جست‌وجوی استاد و پژوهشگر

Natalie Simpsonمشاهده پروفایل

استاد

• Emergency Response Operations
• Supply Chain Logistics
• Educational Technology

Dr. Natalie Simpson is Professor and Associate Dean for Graduate Programs at the University at Buffalo's School of Management, Department of Operations Management and Strategy. She holds a PhD and MBA from the University of Florida, and a BFA from North Carolina School of the Arts. Her research explores emergency response systems , supply chain logistics , and educational technology , with particular focus on operational challenges in crisis management. She investigates hyper-project coordination in emergency contexts and resource allocation frameworks for incident commanders. Simpson's scholarly contributions show strong emphasis on: Modeling emergency response operations and supply chain vulnerabilities Developing pedagogical innovations for operations management education Analyzing healthcare workflow efficiency and disaster management systems Her extensive recognition includes: Decision Sciences Institute's Best Case Studies Award (2005) National Instructional Innovation Award (2004) SUNY Chancellor's Award for Excellence in Teaching (2002) Grinter Fellowship and Matherly Scholarship As Academic Director of Digital Access Education, she leads technology-enhanced learning initiatives and advises graduate programs. Administrative responsibilities include heading the Digital Access Working Group and serving on editorial boards for Decision Sciences.

Tim Cohenمشاهده پروفایل

دانشیار

• Particle Physics
• Large Hadron Collider Phenomenology
• Effective Field Theory
• +۵ مورد دیگر

Tim Cohen is an Associate Professor of Physics at the University of Oregon, with affiliations at CERN and EPFL's Lausanne Theory Physics Laboratory. He is based at the Institute for Fundamental Science within the Department of Physics at the University of Oregon's College of Arts and Sciences. His research focuses on theoretical particle physics, particularly exploring phenomena beyond the Standard Model. Dr. Cohen's research interests center on particle physics beyond the Standard Model, with specific expertise in Large Hadron Collider phenomenology, effective field theory, electroweak naturalness, and dark matter. His work bridges theoretical frameworks with experimental possibilities at major particle physics facilities. His research program encompasses both theoretical developments in quantum field theory and practical applications to collider physics and cosmology. Analysis of his recent publications reveals a strong focus on effective field theory applications, de Sitter space physics, and dark sector phenomenology. His work demonstrates sophisticated mathematical approaches to problems in quantum field theory while maintaining connections to observable phenomena at particle colliders and in cosmological settings. He frequently collaborates with researchers across institutions including CERN, EPFL, and various US universities. Dr. Cohen serves as a senior researcher with active roles at multiple institutions, contributing to major collaborative efforts such as the Snowmass community planning process for particle physics. His work appears in leading journals including Journal of High Energy Physics, Physical Review D, and Physics Letters B, demonstrating consistent productivity and impact in the field. His research group operates within the Institute for Fundamental Science at the University of Oregon, with additional connections to theoretical physics groups at CERN and EPFL. This international collaboration network enables him to work at the intersection of theoretical developments and experimental frontiers in particle physics.

Steven Swansonمشاهده پروفایل

استاد

• Non-Volatile Memory
• Persistent Memory Systems
• Storage Systems
• +۱۲ مورد دیگر

Steven Swanson is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego, within the Jacobs School of Engineering. He is the Director of the Non-Volatile Systems Laboratory (NVSL), where he leads cutting-edge research in non-volatile memory, storage systems, and hardware-software co-design. His work bridges computer architecture, systems, and software to develop efficient, reliable, and secure computing platforms. Ph.D., University of Washington, 2006 B.S., University of Puget Sound, 1999 Dr. Swanson's research centers on non-volatile and persistent memory systems , exploring how next-generation storage technologies can transform computing. His lab develops full-stack solutions including file systems like NOVA and Orion , programming models such as NV-Heaps , and hardware prototypes like Moneta and Onyx . The team also works on low-power co-processors (e.g., GreenDroid ) and tools for debugging and verifying persistent memory programs. Research spans system reliability, security, energy efficiency, and performance optimization. His recent publications reveal a strong focus on persistent memory safety , zero-copy I/O , RDMA-based distributed file systems , and real-world characterization of Intel Optane . These works appear in top venues including ASPLOS, FAST, MICRO, and USENIX ATC, demonstrating sustained innovation in storage and systems research. Scientific honors include: NSF CAREER Award Google Faculty Award Facebook Faculty Award NetApp Faculty Fellow Dr. Swanson has advised 15 PhD students and 4 postdocs , many now faculty or senior engineers at Google, Microsoft, Intel, and other leading tech firms. He has secured significant research funding and leads major community initiatives such as the annual Non-Volatile Memories Workshop and Persistent Programming In Real Life (PIRL) . His educational efforts include innovative courses on robotic system design, quadcopter building, and modern storage systems, emphasizing hands-on learning and real-world implementation. The Non-Volatile Systems Laboratory (NVSL) under his leadership fosters a collaborative, international research environment, hosting visitors and postdocs from around the world. The lab is recognized globally as a pioneer in storage systems research and a key contributor to the adoption of persistent memory technologies in industry.

Aspy P. Paliaمشاهده پروفایل

استاد

• Marketing Decision Support Systems
• Countertrade in Asia-Pacific
• Strategic Market Planning
• +۴ مورد دیگر

Aspy P. Palia is a Professor of Marketing at the Shidler College of Business, University of Hawaii at Manoa. He has held academic roles since 1984, including visiting professorships at institutions such as Singapore Management University, Chulalongkorn University, and the National University of Singapore. His research focuses on Marketing Decision Support Systems, Countertrade in Asia-Pacific, and experiential learning methodologies. He has published extensively in journals like European Journal of Marketing and Developments in Business Simulation and Experiential Learning , with a recent emphasis on virtual scaffolding and engagement in educational simulations. His work has earned multiple best paper awards and nominations. Dr. Palia's education includes a DBA in International Business from Kent State University (1985), an MBA from the University of Hawaii (1976), and a BS in Mechanical Engineering from the University of Bangalore (1966). His teaching spans global institutions, emphasizing strategic marketing and decision-making tools. Notable awards include the 2017 Marquis Lifetime Achievement Award and the 2011 Fellowship from the Association for Business Simulations and Experiential Learning. His research contributions bridge theoretical marketing frameworks with practical applications, particularly in leveraging technology for pedagogical innovation. Collaborations with organizations like the Japan America Institute of Management Science further underscore his engagement with global academic networks.

Hamza Salih Erdenمشاهده پروفایل

دانشیار

• Data Center Energy Efficiency
• Computational Fluid Dynamics
• Thermal Management
• +۳ مورد دیگر

Hamza Salih Erden is an Associate Professor (Docent) at the Informatics Institute of Istanbul Technical University in Turkey. His research focuses on energy optimization in data centers, thermal management systems, and computational fluid dynamics applications. With over 34 research outputs and an h-index of 12, he leads projects in energy-grid integration and carbon-aware load management. Research Focus Dr. Erden's work centers on improving energy efficiency in technological infrastructure through: Advanced cooling techniques for data centers Integration of thermal energy storage systems Computational fluid dynamics modeling Demand-response optimization for smart grids AI-driven monitoring of energy systems Publication Trends Recent works (2022-2025) demonstrate strong focus on sustainable energy technologies, particularly optimization of data center operations through thermal management innovations, integration of renewable energy solutions, and AI applications for system monitoring. Economic assessments of energy-saving techniques feature prominently. Awards and Recognition Technical Paper Award (2016) Multiple International Scientific Publication Incentive Awards (2017-2021) Poster Award (2012) Graduate Student Grant (2007) Projects and Funding Leads multiple energy research projects including: Carbon-aware load management in data centers (2025) Grid-integrated energy system modeling for data centers (2021-2023) CFD analysis of CRAH bypass methods (2018-2020) Economizer applications in Turkish data centers (2016-2017)

Nina Balcanمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Theoretical Computer Science
• +۵ مورد دیگر

Nina Balcan is the Cadence Design Systems Professor of Computer Science at Carnegie Mellon University's School of Computer Science, with affiliations in both the Machine Learning Department (MLD) and Computer Science Department (CSD). She maintains her office in Gates Hillman Center (GHC) 8205 and is a prominent figure in theoretical machine learning and algorithmic game theory. Her research spans multiple critical areas in computer science, with a strong focus on the theoretical foundations of machine learning, algorithm design and analysis, and computational approaches to game theory and economics. Balcan has made significant contributions to developing principled algorithms for deep learning, learning with limited supervision, representation learning, and life-long learning. Her work uniquely bridges theoretical computer science with practical applications, particularly in the analysis of complex objects and processes, including algorithmic learning and multi-agent systems. Analysis of her recent publications reveals a strong trend toward data-driven algorithm design, with particular emphasis on learning to optimize combinatorial algorithms, revenue-maximizing mechanisms, and robust learning frameworks. Her work consistently demonstrates how theoretical guarantees can inform practical algorithm development across diverse domains from optimization to economics. Major Awards and Honors: ACM Fellow AAAI Fellow Simons Investigator 2019 ACM Grace Murray Hopper Award (awarded to the outstanding young computer professional of the year) Winner of Outstanding Student Paper Award at UAI 2024 Winner of Exemplary Artificial Intelligence Track Paper Award at ACM EC 2019 Runner Up Best Paper Award at COLT 2012 Professor Balcan has served as Program Committee Co-chair for major conferences including NeurIPS 2020, ICML 2016, and COLT 2014, demonstrating her leadership in the machine learning community. Her teaching portfolio at CMU includes foundational courses such as 10-701 Machine Learning, 10-315 Machine Learning, and 10-715 Advanced Introduction to Machine Learning, where she has mentored numerous students in both theoretical and applied aspects of the field. Her research group focuses on developing theoretically sound yet practically applicable machine learning algorithms, with particular attention to algorithm configuration, data-driven optimization, and learning in strategic environments. Current projects involve learning to improve combinatorial algorithms, designing revenue-maximizing mechanisms, and developing robust learning frameworks that can operate effectively in challenging environments.

• Operations Management
• Healthcare Operations
• Queueing Theory
• +۳ مورد دیگر

Mustafa Akan is an Associate Professor of Operations Management at the Tepper School of Business, Carnegie Mellon University . He holds a Ph.D. in Managerial Economics and Strategy from Northwestern University (2008) and a B.Sc. in Industrial Engineering from Carnegie Mellon University (2004). Research Interests : His work focuses on healthcare operations management , queueing theory , and dynamic pricing strategies . He investigates efficient resource allocation in service systems, equity in organ transplantation, and optimization of remanufacturing processes under uncertainty. His research bridges applied mathematics , computation theory , and business strategy . Article Trends : Recent publications address liver allocation equity (2025), two-sided market pricing (2025), and task allocation in tandem queueing systems (2024). Earlier works explore transplant health disparities (2024), remanufacturing procurement (2023), and fashion product pricing (2021). Common themes include service science , healthcare operations , and policy-driven optimization . Scientific Awards : Best Dissertation Award (INFORMS Aviation Applications Section, 2008) Xerox Faculty Chair (2009) INFORMS Best Paper in Service Science (2009) POMS Healthcare Best Paper Award (2012) Lave-Weil Prize (2013) Gerald L. Thompson Teaching Award (2014) NSF CAREER Award (2014) Mehrotra Research Excellence Award (2024) DEIJ Best Paper Award (2023) Teaching & Grants : He teaches courses like Healthcare Operations , Risk Analytics , and Demand Management & Price Optimization . His NSF CAREER Award (2014) supports research in operational systems. He has served on committees for INFORMS , POMS , and Naval Research Logistics .

• Computer Science
• Algorithmic Transparency
• AI Ethics
• +۷ مورد دیگر

Jeanna Matthews is a Full Professor of Computer Science at Clarkson University and an affiliate at Data and Society. She holds a PhD from UC Berkeley (1999) and teaches courses ranging from operating systems to cybersecurity. Her research focuses on algorithmic transparency, AI ethics, and societal impacts of automated systems. Matthews is a prominent ACM leader, serving on multiple committees including the Technology Policy Subcommittee on AI Accountability. She has pioneered work on forensic software analysis in criminal justice systems and delivered DEF CON presentations on virtualization security and adversarial testing. Awards include ACM Distinguished Speaker and Fulbright Specialist roles. Her work emphasizes open-source tools and critical thinking in education, extending to global service learning programs in the Dominican Republic and Brazil. Education: PhD in Computer Science (UC Berkeley, 1999), B.S. in Math/Computer Science (Ohio State, 1994), B.A. in Spanish (SUNY Potsdam, 2016). Research Interests: Cybersecurity vulnerabilities, algorithmic accountability frameworks, automated decision systems in justice contexts, and ethical AI design. Recent projects include investigating bias in DNA forensic software through a Brown Institute grant and analyzing political polarization on social platforms. Awards & Recognition: ACM Distinguished Speaker (2018-present) Fulbright Specialist (2018-present) 2018-2019 Brown Institute Magic Grant ACM SIGOPS Chair (2011-2015) ACM Special Interest Group Governing Board Chair (2016-2018) Teaching & Outreach: Designed courses integrating open-source tools and critical inquiry, including abroad programs in Mexico, Brazil, and the Dominican Republic. Advocates for lifelong learning strategies and questioning underlying assumptions in computing systems. Key Projects: Forensic Software Accountability: Examining discrepancies in DNA analysis tools Algorithmic Transparency: Frameworks for auditing automated systems Cybersecurity Education: Adversarial testing methodologies for justice software

Geoffrey Tranmerمشاهده پروفایل

دانشیار

• Medicinal Chemistry
• Drug Discovery
• Organic Synthesis
• +۴ مورد دیگر

Geoffrey Tranmer is a Tenured Associate Professor in the College of Pharmacy at the University of Manitoba. His research integrates medicinal chemistry, drug discovery, and synthetic organic methodologies, with a focus on flow chemistry and targeted cancer therapies. NSERC Post-Doctoral Fellow, University of Cambridge Post-Doctoral Fellow, Princeton University PhD in Organic Chemistry, University of Guelph BSc (Hons) in Chemistry, Brock University His research explores: Development of flow chemistry techniques to enhance synthetic organic methods Lead generation and optimization in drug discovery Bioconjugation strategies for chemical biology applications Targeted cancer therapies leveraging hypoxia-activated prodrugs Recent publications highlight his work in neurodegenerative disease drug design, biomarker discovery, and sustainable synthesis technologies. Scientific Awards CIHR Project Grant (2024-2029) NSERC Discovery Grant (2023-2028) CIHR Bridge Grant (2022) NSERC Alliance Grant (2020) NSERC Engage Grant (2017) Research Manitoba New Investigator Operating Grant (2017) Dr. Tranmer's industrial experience at Merck Frosst and academic leadership at Manitoba position him uniquely to bridge chemistry-biology-industry collaborations. His lab actively trains graduate students in cutting-edge synthesis platforms.

Ralph Evinsمشاهده پروفایل

دانشیار

• Building Energy Simulation
• Energy System Optimization
• Machine Learning Applications in Energy
• +۳ مورد دیگر

Dr. Ralph Evins is an Associate Professor and Director of the Graduate Program in the Department of Civil Engineering at the University of Victoria. He holds affiliations with the Urban Energy Systems laboratory at Empa and ETH Zurich in Switzerland. His expertise spans building energy simulation, energy system optimization, and machine intelligence applications in sustainable design. Evins holds an MEng from Imperial College London and an EngD from the University of Bristol. His research focuses on computational problem-solving in energy systems, including surrogate modeling, optimization algorithms, and machine learning. He develops tools like the Holistic Urban Energy Simulation (HUES) platform and BESOS software framework to bridge building, district, and city-scale energy analysis. His work emphasizes holistic systems thinking, integrating energy hubs, thermal modeling, and digital twin technologies. Recent articles explore surrogate model refinement, inverse modeling for building characterization, and decarbonization strategies. He collaborates with industry to translate academic innovations into practical solutions. Evins advises students in energy systems and leads projects on net-zero building design, retrofit prioritization, and smart grid integration. His research addresses challenges in climate adaptation, energy efficiency, and sustainable urban development through interdisciplinary approaches.

Kylie Kingمشاهده پروفایل

مدرس ارشد

• suicide prevention
• program evaluation
• men's health
• +۳ مورد دیگر

Kylie King is a Senior Lecturer at the School of Psychological Sciences at Monash University and affiliated with the Turner Institute for Brain and Mental Health. She joined Monash University in November 2019 as an Impact Fellow and transitioned to her current Senior Lecturer role in February 2023, where she focuses on fostering research connections with industry, community, and people with lived experience. Her educational background includes a Doctor of Psychology from Deakin University (2001) and a PhD completed in early 2020 focusing on suicide prevention. Prior to joining Monash, she worked as a psychologist specializing in addictions and spent ten years (2009-2019) as a Research Fellow at the Melbourne School of Population and Global Health at the University of Melbourne. Dr. King's research primarily centers on suicide prevention, with particular emphasis on males and communities experiencing disproportionate suicide rates. Her work integrates program evaluation methodologies to develop targeted interventions and suicide prevention education. She leads research teams focused on creating evidence-based approaches to address mental health challenges in vulnerable populations. Her research aligns with UN Sustainable Development Goals related to health and wellbeing. Analysis of her recent publications reveals a strong focus on gender-specific suicide prevention, particularly for men and older males, as well as attention to culturally specific approaches for Indigenous communities. Her work bridges clinical psychology with public health interventions, examining how societal factors, occupational environments, and cultural contexts influence mental health outcomes and suicide risk. Associate Editor, Australian Psychologist Journal (2020-present) Associate Editor, Australian Psychologist Journal (2021-present) Guest Editor, Frontiers in Public Health (2020) Dr. King is actively involved in peer review responsibilities and currently leads significant research projects including "Preventing suicide in boys and men" (2020-2026), "Formative evaluation of suicide prevention gatekeeper training for aged care workers" (2023-2025), and "Zest – A personalised, digital intervention for sleep and wellbeing in Australian shift workers" (2023-2026). She is accepting PhD students for research supervision through Monash University's Supervisor Connect platform. Her research team operates at the intersection of clinical psychology and public health, developing evidence-based interventions for vulnerable populations with strong emphasis on community-centered approaches and collaboration with individuals with lived experience of mental health challenges.

Lenya Ryzhikمشاهده پروفایل

استاد

• Partial Differential Equations
• Analysis
• Applied Mathematics
• +۵ مورد دیگر

Lenya Ryzhik is a Professor in the Department of Mathematics at Stanford University, specializing in analysis and partial differential equations with applications in various physical contexts. His research spans stochastic processes, wave propagation, and front dynamics in random media, with significant contributions to understanding reaction-diffusion systems and their applications in mathematical biology and physics. Professor Ryzhik's research interests focus on the mathematical analysis of partial differential equations arising in physical systems. His work particularly emphasizes stochastic PDEs, wave propagation in random media, front propagation in reaction-diffusion systems, and homogenization theory. He investigates how randomness and complex structures affect wave propagation, front speeds, and transport phenomena, with applications ranging from combustion theory to population dynamics and quantum mechanics. The publication record demonstrates a consistent focus on understanding propagation phenomena in complex environments. Ryzhik's research shows a progression from classical PDE analysis toward increasingly sophisticated stochastic frameworks, particularly examining high-dimensional systems and random media. His recent work has focused on KPZ fluctuations, random heat equations, and non-local reaction-diffusion models, revealing deep connections between probability theory and partial differential equations. Alfred P. Sloan Research Fellowship (2002-2004) AFOSR NSSEFF Fellowship (2010-2015) Ryzhik has advised graduate students including Alexandra Stavrianidi, and has secured substantial research funding throughout his career. His grant history includes multiple NSF awards (DMS-9971742, DMS-0203537, DMS-0604687, DMS-0908507, DMS-1311903), ONR funding (N00014-02-1-0089, N00014-04-1-0224), and FRG support for collaborative research on nonlinear evolution problems. He co-organized a Summer School and Workshop on 'Recent Advances in PDEs and Fluids' at Stanford in 2013. Ryzhik maintains an active research group collaborating with leading mathematicians worldwide, particularly with researchers at institutions like NYU, Chicago, and various European universities. His work frequently involves interdisciplinary collaborations bridging mathematics with physics and biology.

Dimitrios Tsaoulidisمشاهده پروفایل

مدرس ارشد

• Clean Energy
• Process Intensification
• Multiphase Flow Dynamics
• +۶ مورد دیگر

Dimitrios Tsaoulidis is a Senior Lecturer in Chemical Engineering at the University of Surrey and an Honorary Lecturer at University College London . He holds a PhD in Chemical/Nuclear Engineering and a Diploma in Chemical Engineering. University roles: Academic Integrity Officer, Senior Personal Tutor, Disability & Neurodiversity Representative Research spans clean energy (nuclear, bio, solar), healthcare (bioprocess scalability), and manufacturing using process intensification and microfluidics . His work combines experimental investigation , CFD simulations , and scale-up optimization for multiphase reactors . Notable research trends include: 15+ publications (2012–2023) on uranium extraction , biodiesel production , and pharmaceutical microfluidics , with grants from UKRI and Innovate UK . Scientific Awards : David Newton’s Award for Sustainability (UCL) Springer Thesis Award Fellow of the Higher Education Academy (FHEA) Associate Member of the Institution of Chemical Engineers (AMIChemE) Research Collaborations : Academic : Prof Panagiota Angeli (UCL), Prof Eric Fraga (UCL), Dr Maryam Parhizkar (UCL) Industrial : UK Atomic Energy Authority, National Nuclear Laboratory, GSK, Greenergy Ltd, Armfield Dr Tsaoulidis supervises PhD students (e.g., Mustapha Hamdan, Anna Tsitouridou) and PDRA staff (e.g., Dr Jamshid Zarkesh) in projects related to solar energy systems , nuclear fuel cycles , and pharmaceutical automation .

Xiaolei Fangمشاهده پروفایل

دانشیار

• Statistical Learning
• Deep Learning
• Federated Learning
• +۳ مورد دیگر

Xiaolei Fang is Associate Professor in the Edward P. Fitts Department of Industrial and Systems Engineering at North Carolina State University. His research develops advanced statistical learning, deep learning, and optimization methods for industrial applications involving high-dimensional data, with particular focus on condition monitoring, failure prognostics, and system performance optimization. He holds a PhD in Industrial Engineering and MS in Statistics from Georgia Tech. Professor Fang's research integrates machine learning with industrial engineering to solve complex problems in predictive maintenance, quality control, and energy systems. His methodological innovations include federated learning approaches for privacy-preserving prognostics, distributionally robust machine learning models, and tensor-based statistical methods for manufacturing quality diagnostics. He has received multiple prestigious awards including the ISE Outstanding Research Award (2024), Sigma Xi Best PhD Thesis Award (2019), and SAS Data Mining Best Paper Award (2016). His research has been funded by NSF, Cisco Systems, and the US Department of Energy. Professor Fang teaches courses in Quality Design & Control, Statistical Models for Systems Analytics, High-Dimensional Data Analytics, and Optimization Models. He has supervised 9 PhD students to completion and currently advises 7 graduate students working on projects spanning federated learning for prognostics, tensor-based quality control, and machine learning applications in manufacturing and energy systems.

Andrei Jorzaمشاهده پروفایل

دانشیار

• Number Theory
• Algebraic Geometry
• Representation Theory
• +۴ مورد دیگر

Andrei Jorza is an Associate Professor of the Practice in the Department of Mathematics at the University of Notre Dame. His research focuses on the interplay between number theory and algebraic geometry, including topics such as modular forms, Galois representations, p-adic Hodge theory, and arithmetic geometry. He holds an A.B. from Harvard University (2005) and a Ph.D. from Princeton University (2010), advised by Andrew Wiles. Prior to his current position, he was a Taussky-Todd Instructor at Caltech and a member of the Institute for Advanced Study (IAS). Dr. Jorza has taught advanced courses on p-adic Hodge theory, global class field theory applications, algebraic number theory, and graduate algebra. His work includes significant contributions to computational verification of the Birch and Swinnerton-Dyer conjecture and studies on Galois representations for Siegel modular forms. His research also extends to topics like Lagrangian hyperplanes in holomorphic symplectic varieties and eigenvarieties in automorphic forms. He is affiliated with Notre Dame's Department of Mathematics, located in 275 Hurley Hall, and actively participates in seminars on algebraic geometry and commutative algebra. His lecture notes and courses reflect a deep engagement with foundational topics in number theory and algebra, emphasizing adelic methods and applications of class field theory.