listed in the provided information. Afkhami's research has been supported by collaborative projects such as the VERKOTA initiative, though specific grants are not detailed here. He maintains an active presence on professional networks including LinkedIn and Google Scholar.

Scott T. M. Dawsonمشاهده پروفایل

استادیار

• Fluid Mechanics
• Dynamical Systems
• Control Theory
• +۵ مورد دیگر

Scott T. M. Dawson is an Assistant Professor in the Mechanical, Materials, and Aerospace Engineering Department at Illinois Institute of Technology (Illinois Tech). He holds positions in the Armour College of Engineering and leads research at the intersection of fluid mechanics, dynamical systems, control theory, and data science. His work focuses on extracting dynamic models from large datasets to analyze and control turbulent flows and unsteady aerodynamic systems. Education includes a Ph.D. and M.A. from Princeton University (2017, 2013), and B.Eng. and B.S. degrees from Monash University (2010, 2009). Prior to Illinois Tech, he was a postdoctoral scholar at Caltech’s Graduate Aerospace Laboratories under Prof. Beverley McKeon. Research interests emphasize reduced-order modeling, data-driven techniques for fluid flows, and flow control applications. His group’s work is supported by NSF, AFOSR, and DOE grants. Recent projects include sparsity-promoting methods for flow analysis, wavelet-based resolvent analysis, and neural network-driven flow control systems. Publications span over 60 peer-reviewed articles, with a focus on turbulence modeling, transient flow dynamics, and machine learning integration in fluid mechanics. Key contributions include novel algorithms for isolating amplification mechanisms in wall-bounded flows and robust neural network frameworks for closed-loop flow stabilization. Grants and collaborations include multi-year NSF CAREER funding for automated distillation of coherent flow structures. Ongoing efforts explore time-localized spectral methods, nonlinear dimensionality reduction, and hydrogen decarbonization in vehicular systems.

• Meta-Research
• Obesity Disparities
• Systematic Reviews
• +۶ مورد دیگر

Dr. Kathryn Kaiser is an Assistant Professor in the Department of Health Behavior at the University of Alabama at Birmingham (UAB) School of Public Health. She holds concurrent appointments in multiple research centers including the Center for Clinical and Translational Science and the Nutrition Obesity Research Center (NORC). Her research focuses on meta-research methodologies, race/sex disparities in obesity, systematic reviews of nutrition interventions, and advancing FAIR data principles for scientific communication. Education: B.S. Microbiology (Texas A&M), B.S. Medical Technology (University of Texas Health Science Center), Ph.D. in Health Psychology (University of North Texas Health Science Center). Postdoctoral training in Vascular Biology/Hypertension at UAB. Extensive background in medical diagnostics instrumentation and laboratory science prior to academia. Research Interests: Systematic review methodologies, FAIR data standards, obesity disparities with a focus on neuroendocrine mechanisms, and translational research in bariatric surgery outcomes. Specializes in methodological rigor for clinical trials and evidence synthesis. Grants: NIH-funded projects on FAIR principles implementation, dairy intake research, obesity energetics, and lifespan studies. Recent grants include $2.1M for metadata education programs and $1.8M for knowledge mapping initiatives. Awards: Recognized as 2015 Top Reviewer for American Journal of Preventive Medicine. Serves as Associate Editor for Frontiers in Nutrition. Active member of Cochrane Collaboration and multiple professional societies. Teaching: Graduate courses in Health Program Evaluation, Psychophysiology, and Systematic Review Design. Supervises doctoral students in health behavior research through 30+ dissertation committees since 2011. Labs/Teams: Key contributor to UAB's Nutrition Obesity Research Center (NORC) and Center for Outcomes and Effectiveness Research (COERE). Collaborates with international metadata initiatives like Metadata 2020 and science dialogue mapping projects.

Young-Jin Chaمشاهده پروفایل

استاد

• Deep Learning
• Structural Health Monitoring (SHM)
• Autonomous UAVs
• +۵ مورد دیگر

Dr. Young-Jin Cha is a tenured full Professor in the Department of Civil Engineering at the University of Manitoba, affiliated with the Price Faculty of Engineering. He holds a PhD from Texas A&M University and has postdoctoral experience at MIT. His research focuses on deep learning-based structural health monitoring (SHM), autonomous UAVs for infrastructure inspection, and smart transportation systems, with over 100 peer-reviewed publications and $1.2M in grants. He is a Fellow of ASCE and has received notable awards including the 2021 Merit Award and 2022 International Association of Advanced Materials Scientist Award. His work has been cited over 9,200 times globally. Research interests include automated SHM with UAVs, nonlinear system identification, unsupervised deep learning for damage detection, and sustainable infrastructure design. He serves as an editor for journals like Structural Control & Health Monitoring and Engineering Reports . His lab, the Laboratory for Infrastructure Science and Technology (LIST), develops advanced technologies for infrastructure resilience. Key achievements include pioneering deep learning-based SHM with UAVs, top-cited papers in civil engineering journals, and leadership in organizing international conferences. He actively seeks graduate students for research in AI-driven infrastructure solutions.

• Social Media Analysis
• Sentiment Analysis
• Computational Journalism
• +۶ مورد دیگر

Fabrício Benevenuto is an Associate Professor in the Computer Science Department at Federal University of Minas Gerais (UFMG), where he conducts interdisciplinary research at the intersection of social media analysis, data science, and computational journalism. His work spans complex networks, machine learning, and natural language processing with strong societal impact. His research focuses on social media dynamics, particularly in Brazilian contexts, with major contributions to hate speech detection, fake news analysis, and political discourse monitoring. He leads large-scale projects against misinformation, including development of systems like WhatsApp Monitor, Media Bias Monitor, and Purple Feed. His work combines technical innovation with real-world applications for election transparency and public discourse integrity. Benevenuto's recent publications demonstrate strong trends in multilingual NLP for social media analysis, with emphasis on Brazilian Portuguese contexts. His team produces both theoretical contributions and practical systems addressing hate speech, misinformation, and media bias. Notable methodological approaches include combining network analysis with linguistic features, developing culturally-aware detection systems, and creating large annotated datasets for understudied languages. CAPES award for best Brazilian computer science thesis (2010) Humboldt Foundation scholarship recipient (2017-2018) Member of TikTok Safety Advisory Council WWW'20 Best Paper Nominee & CNIL-INRIA Privacy Protection Prize winner Multiple best paper awards at CEAS, WBC, and ICWSM conferences Test-of-Time Award at ICWSM'20 Benevenuto actively mentors PhD and MSc students, with numerous advisees securing academic positions at Brazilian universities and research roles at institutions like Max Planck Institute. His projects often receive funding supporting interdisciplinary collaborations across computer science and social sciences. Current work includes large-scale analysis of Telegram political groups, real-time election monitoring systems, and developing culturally-aware NLP tools for Portuguese. He leads research teams working on social media analysis systems with societal impact, particularly focused on Brazilian digital ecosystems. Projects involve cross-institutional collaborations with researchers from MPI-SWS, Max Planck Institute, and various Brazilian universities, emphasizing practical applications for public discourse integrity.

Iain Garnerمشاهده پروفایل

استاد

• Forensic Psychology
• Applied Psychology
• Eyewitness Testimony
• +۷ مورد دیگر

Dr. Iain Garner is the Executive Dean of the College of Social Sciences and Arts at Sheffield Hallam University. He has held several senior roles, including Associate Dean for Business and Enterprise (2019-2022), Head of the Department for Education Childhood and Inclusion (2013-2019), and Director of International and Market Development (2010-2013). His academic background in Psychology drives his research into Forensic Psychology , Eyewitness Testimony , and the Media's Portrayal of Crime . He explores how psychological perception affects legal systems and public understanding of criminal justice. Recent publications highlight his work in Medical Education (e.g., mental simulation for cardiac arrest training), Autism Research , and Higher Education Leadership . Dr. Garner actively supervises postgraduate research, including Stacey, Al-Ali, Moore, and Beardon. He contributes to university governance as a member of the Strategic Marketing Development Group and manages student recruitment for those with criminal convictions. His work emphasizes Internationalization of curricula, Virtual Learning Environments , and Applied Psychology in real-world contexts.

Alicia L Carriquiryمشاهده پروفایل

استاد

• Forensic Science
• Statistics
• Nutrition Epidemiology
• +۳ مورد دیگر

Alicia L Carriquiry is a Distinguished Professor and President's Chair at Iowa State University, serving as Director of the Center for Statistics and Applications in Forensic Evidence (CSAFE). She holds a PhD in Statistics from Iowa State University (1989), an MS from the University of Illinois at Urbana-Champaign/ISU (1985/1986), and a BS from Universidad de la Republica in Uruguay (1981). Her research focuses on applying statistical methods to forensic science, nutrition epidemiology, and plant and animal breeding, with a particular emphasis on Bayesian frameworks. Recent research emphasizes forensic evidence analysis, including footwear impression algorithms, handwriting software development, and probabilistic evidence assessment tools. She also explores dietary intake patterns in populations across Latin America and Southeast Asia, addressing nutrient deficiencies and public health interventions. Her work bridges statistical rigor with practical applications in criminal justice, improving forensic methodologies through algorithmic innovation and interdisciplinary collaboration. As CSAFE Director, she leads initiatives to enhance statistical foundations in forensic disciplines, train practitioners, and develop open-source datasets. Notable contributions include database search methodologies, error rate analyses, and software tools like handwriter for handwriting analysis. Her research underscores the importance of probabilistic reasoning in legal contexts and addresses challenges in multi-camera source identification and nonlinear image distortion correction. Carriquiry’s leadership extends to editorial roles and professional service, advancing statistical standards in forensic science. She remains active in training programs and collaborative research projects, fostering reproducibility and relevance in scientific inquiry.

Brian Surgenorمشاهده پروفایل

استاد

• Mechanical Engineering
• Machine Vision Systems
• Autonomous Vehicles
• +۳ مورد دیگر

Professor Brian Surgenor is a faculty member at Queen's University's Department of Mechanical and Materials Engineering, part of the Smith Engineering faculty. He holds a B.Sc. (1977), M.Eng. (AECL/Whiteshell), and Ph.D. (1983) in Mechanical Engineering from Queen's University. His research focuses on machine vision systems for automation, autonomous vehicle navigation, and mechatronic system design education. He has held key administrative roles including Department Head (1993-2002), Associate Dean (2008-2013), and Vice-Dean (2013-2016). His work emphasizes interdisciplinary innovation, such as the Mitchell Hall design project and contributions to Ingenuity Labs. Education: B.Sc. Mechanical Engineering, Queen's University (1977) M.Eng. Engineering Physics, McMaster University (AECL/Whiteshell) Ph.D. Mechanical Engineering, Queen's University (1983) Research interests include: - Pneumatic servosystems - Intelligent algorithms for machine vision - Off-road autonomous vehicle systems - Mechatronics education methodologies - Hybrid powertrain systems for vehicles His recent publications (2017–2024) explore autonomous systems, machine vision applications, and fuel cell hybrid technologies. Notable trends include advancements in UAV-based infrastructure inspection, terrain-adaptive autonomous driving, and low-cost machine vision solutions for small part sorting. His work bridges theoretical control systems with practical industrial automation challenges. He has contributed to laboratory design for CDIO curricula and pioneered mechatronics education through problem-based learning. His administrative leadership has shaped Queen's engineering graduate programs and research infrastructure. Currently involved in Ingenuity Labs, fostering cross-disciplinary innovation.

Xi Chenمشاهده پروفایل

دانشیار

• Algorithmic Game Theory
• Economics
• Complexity Theory
• +۳ مورد دیگر

Xi Chen is an Associate Professor in the Department of Computer Science at Columbia University. Prior to this, he was a postdoctoral researcher at the Institute for Advanced Study (Princeton University) and the University of Southern California. He holds a B.S. in Physics/Maths from Tsinghua University (2003) and a Ph.D. in Computer Science from Tsinghua University (2007), advised by Professor Bo Zhang under the guidance of the Institute for Theoretical Computer Science led by Andrew Chi-Chih Yao. His research focuses on Algorithmic Game Theory, Economics, and Complexity Theory. His work is supported by an NSF CAREER award, a Sloan Research Fellowship, and Columbia University startup funds. He has received the EATCS Presburger Award and multiple best paper awards, including at FOCS 2006, ISAAC 2009, and CCC 2017. Xi Chen has taught courses such as Analysis of Algorithms , Lower Bounds in Theoretical Computer Science , and Introduction to Computational Complexity . He co-advises current PhD students Tim Randolph and Erik Waingarten, and has graduated students like Timothy Sun (Emory University) and Xiaorui Sun (University of Illinois at Chicago). He has served on program committees for conferences like WINE, SODA, and STOC. His research spans theoretical computer science, including property testing, graph isomorphism, and fixed-point computation. He is affiliated with Columbia's Theory Group and actively participates in the Theory Seminar organized by Alex Andoni. Xi Chen's research also extends to algorithmic economics, exploring mechanisms, pricing strategies, and market equilibria. His work on complexity theory includes contributions to counting problems and circuit complexity. He maintains a lab and collaborates with researchers in theoretical computer science and algorithmic game theory.

Laura Mersini-Houghtonمشاهده پروفایل

استاد

• Cosmology
• Theoretical Physics
• Quantum Physics
• +۶ مورد دیگر

Laura Mersini-Houghton is a Professor of Theoretical Physics and Cosmology at the University of North Carolina at Chapel Hill. She is affiliated with the Gravity, Cosmology, and HEP (GCHEP) theory group and the Institute of Field Physics , supported by the Bahnson Fund. Her research spans three main areas: origins of the universe, dark energy, and quantum black hole physics. Her work includes proposing a quantum landscape multiverse theory to explain the universe's origin, with predictions tested by PLANCK and LHC experiments. She has also demonstrated that Hawking radiation back-reaction prevents singularity formation in collapsing stars. Education : PhD in Physics (University of Wisconsin-Milwaukee, 2000), MSc (University of Maryland-College Park, 1997), Fulbright Scholar (University of Maryland, 1994). Key trends in her recent publications include cosmological tensions, quantum multiverse implications, and time crystal-based dark energy models. She co-authored works on inflationary cosmology and cosmic probes of fundamental physics. Scientific Awards : UWM Distinguished Alumni She has been featured in media coverage and public talks, exploring topics like the arrow of time and cosmic puzzles. Her research integrates theoretical physics, string theory, and observational cosmology, supported by the Bahnson Fund.

• Machine Learning
• Database Systems
• Artificial Intelligence
• +۳ مورد دیگر

Christopher Re is a Professor in the Department of Computer Science at Stanford University, affiliated with the Stanford AI Lab, Machine Learning Group, and Center for Research on Foundation Models. His research focuses on the intersection of machine learning, database systems, and scientific computing, with applications in humanitarian efforts, scientific discovery (e.g., extrasolar neutrinos, DNA foundation model Evo), and industry partnerships with companies like Apple and Google. He has been recognized with prestigious awards, including the MacArthur Foundation Fellowship and multiple test-of-time awards. His work emphasizes advancing thermal materials, phase-change memory, and ultrafast electron microscopy technologies. Re's research contributions span database theory, systems, and machine learning, with best papers at PODS 2012, SIGMOD 2014, and ICML 2016. His lab’s innovations have been incorporated into products globally, and he actively invests in technology startups. Key projects include developing thermal interface materials for 3D integrated circuits and exploring energy-efficient neuro-inspired memory systems. His awards reflect sustained excellence: NeurIPS 2020 and PODS 2022 test-of-time awards, along with recent accolades for student-led initiatives at MIDL 2022 and ICLR22. Re’s interdisciplinary approach bridges academia and industry, driving both scientific and humanitarian impact.