جست‌وجوی استاد و پژوهشگر

Bård Harstadمشاهده پروفایل

استاد

• Environmental Economics
• Political Economics
• Economic Theory

Bård Harstad is The David S. Lobel Professor in Business and Sustainability and Professor of Political Economy at Stanford University’s Graduate School of Business, with courtesy appointments in the Doerr School of Sustainability and the School of Humanities and Sciences (Economics). He joined Stanford in 2023 after previous faculty positions at Northwestern University’s Kellogg School of Management (where he held the Max McGraw Chair in Management & Environment) and the University of Oslo. He has also taught at Harvard, MIT, and Toulouse School of Economics. His research centers on three interconnected domains: Environmental Economics : Climate policy design, conservation incentives, deforestation, and energy transitions. Political Economics : Treaty bargaining, international agreements, legislative gridlock, and policy enforcement. Economic Theory : Contract design, time inconsistency, and strategic behavior in regulatory frameworks. His work frequently examines how institutions and incentives shape global environmental outcomes. Harstad’s publications focus on climate governance, with recurring themes of self-enforcing agreements, supply-side policy interventions, and the political economy of conservation. Recent articles analyze trade-offs in energy transitions (e.g., natural gas vs. renewables), mechanisms for credible international commitments, and deforestation incentives linked to trade. His research combines theoretical rigor with policy-relevant applications, often using game-theoretic frameworks. He has received significant recognition, including: European Research Council (ERC) Advanced Grant (2022) and Consolidator Grant (2016–21) Elected fellowships in the Econometric Society (2021) and Society for the Advancement of Economic Theory (2021) Multiple Erik Kempe Awards for environmental economics research Prizes from the Norwegian Academy of Sciences and Royal Swedish Academy of Sciences Harstad serves as Editor of the Review of Economic Studies and teaches courses on Strategy Beyond Markets, Political Economy, and Environmental Economics. He leads Stanford GSB’s executive program on Managing Risk and Reputation in a Complex World .

Pia Hüttlمشاهده پروفایل

پژوهشگر

• Monetary Policy
• Banking Sector
• Financial Integration
• +۳ مورد دیگر

Pia Hüttl is a Researcher in the Macroeconomics department at the German Institute for Economic Research (DIW Berlin). She holds a doctorate from Humboldt University of Berlin, preceded by a bachelor’s degree from University of Rome Tor Vergata and a master’s in European Political Economy from the London School of Economics. Education: BA (University of Rome Tor Vergata), MSc (London School of Economics), PhD (Humboldt University) Key roles: Researcher at DIW Berlin, former work at European Commission, European Central Bank, Bruegel think tank Her research spans monetary policy, banking sector dynamics, financial integration, and the intersection of credit bubbles with political behavior. She has contributed to policy analysis through the Gemeinschaftsdiagnose project and ECB collateral framework studies. Recent publications examine: 2025: Political implications of credit bubbles 2025: Macroeconomic effects of banking union reforms 2024: Economic outlook under trade conflicts 2023: Climate policy and monetary instruments She has participated in media discussions on financial market integration and sanctions against Russian oligarchs.

Seojeong Jay Leeمشاهده پروفایل

دانشیار

• Econometric methods
• Statistical inference
• Causal econometrics
• +۷ مورد دیگر

Associate Professor Seojeong Jay Lee is a faculty member at the UNSW Business School , specializing in Econometrics and Statistical Methods . Joining the University of New South Wales (UNSW) in 2012 after completing a PhD at the University of Wisconsin-Madison, they focus on developing robust statistical tools for economic models where traditional experimental controls are impractical. Research Interests Generalized Method of Moments (GMM) Instrumental Variables (IV) and Two-Stage Least Squares (2SLS) Robust inference under model misspecification Handling invalid/many/weak instruments in econometrics Heterogeneous treatment effects and clustered sampling analysis Grants & Funding Australian Research Council (ARC) Discovery Project DP210101440 (AUD 336,939), 2021-2023 Health@Business UNSW Grant (AUD 3,500), 2020 ARC Discovery Early Career Researcher Award (DECRA) DE170100787 (AUD 331,000), 2017-2019 UNSW Business School Special Research Grant (AUD 17,699), 2013-2014 Awards & Recognition Zellner Thesis Award (Honorable Mention), American Statistical Association, 2014 Non-Professorial Research Achievement Award, UNSW Business School, 2017 Academic Leadership Currently supervising PhD candidates Wei Tian and Fangzhou Yu in econometric theory and applications.

Bern Kleinمشاهده پروفایل

استاد

• Mineral Processing
• Comminution
• Sensor-Based Ore Sorting
• +۳ مورد دیگر

Bern Klein is a Professor at the University of British Columbia's Faculty of Applied Science, specifically within the Norman B. Keevil Institute of Mining Engineering. His career spans over three decades, beginning with extensive industry experience from 1990 to 1998, followed by his academic role at UBC since 1997. He has held leadership positions including Graduate Advisor (1999-2008) and Department Head (2008-2014), and has been instrumental in establishing research centers like the Centre for Industrial Minerals Innovations and the Canadian International Resources and Development Institute. Education: PhD in Mineral Process Engineering, University of British Columbia (1992) BASc in Mining and Mineral Process Engineering, University of British Columbia (1985) Research Interests: Professor Klein's research is centered on mineral processing technologies , with a strong emphasis on energy efficiency and environmental sustainability in mining operations. His work encompasses: Comminution processes and energy optimization Rheology of mineral suspensions Sensor-based ore sorting technologies Water and energy conservation in mining Development of innovative mineral processing flowsheets His research has led to the creation of Mine Sense Technologies Ltd , a startup company that has developed novel sensor-based sorting systems for the mining industry. Scientific Awards: Institute of Mining and Metallurgy Transactions Best Paper Award (2008) Canadian Institute of Mining Distinguished Lecturer Award (2011) CEEC Medal for Best Paper (2013, 2016) CEEC Honorable Mention for Best Paper (2022) Mitacs Award for Exceptional Leadership for a Professor (2023) Teaching and Supervision: Professor Klein teaches courses including MINE 201 Mineral Resources Engineering II , MINE 434/524 Processing of Precious Metal Ores , MINE 508 Integrated Mining and Processing Systems , and MINE 579 Rheology of Mineral Suspensions . He has supervised numerous graduate students, with Uuganbadrakh Oyunkhishig being one of his Master's students. Research Teams and Labs: His research involves interdisciplinary collaboration, particularly through the Quantum Matter Institute and the Centre for Industrial Minerals Innovations. He is open to collaborations with undergraduate students and other researchers, fostering a collaborative research environment.

Seojeong Leeمشاهده پروفایل

دانشیار

• Econometrics
• Statistical Inference
• Generalized Method of Moments (GMM)
• +۸ مورد دیگر

Associate Professor Seojeong Lee is a faculty member at the University of New South Wales (UNSW) Business School, School of Economics, specializing in advanced econometric theory. She joined UNSW in 2012 after completing her PhD at the University of Wisconsin-Madison and has established herself as a leading researcher in robust inference methods under complex data conditions. Her educational background includes: Ph.D. in Economics, University of Wisconsin-Madison (2008-2012) M.A. in Economics, Seoul National University (2006-2008) B.A. in Economics and Political Science (dual major), Seoul National University, summa cum laude (2000-2006, with military service 2002-2004) Professor Lee's research centers on developing theoretically rigorous methods for econometric inference, with primary focus on generalized method of moments (GMM), instrumental variables (IV), and two-stage least squares (2SLS) under model misspecification. Her work addresses critical challenges including invalid/many/weak instruments, heterogeneous treatment effects, and clustered sampling, contributing foundational advances to statistical inference in economics. Analysis of her recent publications reveals a strong trajectory in refining methods for many-instrument settings and misspecified models, with increasing emphasis on computational implementations (e.g., Stata packages) and applications to causal inference. Her work bridges theoretical econometrics with practical policy-relevant analysis. Her scientific achievements include: Australian Research Council DECRA Fellowship (2017-2019) UNSW Dean's Research Fellowship (2020-2022) Zellner Thesis Award Honorable Mention from American Statistical Association (2014) Multiple competitive UNSW research awards Professor Lee actively supervises PhD candidates Wei Tian and Fangzhou Yu, and has secured over AUD 700,000 in research funding including ARC Discovery Projects. She teaches undergraduate and postgraduate econometrics courses, integrating her research into pedagogy. Her ongoing work continues to push boundaries in robust econometric methodology for modern data challenges.

• Biomechanics
• Human Movement Science
• Gait Analysis
• +۱۰ مورد دیگر

Friedl De Groote is a Senior Lecturer at KU Leuven's Faculty of Human Movement and Rehabilitation Sciences, Department of Human Movement Sciences, specializing in the biomechanics of human movement. She leads the Biomechanics of Human Movement Research Group and is a member of the iSi Health - KU Leuven Institute for Physics-based Modeling for In Silico Health. Her research focuses on understanding neuromusculoskeletal control of human movement, particularly through computational modeling approaches. She investigates gait disorders in children with cerebral palsy and Duchenne muscular dystrophy, examining how muscle impairments, contractures, and neural control mechanisms contribute to altered movement patterns. Her work combines experimental biomechanics with predictive computer simulations to uncover the underlying mechanisms of movement disorders and develop new rehabilitation approaches. She also studies fundamental aspects of human locomotion, balance control, and energy expenditure during walking. Her recent publications demonstrate a strong emphasis on predictive simulations to understand the relationship between neuromusculoskeletal impairments and movement pathology. Her research spans multiple domains including cerebral palsy, Duchenne muscular dystrophy, gait analysis, balance control, and musculoskeletal modeling. She frequently collaborates with clinical researchers to bridge the gap between computational models and clinical applications. Dr. De Groote is actively involved in various academic councils including the Faculty Council FaBeR, POC Rehabilitation Sciences and Physiotherapy, POC Physical Education and Movement Sciences, and multiple departmental councils within Human Movement Sciences. Her ORCID identifier is 0000-0002-4255-8673 . She currently leads or co-leads numerous research projects funded through KU Leuven and external grants, with a focus on understanding walking control mechanisms, energy expenditure during locomotion, and developing computational models to inform rehabilitation strategies for children with movement disorders. Her research portfolio demonstrates a commitment to translating biomechanical insights into clinically relevant applications.

Mehrdad Moallemمشاهده پروفایل

استاد

• Control Systems
• Power Electronics
• Energy Harvesting
• +۳ مورد دیگر

Dr. Mehrdad Moallem is a Professor and Graduate Student Supervisor in the Department of Mechatronic Systems Engineering at Simon Fraser University (SFU). He holds a Ph.D. in Electrical & Computer Engineering from Concordia University (1997), an M.Sc. from Sharif University (1988), and a B.Sc. from Shiraz University (1986). His research focuses on control systems in sustainable energy, power electronics, energy harvesting, robotics, and embedded systems. He has authored/co-authored four technical books and serves on editorial boards for journals like IEEE/ASME Transactions on Mechatronics. Dr. Moallem has held academic roles at Duke University and the University of Western Ontario. His teaching includes courses on real-time control systems, mechatronics design, and microprocessors. Research interests span embedded control systems, nonlinear dynamics, and applications in renewable energy and robotics. Recent work includes IoT-enabled lighting systems for agriculture, RF cavity control, and smart energy harvesting. He emphasizes hands-on student projects and industry collaboration, such as the Siemens Certification Program and Industry 4.0 bootcamps. Dr. Moallem's lab develops innovative solutions for energy efficiency and automation, with a focus on sustainable systems and smart manufacturing. He actively advises graduate students on advanced topics like grid-connected inverters, motor drives, and vibration control.

• Econometrics
• Applied Economics
• Causal Inference
• +۳ مورد دیگر

Dr. Liyang Sun is a Lecturer in Economics and Deputy Graduate Tutor at the University of College London's Department of Economics, and an Untenured Associate Professor (on leave) at CEMFI in Madrid. She holds a PhD in Economics and Statistics from MIT (2021) and a BA in Economics and Mathematics from Wellesley College (2014). Her research focuses on causal inference methodologies under treatment effect heterogeneity and weak identification with many instruments. Prior to her current roles, she was a Postdoctoral Research Fellow at UC Berkeley. Her academic positions include: Lecturer in Economics, University College London (current) Untenured Associate Professor, CEMFI, Madrid (on leave) Postdoctoral Research Fellow, UC Berkeley (previous) Research interests span econometric method development, applied economics, and policy analysis. Her work emphasizes improving causal inference techniques in realistic economic settings. Recent publications explore synthetic control methods, instrumental variables with many weak instruments, and machine learning applications in structural reforms analysis. Her scholarly contributions address core econometric challenges such as: Policy learning and confidence estimation Temporal aggregation in synthetic control frameworks Adaptive methods for model misspecification No specific grants or advising activities are documented here. She contributes to the department's teaching and graduate training programs as Deputy Graduate Tutor.

Alexandru G. Bardasمشاهده پروفایل

دانشیار

• Cybersecurity
• Systems Security
• Moving Target Defenses
• +۹ مورد دیگر

Alexandru G. Bardas is an Associate Professor at the University of Kansas in the Department of Electrical Engineering & Computer Science (EECS) and the Institute for Information Sciences (I2S) . He received his PhD from Kansas State University under advisors Xinming (Simon) Ou and Scott A. DeLoach. His research focuses on cybersecurity from a systems perspective , including moving target defenses, security operations center (SOC) metrics, DevOps security, power grid cybersecurity, and defensive technologies for political activists. He explores UDP-based DDoS detection, DNS traffic analysis, and the intersection of AI with cybersecurity, emphasizing foundational knowledge over tool-specific training. Key research areas: Cybersecurity, Systems Security, Moving Target Defenses, SOC Metrics, DevOps Security Recent publications in ACSAC 2024 , USENIX Security 2024/2023 , and IEEE Security & Privacy 2022 Dr. Bardas has received significant recognition including: NSF CAREER Award (2022) for SOC automation Bellows Scholar (2021) at KU NSA SoS Honorable Mention (2023) He actively advises students across disciplines, with graduates now at Sandia National Laboratories , Blue Cross Blue Shield , and Pacific Northwest National Laboratory . Dr. Bardas participates in NSF grant reviews , serves on program committees for SOUPS and MILCOM , and leads outreach initiatives like the GenCyber Summer Camp .

Christian B Hansenمشاهده پروفایل

استاد

• applied and theoretical econometrics
• high-dimensional data analysis
• causal inference using machine learning
• +۴ مورد دیگر

Christian B. Hansen is the Wallace W. Booth Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. He serves as the academic coordinator for Booth's Sokolov Executive MBA Program and is co-editor of the Journal of Political Economy - Microeconomics. Hansen joined the Chicago Booth faculty in 2004 after completing his PhD at MIT. Education: PhD in Economics, Massachusetts Institute of Technology (2004) Bachelor's degree in Economics, Brigham Young University (2000) Professor Hansen specializes in applied and theoretical econometrics, with research focusing on high-dimensional statistical methods in economic applications, panel data models, clustered standard errors, quantile regression, and weak instruments. His most recent work explores the application of machine learning and artificial intelligence techniques to estimate causal and policy effects. Hansen teaches courses including Applied Econometrics, Machine Learning, and Statistics at Chicago Booth. Scientific Awards and Honors: Neubauer Family Faculty Fellow at Booth NSF research grant recipient National Science Foundation graduate research fellow during PhD studies Hansen has published in leading journals including the American Economic Review, Annals of Statistics, Econometrica, Journal of Business and Economic Statistics, Journal of Econometrics, Review of Economics and Statistics, and Review of Economic Studies. He is currently working on a book titled "Applied Causal Inference Powered by ML and AI" with Victor Chernozhukov, Nathan Kallus, Martin Spindler, and Vasilis Syrgkanis.

Will Ravenمشاهده پروفایل

استاد

• High-Precision Spectroscopy
• Quantum Electrodynamics
• Nuclear Structure Theory
• +۳ مورد دیگر

Prof. Will Raven is a Professor of Physics at Smith College, where he joined the Department of Physics in 2013. He has mentored over 70 undergraduate researchers, published 8 peer-reviewed articles since 2020, and secured five NSF grants, including the NSF CAREER award. His research focuses on high-precision spectroscopy of neutral light atoms to test quantum electrodynamics (QED) and contribute to nuclear structure theory. Ph.D., University of Wisconsin–Madison B.S., Clarkson University Prof. Raven’s research group explores fundamental atomic physics, testing the Standard Model by measuring properties of beryllium, boron, nitrogen, and oxygen atoms. He designed a course, PHY242 Research in High Precision Spectroscopy, accessible to first-year students without calculus or physics prerequisites. His work combines experimental techniques with educational innovation, emphasizing accessible research opportunities. His recent publications (2025–2020) span precision spectroscopy of light atoms, hyperfine structure analysis, and laser stabilization methods. These articles represent fields such as Atomic Physics, Quantum Mechanics, and Optical Physics. American Physical Society 2025 Prize for a Faculty Member for Research in an Undergraduate Institution NSF CAREER award Smith College Student Government Association’s teaching award (twice) Prof. Raven has secured NSF grants for his research, including RUI grants for experimental projects and MRI grants for instrumentation. He leads the Raven Lab, an experimental group dedicated to undergraduate research training and fundamental atomic physics studies.

Jacqueline McClearyمشاهده پروفایل

استادیار

• Astrophysics
• Cosmology
• Weak Gravitational Lensing
• +۴ مورد دیگر

Dr. Jacqueline McCleary is an Assistant Professor of Physics at Northeastern University's College of Science, specializing in observational cosmology with a focus on galaxy clusters and dark matter. She leads research using weak gravitational lensing to study cosmic structures, collaborating on projects like the COSMOS-Web (JWST), SuperBIT (balloon telescope), and LoVoCCS surveys. Her work leverages multi-wavelength data from space, stratospheric, and ground-based observatories. Education: M.S. in Astronomy (New Mexico State University), M.S. and Ph.D. in Physics (Brown University), Postdoctoral Fellow at NASA's Jet Propulsion Laboratory. She transitioned to Northeastern as an ADVANCE Future Faculty Fellow before becoming a tenure-track faculty member in 2022. Research Interests: Dark matter interactions, galaxy cluster dynamics, gravitational lensing techniques, and next-generation observational platforms. Her team develops advanced algorithms and instrumentation for high-resolution imaging. Recent Contributions: COSMOS-Web has enabled unprecedented observations of distant galaxies using JWST, while SuperBIT's stratospheric flights provide diffraction-limited data. Key publications focus on lensing surveys, data reduction techniques, and dark matter-halo relationships. Awards: Recognized as a Northeastern ADVANCE Future Faculty Fellow. Media Engagement: Regularly comments on space exploration, asteroid risks, and cosmic phenomena for public outlets.

Hongbin Caiمشاهده پروفایل

استاد

• game theory
• industrial organization
• corporate finance
• +۳ مورد دیگر

Professor Hongbin Cai serves as Dean and Chair Professor of Economics at the Faculty of Business and Economics, The University of Hong Kong. He also directs the Institute of China Economy and holds significant advisory roles including on the Hong Kong SAR Chief Executive's Policy Unit and the Northern Metropolitan Region Advisory Committee. Previously, he was Dean of the Guanghua School of Management at Peking University from December 2010 to January 2017. Professor Cai's educational background includes: Bachelor's degree in Mathematics from Wuhan University (1988) Master's degree in Economics from Peking University (1991) Doctorate in Economics from Stanford University (1997) Professor Cai's research focuses on game theory, industrial organization, corporate finance, and the Chinese economy. His work bridges theoretical economic frameworks with practical applications in China's economic development and Hong Kong's economic challenges. He has been particularly active in analyzing Hong Kong's economic structural transformation, the impact of geopolitical shifts on its intermediary economy, and strategies for building a knowledge-based, innovation-driven economy. His recent publications demonstrate a strong focus on Hong Kong's economic challenges in the post-pandemic era, with particular attention to economic structural transformation, talent development, and the evolving role of Hong Kong within China's "dual circulation" strategy. His work consistently emphasizes the need for Hong Kong to leverage its unique advantages while addressing long-standing structural weaknesses in its economy. Professor Cai has received numerous prestigious awards: New Century Excellent Talent by the Ministry of Education (2006) National Natural Science Foundation for Distinguished Young Scholars (2007) Changjiang Scholar Distinguished Professor by the Ministry of Education (2008) Elected Fellow of the Econometric Society (2011) As an academic leader, Professor Cai has supervised numerous doctoral students and has been instrumental in recruiting 45 international experts to the HKU School of Business and Economics since 2017. He has championed initiatives to strengthen HKU's research capabilities on Hong Kong's economy, including the development of an "Economic Policy Green Paper" specifically tailored for Hong Kong. His leadership has overseen significant growth in student enrollment and plans for a new campus on Pokfield Road. Professor Cai founded and directs the Institute of China Economy at HKU, which serves as a platform for research on China's economic development and its implications for Hong Kong and the global economy. The Institute has organized major forums, including the 2024 China and Global Economy Forum, bringing together leading economists and business leaders to analyze China's economic future.

David Frazierمشاهده پروفایل

استاد

• Simulation-based inference
• Financial Econometrics
• Nonparametric and semiparametric econometric modeling
• +۳ مورد دیگر

David Frazier is a Professor in the Department of Econometrics & Business Statistics at Monash University, specializing in simulation-based inference, financial econometrics, and nonparametric/semiparametric modeling. He teaches ETC 1010: Data Modeling and Computing. His research focuses on robust statistical methods, Bayesian computation, and model misspecification. Key projects include 'Consequences of Model Misspecification in Approximate Bayesian Computation' (2020-2025) and 'Loss-based Bayesian Prediction' (2020-2025). Recent work addresses forecasting in misspecified models, weak identification in econometric frameworks, and robust variational Bayes techniques. His contributions align with UN Sustainable Development Goals related to economic and environmental sustainability. Projects: 4 active/funded projects with ARC, Brown University, and international collaborators. Publications: Over 37 peer-reviewed articles in journals like the Journal of the American Statistical Association and Journal of Econometrics. Research interests include advancing Bayesian methodologies for complex models, with applications in asset pricing and economic forecasting. His work emphasizes reliability in statistical inference under model uncertainty and computational efficiency.

Andreas Jungمشاهده پروفایل

دانشیار

• High Energy Physics
• Particle Physics
• Detector Development
• +۳ مورد دیگر

Andreas Jung is an Associate Professor of Physics and Astronomy at Purdue University, affiliated with the CMS experiment at CERN. His research focuses on understanding the electroweak scale stabilization via precision measurements of top quark interactions, Higgs boson studies, and detector R&D. He also explores quantum algorithms for high-energy physics and supply chain optimization. Jung earned his Ph.D. from the University of Heidelberg (2009) and a diploma from the University of Dortmund (2004). Education: Ph.D. in Physics, University of Heidelberg, 2009 (Dissertation: D* Meson Cross Section Measurement) Diploma in Physics, University of Dortmund, 2004 (Commissioning of H1 Fast Track Trigger) Research Interests: High Energy Physics, Particle Physics, Detector Development, Quantum Computing Applications, Material Science for Detectors, and Collider Experiments. His work includes analyzing top quark spin correlations, quantum annealing for vertex reconstruction, and carbon fiber composites for CMS upgrades. Awards: Senior Distinguished Researcher fellowship at Fermilab LHC Physics Center (2019) 3-year PhD scholarship from German Research Society (2004–2007) Teaching & Leadership: Teaches courses on particle physics and data science. Serves as Convener of CMS TOP Physics Analysis Group and leads detector mechanics R&D. Engages in quantum computing collaborations with DoD and industry partners. Labs/Teams: Jung Research Group at Purdue, CMS Collaboration, and Purdue Quantum Science & Engineering Institute (PQSEI). Active in detector development for the High-Luminosity LHC upgrade, including carbon fiber support structures and silicon pixel detectors.