جست‌وجوی استاد و پژوهشگر

João Paulo Costeiraمشاهده پروفایل

دانشیار

• Computer Vision
• 3D Reconstruction
• Structure from Motion
• +۳ مورد دیگر

João Paulo Costeira is an Associate Professor at the Department of Electrical and Computer Engineering, Instituto Superior Técnico (IST), Lisbon. He holds a PhD in Electrical and Computer Engineering from IST (1995) and was a Visiting Scientist at Carnegie Mellon University's Robotics Institute (1991–1995). His research focuses on Computer Vision, 3D Reconstruction, and Structure from Motion, with contributions to object recognition, robotics, and multimedia analysis. Education: PhD in Electrical and Computer Engineering, IST (1995); Visiting Scientist, CMU Robotics Institute (1991–1995). Roles: Coordinator of the Signal and Image Processing Group (SIPg), Co-director of the Carnegie Mellon|Portugal Dual PhD Program in ECE and Robotics (2007–2018), and Scientific Director of Carnegie Mellon|Portugal (2014–2018). Research Interests: João's work emphasizes 3D reconstruction from video, rigid and non-rigid motion analysis, and applications in robotics and urban surveillance. He has pioneered methods for motion segmentation and robust correspondence problems in computer vision. Publications: His recent work includes advancements in apple counting systems, rotation averaging for robotics, and domain adaptation for traffic density estimation. These contributions highlight his expertise in real-world computer vision challenges. Awards: None explicitly listed. However, his extensive publication record and academic leadership reflect significant scholarly impact. Advising & Grants: Supervised 13 PhD students, many co-advised with CMU faculty. Active in projects like CityCam (vehicle counting) and MultiDrone (robotics collaboration). Funded by FCT, EU, and industry partnerships. Labs/Teams: Leader of the Signal and Image Processing Group (SIPg) at ISR. Involved in NETSyS program for networked systems and robotics.

Navid Izadyمشاهده پروفایل

مدرس ارشد

• Operations Research
• Healthcare Management
• Stochastic Modelling
• +۳ مورد دیگر

Dr. Navid Izady is a Reader in Operations & Supply Chain at Bayes Business School, part of City St George's, University of London. His academic career includes a PhD from Lancaster University Management School (2010), and prior roles at the University of Southampton. He specializes in stochastic modelling for healthcare and manufacturing operations, collaborating with hospitals and healthcare organizations on sponsored research and consultancy projects. Dr. Izady holds qualifications in Industrial Engineering from Sharif University of Technology (BSc and MSc) and a PhD in Management Science. He teaches operations management, stochastic modelling, healthcare modelling, and decision analysis across BSc, MSc, and MBA programs. His research focuses on optimizing healthcare logistics, patient flow management, and resource allocation in hospitals. He has developed frameworks for managing pandemic and non-pandemic demand, reconfiguring inpatient services, and optimizing staffing and patient admission/discharge processes. His work bridges theoretical stochastic models with practical healthcare challenges, emphasizing operational efficiency and resilience. Notable contributions include studies on inpatient bed pressure reduction, sample pooling techniques for pandemic testing, and queueing theory applications in emergency departments and specialty clinics. His publications highlight innovations in healthcare operations management and simulation methods. Dr. Izady's expertise includes operations research, simulation, statistics, and stochastic processes. He supports industry partnerships and has supervised numerous research students, contributing to both academic and applied knowledge in healthcare and manufacturing systems.

• Organoid Engineering
• Systems Biology
• Developmental Biology
• +۳ مورد دیگر

Keisuke Ishihara is an Assistant Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His research focuses on engineering human brain and cardiac organoids using genetic, chemical, and computational approaches to uncover novel regulatory mechanisms and physical principles underlying tissue development. His lab is located at Biomedical Science Tower 3, with an office in room 10020A. Dr. Ishihara holds a PhD in Systems Biology from Harvard University. His work bridges synthetic biology, developmental biology, and biophysics to address fundamental questions in organogenesis and cellular morphogenesis. Recent research highlights include studies on BMP-mediated neural tube patterning in organoids and the biophysical dynamics of microtubule assemblies in large cells. Publications from his lab emphasize interdisciplinary approaches to understand cell size scaling, mitotic spindle dynamics, and self-organization in synthetic tissues. His team has contributed to advancements in organoid technology, uncovering dormant genetic programs and physical principles governing tissue architecture. Laboratory activities are centered at the University of Pittsburgh, collaborating with the School of Medicine's computational and systems biology initiatives. For more details, visit his lab website linked below.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

Robert G. Blandمشاهده پروفایل

استاد

• Linear Programming
• Combinatorial Optimization
• Network Flow Theory
• +۳ مورد دیگر

Robert G. Bland is a Professor at Cornell University's School of Operations Research and Information Engineering (ORIE). He joined Cornell in 1978 after roles at SUNY Binghamton and research fellowships in Belgium. He is affiliated with the Center for Applied Mathematics and specializes in linear programming, combinatorial optimization, and network flow theory. His research emphasizes algorithmic efficiency, duality theory, and applications in scheduling and resource allocation. Education: B.S. (1969), Cornell University M.S. (1972), Cornell University Ph.D. (1974), Cornell University Research Interests: Focuses on linear programming duality, combinatorial abstractions, computational methods for optimization, and applications in logistics, scheduling, and scientific computing. Notable work includes the development of new pivoting rules for the simplex method and empirical studies of network flow algorithms. Publications Insight: His work spans foundational LP theory, combinatorial optimization, and algorithmic analysis. Key themes include duality frameworks, Camion bases, and large-scale TSP applications in crystallography. Recent publications address abstract dualities and historical perspectives on pioneers like D. Ray Fulkerson. Awards: Recipient of Cornell's prestigious Merrill Outstanding Educator Award (3 times) and twice recognized as ORIE's best teacher. Member of the Mathematical Optimization Society and American Society for Engineering Education. Grants & Projects: Conducted service projects on vehicle routing and examination scheduling. Collaborated on computational studies of min cost flow algorithms and network flow performance. Labs/Teams: Active in ORIE's research groups, particularly those focused on optimization theory and computational methods.

Aliasghar Arabmaldarمشاهده پروفایل

استادیار

• Operations Research
• Data Envelopment Analysis
• Robust Optimization
• +۴ مورد دیگر

Aliasghar Arabmaldar is an Assistant Professor in Business Analytics and Systems (BAS) at the Hertfordshire Business School, University of Hertfordshire. He holds a PhD in Operations Research from the University of Sistan and Baluchestan (2017), an MSc in Applied Mathematics-Operations Research from the University of Guilan (2011), and a BSc in Applied Mathematics from the same institution (2009). His research focuses on robust optimization, data envelopment analysis (DEA), decision-making under uncertainty, and performance evaluation in complex systems. Key research interests include: Developing robust DEA models to handle uncertainty in data Resilience-efficiency trade-offs in retail logistics Network production processes and efficiency measurement Integration of undesirable outputs in performance evaluation Recent work emphasizes application in retail management, oil industries, and higher education sectors. His 2025 project, 'Enhancing Research Publication Skills Through Writing Retreats,' highlights his commitment to academic development. Peer-reviewed contributions appear in top journals like European Journal of Operational Research and Expert Systems with Applications. He serves as a reviewer for 12+ journals including OMEGA and Operations Research Spectrum, demonstrating his influence in operational research and analytics.

Mahdi Asgariمشاهده پروفایل

دانشیار

• Automorphic Forms
• Number Theory
• Representation Theory
• +۱ مورد دیگر

Mahdi Asgari is an Associate Professor in the Department of Mathematics at Oklahoma State University. He specializes in Automorphic Forms , Number Theory , and Representation Theory , with a focus on L-functions, local Langlands conjectures, and functoriality for classical and spin groups. PhD in Mathematics from Purdue University (2000) Active in organizing the Texas-Oklahoma Representations and Automorphic Forms (TORA) conference series since 2012 His recent research involves Rankin-Selberg L-functions, combinatorics of Arthur trace formulas, and toric varieties. He has collaborated with prominent mathematicians like Freydoon Shahidi, Ralf Schmidt, and James W. Cogdell. Mahdi Asgari has taught a wide range of courses at Oklahoma State University, including advanced linear algebra, combinatorics, calculus, and specialized topics like automorphic forms on GL(n) and spectral theory of automorphic forms.

Behzad Alaeiمشاهده پروفایل

دانشیار

• Structural Geology
• Sedimentary Basin Analysis
• Fault Zone Architecture
• +۶ مورد دیگر

Behzad Alaei serves as an Associate Professor in the Section for Study of Sedimentary Basins within the Department of Geosciences at the University of Oslo's Faculty of Mathematics and Natural Sciences. His office is located in room K38 of the Geology Building at Sem Sælands vei 1, 0371 Oslo, with a professional email contact at behzad.alaei@geo.uio.no. Dr. Alaei maintains an active research profile with publications spanning from 2005 to the present, demonstrating his ongoing contributions to geological sciences. Dr. Alaei's research spans multiple critical areas within structural geology and sedimentary basin analysis, with particular expertise in fault zone architecture, seismic interpretation techniques, and CO2 storage site assessment. His work bridges theoretical geological concepts with practical applications in petroleum geology and carbon sequestration. A significant portion of his research focuses on the Norwegian Barents Sea region, where he has conducted extensive studies on normal fault systems and their geometric characteristics. His recent work increasingly integrates machine learning and deep learning approaches with traditional geological analysis, reflecting the evolving nature of geoscience research methodology. The analysis of Dr. Alaei's publication record from 2018-2024 reveals a strong thematic continuity in fault characterization research, with progressive incorporation of advanced computational methods. Early publications focused primarily on traditional structural analysis of fault systems in sedimentary basins, while more recent work demonstrates increasing integration of machine learning techniques for fault detection and characterization. A notable trend is the application of these geological insights to practical challenges in carbon capture and storage, particularly regarding fault risk assessment for CO2 storage sites in the North Sea region. His collaborative work with Anita Torabi appears consistently throughout this period, suggesting a strong research partnership. Dr. Alaei maintains an active research program with multiple ongoing projects related to sedimentary basin analysis and fault characterization. His work appears to involve significant collaboration with both academic and industry partners, particularly in the context of CO2 storage research. While specific grant details aren't provided in the available information, his consistent publication record across multiple high-impact journals suggests successful funding of his research activities over the past two decades.

Lena Wesselمشاهده پروفایل

استاد

• Mathematics Education
• Teacher Training
• Language Development in Education
• +۴ مورد دیگر

Prof. Dr. Lena Wessel is a Mathematics Education faculty member at the Department of Mathematics Didactics, Faculty of Electrical Engineering, Computer Science and Mathematics, University of Paderborn. She leads teacher training programs and participates in university governance as elected Faculty Council member. Research Focus: Her work centers on comprehension-oriented mathematics instruction at secondary/vocational levels, emphasizing language development, continuity in curriculum design (spiral principle), and digital mathematics tools. As DZLM network partner, she develops professional development programs for secondary educators. LiaNMU project (scalar products, plane reflections) VioLa project (digital discussion formats) LLV.HD project (cross-university learning networks) Key Contributions: She has coordinated major projects like MESUT (language-supported fraction understanding) and LaMaVoC (language in vocational mathematics). Her 2024 publications analyze language-integrated pedagogy and algebraic concept unification in teacher training.

Peter G. Troyanمشاهده پروفایل

دانشیار

• Microeconomic theory
• Game theory
• Market design
• +۳ مورد دیگر

Peter G. Troyan is an Associate Professor of Economics and Director of Graduate Studies at the University of Virginia, where he has served on the faculty since 2014. His research bridges theoretical and experimental economics with practical applications in market design, focusing on strategic behavior in matching systems and auction mechanisms. Education: Ph.D. in Economics, Stanford University (2014) B.S. in Mathematics (with High Honors) and Physics, University of Michigan (2008) Troyan's research centers on microeconomic theory with emphasis on game-theoretic foundations of market design. His work develops novel frameworks for matching under constraints, analyzes strategic manipulation in allocation mechanisms, and pioneers experimental validations of theoretical predictions. Key contributions include formalizing 'obvious strategyproofness' as a solution concept and designing ranking methods that improve welfare in competitive matching processes. His interdisciplinary approach integrates experimental economics to test theoretical models in real-world settings like school choice and labor markets. His publication record reveals a consistent trajectory toward foundational contributions in mechanism design, with increasing focus on simplicity principles and behavioral realism. Recent work in Econometrica establishes theoretical limits of mechanism simplicity, while experimental studies in Games and Economic Behavior validate preference structures in matching markets. The recurring themes across his publications demonstrate how theoretical insights can be operationalized to solve allocation problems with distributional constraints. Scientific Awards: Best Paper Award and Exemplary Theory Paper Award at ACM Conference on Economics and Computation (EC19) UVA Quantitative Collaborative (2022) and Arts & Sciences Research Grant (2022) Roger Sherman Fellowship (2019-2020) and multiple university research grants Stanford and University of Michigan fellowships during graduate training Troyan directs the Economics Department's graduate program while securing continuous research funding, including five consecutive Bankard Fund grants (2017-2024) supporting his theoretical and experimental work. His service includes editorial roles at the American Economic Journal: Microeconomics and extensive peer review for top economics journals. As an active conference participant, he regularly presents at the ACM Conference on Economics and Computation and Econometric Society meetings, contributing to the market design research community through the University of Virginia Bankard Workshop in Economic Theory. His leadership extends to mentoring graduate students in economic theory research and collaborating with international scholars like Marek Pycia and Thayer Morrill. Current projects explore desirable ranking methodologies and the boundaries of strategyproof allocation mechanisms, positioning his work at the forefront of market design theory.

Elad Hazanمشاهده پروفایل

استاد

• Machine Learning
• Mathematical Optimization
• Control Theory
• +۴ مورد دیگر

Elad Hazan is a Professor of Computer Science at Princeton University and co-founder/director of Google AI Princeton. His research focuses on algorithmic foundations of machine learning and optimization, with significant contributions to online learning, nonstochastic control, and adaptive gradient methods. Princeton University (Faculty) Google AI Princeton (Co-founder & Director) His work bridges mathematical optimization, control theory, and computational complexity. Key contributions include the AdaGrad algorithm, sublinear-time optimization methods, and spectral filtering techniques for sequence modeling. Recent research emphasizes efficient neural architectures and provable guarantees in online control. Scientific awards include the Bell Labs Prize, IBM Goldberg Best Paper Award (twice), Google Research Award (twice), European Research Council grant, Marie Curie fellowship, and ACM Fellowship. He has served as program chair for COLT 2015 and on the Association for Computational Learning steering committee. His publications highlight trends in online convex optimization, spectral methods for dynamical systems, and adaptive gradient algorithms. Collaborations span Princeton, Google Brain Research, and interdisciplinary projects in robotics and AI safety.

Geoffrey Lindsay Hermanمشاهده پروفایل

استاد آموزشی

• Computer Science Education
• Engineering Education
• Learning Theories
• +۴ مورد دیگر

Dr. Geoffrey L. Herman serves as the Severns Teaching Professor in the School of Computing and Data Science at the University of Illinois at Urbana-Champaign. He earned his Ph.D. in Electrical and Computer Engineering from UIUC as a Mavis Future Faculty Fellow and completed postdoctoral research at Purdue University's School of Engineering Education. His research focuses on understanding how students learn engineering and computing concepts and developing systemic approaches to improve teaching methods in higher education. With over $7 million in research funding and more than 120 peer-reviewed publications, his work spans educational technology, cognitive aspects of learning, and faculty development initiatives. His recent publications demonstrate a consistent focus on evidence-based instructional practices, assessment methodologies, and collaborative learning approaches, with particular emphasis on computer science education, proof writing tools like Proof Blocks, and mastery learning techniques. These works collectively advance the understanding of effective educational strategies in STEM fields. IEEE Education Society Mac Van Valkenburg Early Career Teaching Award Scott H. Fisher Computer Science Teaching Award Best paper award in the first 50 years of the ACM Special Interest Group, Computer Science Education As a mentor, Dr. Herman guides graduate students interested in engineering and computing education research, focusing on designing better instruction. He also works with undergraduates on improving educational experiences through platforms like PrairieLearn. His leadership extends to founding the Grainger College of Engineering's Strategic Instructional Innovations Program, which has secured millions in external funding. He serves on the Computer Research Association Education committee and as associate editor for the Journal of Engineering Education. Dr. Herman leads national workshops on professional development for computer science teaching faculty and has created peer mentoring networks through the Teaching Professionals Program, significantly impacting faculty development in engineering education.

Ankush Agarwalمشاهده پروفایل

دانشیار

• Mathematical finance
• Data science in finance
• Financial statistics
• +۳ مورد دیگر

Ankush Agarwal is an Associate Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario. His research focuses on mathematical finance, financial statistics, and Monte Carlo methods, with applications to risk management and derivatives pricing. He supervises PhD students in quantitative finance and has taught courses on Monte Carlo methods and advanced financial modeling at Western University. Education: PhD in Mathematics from Tata Institute of Fundamental Research (2015) Research interests span regime-switching models, longevity risk hedging, stochastic differential equations, and rare event simulation. His work combines theoretical probability with computational techniques for financial applications. Recent publications include studies on McKean-Vlasov SDEs, implied Sharpe ratio estimation, and optimal portfolio strategies under stochastic volatility. These works demonstrate his expertise in stochastic processes and financial engineering. Supervision: Current PhD advisees include Ying Liao, Buchun Wang, and Shuya Zhang at the University of Glasgow. Former advisees include Yongjie Wang and Yihan Zou.

• Semiconductor Materials
• Laser Crystallization
• Phase Transformations
• +۴ مورد دیگر

Professor James Im serves as Professor of Materials Science in the Departments of Earth and Environmental Engineering and Applied Physics and Applied Mathematics at Columbia University, with an office at 1106 S.W. Mudd (Mail Code 4701). His academic career spans over three decades at Columbia, where he progressed from Assistant Professor (1991-1994) to Associate Professor (1995-2002), and ultimately to full Professor (2002-present), including a tenure as Chair of the Materials Science and Engineering Program (2002-2014). His educational background includes a B.S. with Distinction in Materials Science from Cornell University (1984) and a Ph.D. in Electronic Materials from MIT (1989), followed by postdoctoral research at Caltech (1989-1991). Cornell University: B.S. Materials Science (1984) MIT: Ph.D. Electronic Materials (1989) Caltech: Postdoctoral Scholar (1989-1991) Im's research centers on ultra-rapid phase transitions in beam-irradiated thin films, specifically focusing on laser crystallization of silicon films , energy-beam-induced melting and solidification , and nucleation in discontinuous phase transitions . His work employs experimental, computational, and theoretical approaches to develop innovative semiconductor materials for advanced displays, solar cells, and integrated circuits. Notably, his invention of Sequential Lateral Solidification (SLS) technology has been licensed to major display manufacturers (Samsung, LG, Sharp) and implemented in products by Apple, Blackberry, and Nokia. Current research focuses on advancing the Spot-Beam Crystallization (SBC) platform using fiber lasers for next-generation microelectronics. His publication record spans environmental aerosol studies (2019-2024), oilfield operations technology (2002-2014), and foundational atmospheric research (1980s), reflecting interdisciplinary expertise bridging materials science, environmental engineering, and petroleum technology. The most recent works emphasize low-cost sensor development and aerosol monitoring. Professional recognition includes membership in prestigious societies: Bohmisch Physical Society Sigma Xi Alpha Sigma Mu Materials Research Society American Physical Society Im's research group maintains strong industry connections through technology licensing and collaborative projects, particularly in display manufacturing. His leadership as former department chair demonstrates administrative commitment alongside scientific innovation. The laboratory leverages state-of-the-art laser systems and beam delivery optics for materials development, with recent focus shifting toward environmental monitoring applications while maintaining core semiconductor research.

• Health services research
• Implementation science
• Patient-reported outcomes
• +۶ مورد دیگر

Rachel Hess, MD, MS is Professor of Population Health Sciences and Internal Medicine and Associate Vice President for Research-Health Sciences at the University of Utah Schools of the Health Sciences. She co-directs the Utah Clinical and Translational Science Institute and was founding Chief of the Division of Health System Innovation and Research (2014-2022). A board-certified General Internist and internationally recognized health-services researcher, she focuses on translating evidence into practice through health-information technology and patient-centered outcomes. Education & Training MD – University of New Mexico School of Medicine MS Clinical Research – University of Pittsburgh Fellowship – General Internal Medicine & Women’s Health, University of Pittsburgh / VA Pittsburgh Medical Center Chief Residency – Internal Medicine, Western Pennsylvania Hospital Residency – Internal Medicine, Temple University Hospital BA Mathematics – Washington University in St. Louis Research Focus Dr Hess’s program is dedicated to improving patient-centered outcomes by leveraging implementation science, health-information technology, and patient-reported measures. Her work spans: Design and nationwide deployment of EHR-integrated clinical decision support for cancer genetics, lung-cancer screening, heart-failure management, and antibiotic stewardship. Large multi-site pragmatic trials (ADAPTABLE, RECOVER, BRIDGE, MAINTAIN) examining effectiveness, equity, and scalability of digital-health interventions. Women’s health across the lifespan, including studies on menopause, sexual function, and post-COVID sequelae. Advanced analytics linking patient-reported outcomes (PROs) with healthcare utilization and cost. Scientific Awards & Recognition Board Certification, American Board of Internal Medicine (Internal Medicine) Leadership of NIH RECOVER Consortium adult cohort—one of the largest studies of Long COVID worldwide Principal investigator on >$50 million in federal and foundation funding (PCORI, NHLBI, NCI, AHRQ, CDC) Leadership & Service As Associate Vice President for Research she sets strategic priorities for the Schools of Medicine, Nursing, Pharmacy, Dentistry, and Health. She co-chairs the Utah Clinical and Translational Science Institute, oversees campus-wide clinical-trials infrastructure, and mentors interdisciplinary teams spanning informatics, behavioral science, epidemiology, and clinical medicine. Laboratories & Teams Dr Hess leads the Health System Innovation and Research (HSIR) group—an interdisciplinary unit of data scientists, implementation researchers, clinicians, and patient partners—dedicated to rapid-cycle testing and national scale-up of digital-health solutions.