جست‌وجوی استاد و پژوهشگر

Ahmad Ibrahimمشاهده پروفایل

دانشیار

• Internet of Things
• Fog Computing
• Cloud Computing
• +۷ مورد دیگر

Dr. Ahmad Ibrahim is an Associate Professor in Computer Science at the University of Birmingham Dubai, where he serves as the Undergraduate Programme Director and Year 2 Coordinator for BSc students. He is also the School Outreach Coordinator for the Computer Science program at the Dubai campus. Educational Background: Postgraduate Certificate in Higher Education (PGCHE), University of Birmingham, 2021 Fellow of the Higher Education Academy (FHEA), University of Birmingham, 2021 PhD in Computer Science, University of Pisa, Italy, 2016 MSc in Computer Science, Korea Advanced Institute of Science and Technology (KAIST), South Korea, 2009 BSc in Computer System Engineering, G.I.K Institute of Engineering Sciences and Technology, Pakistan, 2005 Dr. Ibrahim's research focuses on the Internet of Things, Quality of Service (QoS) prediction, Web services, and Cloud and Fog computing. His teaching interests include Object-oriented programming, Full Stack application development, Security and Networks, Operating Systems and Systems Programming, and Advanced Networking. His recent publications demonstrate a strong trend in fog and edge computing, with particular emphasis on QoS optimization, cost-effective deployment, and resource management in distributed environments. His work bridges theoretical modeling with practical application deployment strategies across cloud-edge continua. Scientific Awards and Recognition: Fellow of the Higher Education Academy (FHEA), 2021 Postgraduate Certificate in Higher Education (PGCHE), University of Birmingham, 2021 Dr. Ibrahim has supervised and contributed to numerous research projects in distributed systems and cloud computing, particularly through collaborations on European initiatives like SeaClouds. He has secured recognition for his teaching excellence and is actively involved in curriculum development and academic outreach.

• Sustainable Spatial Planning
• Land Use Planning
• Urban and Regional Development
• +۱۲ مورد دیگر

Gernot Stöglehner is a Full Professor at the Institute of Spatial Planning, Environmental Planning and Land Rearrangement , part of the Department of Landscape, Water and Infrastructure at the University of Natural Resources and Life Sciences, Vienna (BOKU) . He holds a doctorate and habilitation in environmental planning, with a career spanning research, teaching, and applied consultancy. His research focuses on sustainable spatial planning, land use efficiency, integrated spatial and energy planning, climate resilience, and environmental assessment . He investigates how urban and regional development patterns impact energy demand, environmental quality, and climate adaptation, advocating for land-saving strategies and resilient settlement structures. His work bridges planning theory with practical policy tools. The recent publications reflect a strong trend in spatial resilience, energy transition, climate change adaptation, and sustainable land use . Articles cover topics such as flood recovery, urban energy modeling for electric vehicles, bioeconomy spatial aspects, and methodological foundations of planning. His research is highly applied, often contributing to policy frameworks and strategic planning instruments. Preis der Prof. Anton-Kurir-Stiftung zur Unterstützung des wissenschaftlichen Nachwuchses (2004) Stöglehner has led or participated in over 60 research projects, many as principal investigator, funded by the Austrian Research Promotion Agency (FFG), the European Commission, and Austrian federal and regional governments. His projects often involve interdisciplinary teams and knowledge transfer to municipalities and planning authorities. He actively advises on spatial and energy strategies for communities and regions. He leads a research group focused on spatial planning and environmental policy, contributing to doctoral programs and major initiatives like the BOKU Energy Cluster. His work is central to the university’s efforts in sustainability and climate action.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Optimization
• +۷ مورد دیگر

Nikhil Bansal holds the prestigious Patrick C. Fischer Professorship of Theoretical Computer Science in the Department of Computer Science & Engineering at the University of Michigan's College of Engineering. His research program has established him as a leading figure in theoretical computer science, with significant contributions to algorithm design and analysis, particularly in discrete optimization problems. Bansal's research focuses on theoretical computer science with emphasis on design and analysis of algorithms for discrete optimization problems. His work spans multiple areas including discrepancy theory, approximation algorithms, randomized algorithms, combinatorial optimization, complexity theory, machine learning theory, and probability. He has made significant contributions to understanding the limits of approximation algorithms and developing novel techniques for combinatorial optimization problems. Analysis of Bansal's recent publications reveals a strong focus on discrepancy theory, online algorithms, and combinatorial optimization. His work often bridges theoretical computer science with discrete mathematics and probability theory. A recurring theme across his publications is the development of novel algorithmic techniques for solving NP-hard problems with provable guarantees. His research has evolved from foundational work in approximation algorithms to more recent contributions in quantum computing complexity and stochastic optimization. Patrick C. Fischer Professor of Theoretical Computer Science Bansal has advised numerous PhD students including Marek Elias, Shashwat Garg, and Greg Koumoutsous, as well as mentoring several postdoctoral researchers. He has served on editorial boards for top journals including Journal of the ACM, Theory of Computing, and Stochastic Models, and has been active on program committees for major conferences such as STOC, FOCS, SODA, and ICALP, including serving as chair for ICALP 2021. Bansal has organized multiple academic workshops including the STOC 2020 Workshop on Recent Advances in Discrepancy and Applications, several SDP Days at CWI Amsterdam, and the Semester on Bridging Continuous and Discrete Optimization at UC Berkeley in Fall 2017.

Nikhil Bansalمشاهده پروفایل

استاد

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Mathematics
• +۳ مورد دیگر

Nikhil Bansal is a Professor in Theoretical Computer Science at the University of Michigan, Ann Arbor. He earned his PhD from Carnegie Mellon University and previously worked at IBM Research, TU Eindhoven, and CWI Amsterdam. His research focuses on algorithm design, discrepancy theory, and combinatorial optimization. Education: PhD, Carnegie Mellon University Bansal's work bridges classical and quantum computing, with recent publications exploring k -Forrelation, vector balancing, and stochastic scheduling. His algorithmic approaches often combine geometric insights and probabilistic methods. Scientific Awards: Patrick C. Fischer Professor of Theoretical Computer Science NSF Career Award (2023) He has advised numerous PhD and postdoctoral researchers, including Marek Elias, Shashwat Garg, and Makrand Sinha. Bansal actively contributes to program committees (ICALP 2021, STOC 2020, FOCS 2018) and organizes workshops on discrepancy theory and optimization.

Effie Apostolouمشاهده پروفایل

دانشیار

• 3D Chromatin Architecture
• Epigenetics
• Cell Fate Reprogramming
• +۵ مورد دیگر

Effie Apostolou serves as Associate Professor of Molecular Biology in Medicine at Weill Cornell Medicine's Department of Medicine, Division of Hematology/Oncology and Cancer Center. She leads the Chromatin Organization & Cell Fate Decisions laboratory within the vibrant Tri-Institutional research community (Weill Cornell, Rockefeller University, Memorial Sloan Kettering). Her research focuses on the critical interplay between transcription factors, 3D chromatin architecture, and transcriptional regulation during cell fate decisions. Key areas include somatic cell reprogramming to induced pluripotent stem cells (iPSCs), epigenetic inheritance of cell identity, and dysregulation in cancer. Her lab utilizes cutting-edge 4D genomics approaches including Hi-C, ChIP-seq, and CRISPR-based technologies to build molecular roadmaps of cellular transitions. Analysis of her publication record reveals consistent focus on chromatin topology mechanisms across developmental and disease contexts. Her work spans fundamental discoveries in mitotic bookmarking (2021), enhancer-promoter networks (2019), and epigenetic barriers to reprogramming (2012-2013), demonstrating interdisciplinary integration of computational and experimental genomics. Scientific recognition includes: NIH Director's New Innovator Award Emerging Leader Award from the Mark Foundation EMBO Postdoctoral Fellowship Jane Coffins Child Foundation Fellowship As a dedicated mentor, she advises multiple PhD students across BCMB, PBSB, and Tri-I CBM programs while maintaining a multicultural lab environment with members from over 10 nationalities. Her research is supported through the 4D Nucleome Consortium and focuses on translating chromatin architecture insights into therapeutic applications for cancer and regenerative medicine.

Masoud Shahmanzariمشاهده پروفایل

مدرس ارشد

• Operations Management
• Mathematical Programming
• Metaheuristics
• +۹ مورد دیگر

Dr. Masoud Shahmanzari is a Senior Lecturer in Operations and Information Systems Management at Brunel Business School, Brunel University London, where he also serves as Programme Lead for the MSc Business Intelligence and Digital Marketing. He holds a Ph.D. in Operations Management and Information Systems from Koç University (2019) and is actively engaged in research, teaching, and academic leadership. Research Interests: Operations Management Mathematical Programming and Optimization Metaheuristics and Matheuristics Business Analytics and Big Data Machine Learning Algorithms Data-Driven Decision Making in Logistics, Healthcare, and Energy Markets His recent publications focus on applying advanced optimization and analytics to real-world challenges such as election logistics, pandemic response modeling, and transportation planning. The articles demonstrate a strong trend toward integrating learning-based heuristics with operational decision-making in dynamic, high-stakes environments. Scientific Recognition: Editorial Board Member, Journal of Business Analytics Peer reviewer for leading journals including Production and Operations Management , European Journal of Operational Research , and Transportation Research Part E Advising and Grants: Dr. Shahmanzari supervises PhD research in data-driven techniques applied to real-world problems. He secured a research grant from the Economic & Social Research Council for a project on computational analytics of cyber-bullying behavior in online communities (Feb 2022 – July 2023). Labs and Teams: His research is aligned with the Innovation and Sustainability research group at Brunel Business School, focusing on sustainable and intelligent business systems.

• Renewable Energy Integration
• Power Systems Optimization
• Energy Storage
• +۷ مورد دیگر

Daniel Fernández-Muñoz is an Associate Professor at the Universidad Politécnica de Madrid (UPM) , affiliated with the Department of Physical Electronics, Electrical Engineering and Applied Physics. He earned his PhD in 2021 with a thesis on "Generation scheduling in isolated power systems with high variable renewable generation and pump-storage," receiving both the Extraordinary Doctoral Award and Carlos González Cruz Award. He has held academic roles since 2006, including Assistant Professor positions from 2016-2021 and a current permanent Associate Professor appointment. Education : PhD in Electrical Engineering (UPM), DEA in Electrical Engineering (2010), Civil Engineering degree (2006) Research Focus : Renewable energy integration, power system optimization, battery degradation modeling, and frequency control in isolated grids Collaborations : Instituto de Sistemas Eléctricos de Potencia (Austria), EERA Joint Programme on Energy Storage, H2020 project eNeuron His work emphasizes hybrid wind-battery systems , pumped-storage hydropower , and virtual power plants , with notable publications in JCR Q1 journals. He has contributed to the Energy2Win project on sustainability education and served as a peer reviewer for multiple scientific journals. Scientific Awards Premio Extraordinario de Doctorado (UPM) Premio Carlos González Cruz Teaching activities include Physics for Biomedical Engineering and Energy Systems for Telecommunications. He has participated in international conferences as an invited speaker and contributed to projects funded by the Spanish government and private entities.

Sina Ansariمشاهده پروفایل

استادیار

• Operations Research
• Healthcare Operations Management
• Service Systems Optimization
• +۴ مورد دیگر

Sina Ansari is an Assistant Professor at DePaul University's Driehaus College of Business , specializing in Management & Entrepreneurship . He co-directs the MS Business Analytics program and has held academic roles at Northwestern University and Tuck School of Business . Northwestern University (PhD, Industrial Engineering & Management Sciences, 2018) Tuck School of Business (Postdoctoral Research Fellow) His research focuses on optimizing service systems through mathematical models, with applications in healthcare operations, opioid crisis mitigation, and logistics. Key areas include: Dynamic resource allocation Patient scheduling optimization Emergency department operations Humanitarian logistics Recent publications highlight his work in humanitarian operations , healthcare scheduling , and medical decision-making . He has received recognition through editorial roles in journals like Naval Research Logistics and Healthcare Management Science . Professional memberships include: INFORMS (Vice President, Chicago Chapter) Production and Operations Management Society Decision Sciences Institute

• History of Economic Thought
• Macroeconomics
• Business Cycles
• +۴ مورد دیگر

Muriel Dal-Pont-Legrand is a University Professor of Economic Sciences at the University of Côte d'Azur, affiliated with the Research Group in Law, Economics, Management (GREDEG) and the EUR ELMI program. She serves as Vice-President for European Affairs at Université Côte d'Azur, coordinating European project participation and institutional visibility in Brussels since 2020. Her research specializes in the history of economic thought with particular focus on business cycles, macroeconomic theory evolution, and economic expertise institutionalization. Key research trajectories include: Analysis of Schumpeter's theories on productive recessions and capitalist dynamics Historical examination of French economic expertise during wartime Interdisciplinary integration of digital humanities with economic thought history Critical assessment of coordination problems across economic theories Her recent publications demonstrate consistent engagement with both classical economic thinkers (Schumpeter, Solow, Leijonhufvud) and contemporary methodological debates, particularly the comparative analysis of DSGE and Agent-Based Modeling approaches in macroeconomics. As co-leader of GREDEG's History of Thought project and co-managing editor of the European Journal of the History of Economic Thought , she maintains significant institutional leadership in her field. Her administrative roles since 2005 include Department of Economics Director and various academic governance positions within the university system.

Christopher Bishopمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Probabilistic Models
• +۶ مورد دیگر

Christopher Bishop is a Microsoft Technical Fellow and Director of Microsoft Research AI for Science, concurrently serving as Honorary Professor of Computer Science at the University of Edinburgh and Fellow of Darwin College, Cambridge. His distinguished career spans theoretical physics, neural computing, and leadership in AI research. Fellow of the Royal Academy of Engineering (2004) Fellow of the Royal Society of Edinburgh (2007) Fellow of the Royal Society (2017) Founding member of UK AI Council Member of Prime Minister's Council for Science and Technology (2019) Delivered Royal Institution Christmas Lectures (2008) His research focuses on probabilistic models and machine learning, with significant contributions to AI for scientific discovery. Bishop pioneered the concept of the fifth paradigm of scientific discovery , where AI transforms traditional research methodologies across natural sciences. His work bridges theoretical computer science with practical applications in fusion energy, materials science, and computational biology. Analysis of his recent publications reveals a strategic shift toward AI-driven scientific infrastructure , with emphasis on machine learning foundations that endure technological evolution. His 2024 textbook became Springer Nature's top-selling publication, demonstrating exceptional impact in both academic and industrial contexts. Deep Learning: Foundations and Concepts (2024) Pattern Recognition and Machine Learning (2006) Neural Networks for Pattern Recognition (1995) Bishop leads Microsoft's global AI for Science initiative, establishing research teams in Berlin and coordinating interdisciplinary projects that apply machine learning to climate science, fusion energy, and molecular biology. His leadership in the Prime Minister's Council shapes national AI strategy while maintaining active engagement in public science communication through lectures and media appearances.

Noah Gansمشاهده پروفایل

استاد

• Service Operations
• Stochastic Processes
• Queueing Systems
• +۳ مورد دیگر

Noah Gans is the Anheuser-Busch Professor of Management Science at the Wharton School of the University of Pennsylvania, where he serves as Professor in the Operations, Information and Decisions department. His research focuses on service operations with particular emphasis on call center management, stochastic processes, and queueing system control. Department Editor, Stochastic Models and Simulation at Management Science President of Manufacturing and Service Operations Management Society (MSOM) PhD Program Coordinator for the OID Department His academic work spans diverse domains including healthcare technology pricing, container inspection security, workforce optimization, and revenue management. He has pioneered adaptive clinical trial designs and developed novel models for customer demand sensitivity in overbooking scenarios. Key research areas include: Bayesian sequential learning for multi-arm clinical trials Value-based pricing under uncertainty Stochastic control in service systems Security policy analysis for global supply chains Risk-sharing mechanisms in healthcare Scientific honors include NSF CAREER Award (1998), INFORMS George E. Nicholson Prize (1995), and multiple teaching awards from the Wharton MBA program (2004, 2010-2011, 1997-2001). His publications bridge theoretical operations research with practical implementation across healthcare, transportation, and service industries.

Rolf Wankaمشاهده پروفایل

استاد

• Algorithms
• Combinatorial Optimization
• Swarm Intelligence
• +۳ مورد دیگر

Prof. Dr. Rolf Wanka is a Professor at the Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), specializing in efficient algorithms and combinatorial optimization. His research focuses on swarm intelligence, discrete optimization algorithms, and scheduling problems, particularly in timetabling and robotics applications. Education : Sc.D. (Dr. rer. nat.) in Computer Science His work includes theoretical and experimental analyses of particle swarm optimization (PSO) algorithms, addressing runtime complexity, stagnation behavior, and convergence properties. He has developed novel heuristics for timetabling and sorting problems, with applications in multi-robot systems and medical imaging. Notable collaborations include studies on Markov chain-based PSO and fairness in academic scheduling. Key trends in his recent publications span swarm intelligence , discrete optimization , and scheduling heuristics , with a focus on robust timetabling , runtime analysis , and stochastic algorithm behavior . While no explicit scientific awards are listed, his mentorship in the Max Weber-Programm highlights his advisory role in academia. His publications demonstrate interdisciplinary applications of algorithms in robotics , medical imaging , and parallel computing , leveraging both theoretical rigor and practical experimentation. The full description below provides exhaustive details on his academic contributions and affiliations.

• Hydraulic Energy
• Hydroelectric Power
• CFD Simulation
• +۶ مورد دیگر

Cécile Münch-Alligné is a Professor in Hydraulic Energy at the University of Applied Sciences and Arts Western Switzerland (HES-SO) in Sion, where she serves as the Head of the Hydroelectricity Research Group and the Renewable Energy Program. She leads the Hydro Alps Lab, which conducts applied research in hydropower combining experimental and numerical approaches. Her work focuses on enhancing the flexibility of both small and large hydropower plants, with particular emphasis on adapting these systems to the evolving energy landscape and integration of renewable energy sources. Her educational background includes a BSc in Energy and Environmental Techniques, an MSc in Engineering, and a BSc in Industrial Systems, all from HES-SO Valais-Wallis. Her research spans multiple domains within hydraulic engineering and renewable energy systems, with particular expertise in CFD simulation, numerical methods, and hydraulic machine design. Münch-Alligné's research interests primarily center around improving hydropower flexibility through innovative approaches such as hydraulic short-circuit operating modes, variable speed operation, and energy recovery systems in water networks. She investigates both large-scale pumped storage power plants and micro-hydropower systems for urban water networks, with a strong focus on practical implementation and commercialization of research findings. Her work bridges theoretical modeling with experimental validation to address real-world challenges in the energy transition. Her research has been published extensively in leading journals, covering topics from Pelton turbine dynamics and Francis turbine vortex analysis to micro-turbine implementations in drinking water networks. The publications reveal a clear trend toward enhancing operational flexibility of hydropower systems to better integrate with intermittent renewable energy sources, with increasing emphasis on practical demonstration projects and commercial applications. As Principal Investigator, she has led multiple significant research projects including the SCCER 4 WP 3.2.0 2017-2020 (Supply of Electricity), Hydrolienne pour canaux artificiels Centrale de Lavey, and SOLUTION DE TRANSFERT D'ENERGIE PAR POMPAGE-TURBINAGE A PETITE ECHELLE. These projects, totaling over 2 million CHF in funding from sources including CTI, OFEN, and industrial partners, demonstrate her ability to secure substantial research funding and collaborate effectively with both academic and industry partners. Münch-Alligné leads the Hydro Alps Lab research team, which includes numerous researchers such as Steiner Amandus, Walpen Olivier, Vaccari Aldo, and others. Her collaborative approach extends to partnerships with institutions like Stahleinbau GmbH and The Ark Energy, facilitating the transfer of knowledge from research to industry application. The lab's work spans from fundamental fluid dynamics research to full-scale demonstration projects, creating a comprehensive pipeline from theory to practical implementation.

• Statistical Analysis
• Stochastic Processes
• Applied Statistics
• +۸ مورد دیگر

Prof. Dr. Kumru Didem Atalay is a distinguished academic at Başkent University, specializing in Industrial Engineering . With a PhD in Statistics from Ankara University (2007), she has made significant contributions to Operations Research , Fuzzy Logic , and Decision Support Systems . Her work bridges statistical analysis with real-world applications in healthcare logistics, pandemic response, and manufacturing optimization. Education: PhD (2007), MS (2000), BS (1998) in Statistics from Ankara University Current Role: Professor in Industrial Engineering at Başkent University Her research focuses on stochastic processes , fuzzy modeling , and healthcare operations , particularly in pandemic-era service quality and microchannel manufacturing. She has developed innovative methods for project scheduling , risk analysis , and multi-criteria decision-making . Recent publications examine Covid-19's impact on education quality and fuzzy linear programming for project scheduling . She applies intuitionistic fuzzy models to optimize manufacturing systems and hesitant fuzzy regression for pandemic death count estimation. Scientific recognition includes a Runner-up Prize at the 15th ICMSEM (2021) and a Bronze Medal at ISIF21 (1970). She supervises advanced research on topics like multi-trip home healthcare routing and fuzzy quality function deployment .

Klemens Fellnerمشاهده پروفایل

استاد

• Partial Differential Equations
• Reaction-Diffusion Systems
• Kinetic Equations
• +۶ مورد دیگر

Klemens Fellner is a Professor of Mathematics/Computational Sciences and Group Leader of the Applied Analysis Group at the Institute of Mathematics and Scientific Computing, University of Graz. His research focuses on the analysis of partial differential equations and mathematical modeling across physics, chemistry, and biology. Research Interests: Prof. Fellner's work spans theoretical analysis of nonlinear PDEs (reaction-diffusion, kinetic, and non-local equations) using entropy/duality methods, with applications to: Biological systems (lipolysis, protein localization, stem-cell division) Physical processes (organic photovoltaics, semiconductor modeling) Collective behavior (swarming micro-organisms, aggregation dynamics) Interdisciplinary Mathematics-Arts collaborations Publication Trends: His recent articles (2018-2021) demonstrate strong focus on: Global existence and regularity for reaction-diffusion systems Convergence to equilibrium via entropy methods Drift-diffusion models in semiconductor physics Mathematical biology applications (prion dynamics, lipolysis) Novel approaches for non-local aggregation and hysteresis phenomena Research Leadership: Currently leads the Applied Analysis Group with members including postdocs and PhD students. Key projects: Doctoral School IGDK (International Graduate School) SFB Lipid Hydrolysis (Special Research Program) Mathematics and Arts collaborations Colibri research platform Supervises PhD candidate Reymart Lagunero studying generalized reaction-diffusion systems.