جست‌وجوی استاد و پژوهشگر

• Functional Analysis
• Artificial Intelligence
• Foundations of Computational Mathematics
• +۱۵ مورد دیگر

Professor Anders C. Hansen is a mathematician at the University of Cambridge and University of Oslo, leading the Applied Functional and Harmonic Analysis group. His work bridges functional analysis, artificial intelligence, and computational mathematics, focusing on the Solvability Complexity Index (SCI) hierarchy and stability issues in deep learning. He has held prestigious fellowships, including a Royal Society University Research Fellowship and Peterhouse Bye-Fellowship. Educated at the University of Cambridge, UC Berkeley, and the Norwegian University of Science and Technology Developed groundbreaking theories in compressed sensing and deep learning, revealing algorithmic instability paradoxes Organized workshops on computational mathematics and AI interpretability His research explores the SCI hierarchy , exposing computational barriers in AI, quantum mechanics, and inverse problems. Key projects include Smale’s 18th problem and analyzing neural network stability. His work has transformed understanding of compressed sensing, particularly in medical imaging. Recent scientific awards include the Whitehead Prize (2019), IMA Prize (2018), and Leverhulme Prize (2017). Collaborations span institutions like Caltech, MIT, and the University of Vienna. As an educator, he teaches NST Part IA Mathematical Methods , Part II Numerical Analysis , and a Part III course on Compressed Sensing . His group has mentored 17 PhD and postdoctoral researchers since 2012.

Joel Gohمشاهده پروفایل

دانشیار

• Health services and systems
• Transportation, logistics and supply chains
• Operations research
• +۶ مورد دیگر

Joel Goh is Associate Professor at the Department of Analytics and Operations, NUS Business School, National University of Singapore. He serves as Director of the J.Y. Pillay Comparative Asia Research Centre (under NUS Global Asia Institute) and PhD Program Director at the Institute of Operations Research and Analytics (IORA). Previously, he was Assistant Professor at Harvard Business School (2014-2017) and Visiting Scholar (2017-2022). BSc, MSc, PhD in Operations, Information, and Technology from Stanford University His research focuses on healthcare analytics (preventing health conditions, hospital operations, frailty assessment), supply chain analytics (digital business models, platform leakage), and service platform operations (hospital-at-home programs, incentive design). He co-created the Robust Optimization Made Easy (ROME) software. Recent publications analyze workplace psychological safety (2024), hospital-at-home models (2024), and platform leakage dynamics (2023). His work spans 18+ journals with 740+ citations for burnout cost studies (2022) and 606+ citations for physician well-being research (2017). Teaching Honors : 2023: Best MBA Teaching & Skinner Innovation Award 2021: NUS Annual Teaching Excellence Award 2020: Early Career Research Excellence Award & 40 Under 40 Best MBA Professors Advising & Grants : Served as PhD Program Director. Received NUS Start-Up Grant R-314-000-110-133 (2021) and Humanities & Social Sciences Fellowship (2021). Editorial roles include Associate Editor at Management Science , Manufacturing & Service Operations Management , and Senior Editor at Production and Operations Management .

Ly Fie Sugiantoمشاهده پروفایل

دانشیار

• Accounting Information Systems
• Data Analytics
• Artificial Intelligence
• +۸ مورد دیگر

Dr. Ly Fie Sugianto is an Associate Professor in the Department of Accounting at Monash Business School, Monash University. Her research focuses on the integration of data analytics, artificial intelligence, and machine learning in accounting and business systems, with applications in the energy sector and organizational behavior. Monash Business School, Monash University Department of Accounting Specialization: Accounting Information Systems, Data Analytics, AI Her research interests span Accounting Information Systems , Agent-Based Simulation , Decision Support Systems , and Technology Adoption . She applies computational methods to study competitive dynamics in deregulated electricity markets and the impact of digital tools on employee well-being and organizational resilience. The recent publications reflect a strong trend in using AI and simulation to analyze complex socio-technical systems, particularly in energy markets and leadership dynamics. Keywords across her work include agent-based modeling , data analytics , servant leadership , and enterprise social media , indicating interdisciplinary research at the intersection of information systems, management, and public policy. Her scientific awards include competitive grants from the ARC (SPIRT/Linkage) , the Australia Indonesia Governance Research Partnership (AIGRP) , and the Sumitomo Foundation . ARC Grant: Dispatch Optimisation in the Australian National Electricity Market Sumitomo Foundation: Technology Use and Employee Well-Being AIGRP: Governance and MSME Resilience during Pandemic Dr. Sugianto has advised research projects and collaborated with industry partners such as Western Power , Ecogen Energy , and AEMO . She is currently accepting PhD students and leads externally funded research initiatives. Her work contributes to UN Sustainable Development Goals related to industry innovation and responsible consumption. She is affiliated with research teams focusing on intelligent decision support systems and digital transformation in business , with active collaborations in Australia and Indonesia.

• Data Science
• Numerical Optimisation
• Medical Imaging
• +۳ مورد دیگر

Raphael Hauser is an Associate Professor in Numerical Mathematics at the University of Oxford's Mathematical Institute, Director of Graduate Studies - Teaching, and Tanaka Fellow in Applied Mathematics at Pembroke College. His affiliations include membership in the Data Science, Numerical Analysis, and Mathematical and Computational Finance research groups, as well as a fellowship at the Alan Turing Institute. Education: PhD in Operations Research, Cornell University, Ithaca, USA Dipl. Math. ETH, Swiss Federal Institute of Technology (ETH Zurich), Switzerland Research interests span data science, numerical optimisation, medical imaging, distributed computing, and applied probability/statistics. His work integrates mathematical rigor with practical applications, particularly in optimization algorithms, machine learning theory, and medical imaging technology. Publications focus on optimization theory, stochastic processes, medical imaging systems, and computational finance, with recurring themes in non-convex optimization guarantees, PCA variants, and X-ray tomography innovations. Awards: Oxford University Teaching Award (2007) SIAM Optimization Prize (2005) SIAM Student Paper Prize (2000) Advising includes 15+ DPhil students and 40+ MSc students, with projects in optimization, finance, imaging, and machine learning. Current postdocs and students are affiliated with the Alan Turing Institute and industrial partners like Siemens and Macquarie Group. He leads teams in the Mathematical Institute's research groups and collaborates with the Alan Turing Institute on large-scale data science initiatives.

Gary Froylandمشاهده پروفایل

استاد

• Dynamical Systems
• Machine Learning
• Optimisation
• +۱۲ مورد دیگر

Scientia Professor Gary Froyland is a Professor at the University of New South Wales (UNSW), affiliated with the School of Mathematics & Statistics. He leads the ARC Laureate Centre for Dynamical Systems and Data and holds an Einstein Visiting Fellowship from the Einstein Foundation Berlin. His academic credentials include a BSc (Hons 1, Medal) in Pure and Applied Mathematics from the University of Queensland and a PhD in Mathematics from the University of Western Australia. Professor Froyland's research spans two primary domains: dynamical systems and optimization. In dynamical systems, he investigates the interplay of probability and geometry in nonlinear and chaotic systems, employing tools from ergodic theory, functional analysis, and differential geometry. His work extends to applications in oceanography, atmospheric science, and granular flows. In optimization, he focuses on decision-making in complex systems with uncertain information, developing novel approaches in mathematical programming that have been applied to mining, logistics, and medical treatment planning. His recent publications demonstrate a strong focus on coherent structures in dynamical systems, linear response theory, and applications to geophysical phenomena. The research shows increasing interdisciplinary collaboration, particularly with climate scientists and data analysts, reflecting a trend toward applying advanced mathematical techniques to real-world problems in environmental science and engineering. J.D. Crawford Prize (2025) Elected Member of the Academy of Europe / Academia Europaea (2024) ARC Laureate Fellow (2024-2029) Fellow of the Society for Industrial and Applied Mathematics (SIAM) (2021) Fellow of the Australian Academy of Science (2020) Vice-Chancellor's Award for Teaching Excellence - Postgraduate Research Supervision (2015) Professor Froyland actively supervises PhD and honors students, with current advisees including Kevin Felipe Kühl Oliveira, Nicholas Peters, and Kathrin Völkner. His research is supported by multiple grants, including an ARC Laureate Fellowship (2024-2029) for "Breakthrough mathematics for dynamical systems and data," an Einstein Visiting Fellowship (2022-2026), and several ARC Discovery Projects. His work has practical applications in climate science, mining optimization, and medical treatment planning, particularly in radiotherapy. He leads the ARC Laureate Centre for Dynamical Systems and Data, which brings together researchers to develop new mathematical approaches for analyzing complex dynamical systems. The center focuses on creating methods to identify coherent structures in spatiotemporal data, with applications spanning environmental science, social science, health science, and engineering.

• Voltage instability prediction
• Electricity markets
• Stochastic optimization
• +۵ مورد دیگر

Professor Gregor Verbic is a faculty member at the University of Sydney in the School of Electrical and Computer Engineering , where he serves as Director of the Centre for Future Energy Networks . Previously, he held an assistant professor position at the University of Ljubljana and was a NATO-NSERC Postdoctoral Fellow at the University of Waterloo. His career spans academic research, industry leadership as Head of Interenergo's Investment Department, and extensive collaboration with IEEE. PhD in Electrical Engineering (University of Ljubljana) Senior IEEE Member Research Interests focus on transforming power systems to zero-carbon grids through: Aggregation and control of distributed energy resources (DERs) Frequency control with wind generation and electric vehicles Stochastic optimization for multi-energy systems Smart home energy management with phase change materials Notable Contributions include: 2006 IEEE prize paper for voltage instability prediction 2010-2024: 15 recent publications on DER coordination, network tariffs, and low-inertia grid stability Teaching includes courses on: ELEC3203/ELEC9203: Electricity Networks ELEC5213: Engineering Optimisation ELEC5206: Sustainable Energy Systems Labs & Initiatives Centre for Future Energy Networks The Net Zero Institute

David Alldredمشاهده پروفایل

استاد

• Medicines Optimisation
• Patient Safety
• Deprescribing
• +۵ مورد دیگر

Professor David Alldred is a Professor of Medicines Use and Safety at the University of Leeds' School of Healthcare, within the Faculty of Medicine and Health. His expertise spans medicines optimisation, patient safety, deprescribing, and care home medication management. He leads key research initiatives such as the NIHR Yorkshire and Humber Patient Safety Research Collaboration's 'Decluttering Safely for Safety' theme and co-leads the School of Healthcare's Quality and Safety research theme. Education: PhD (clinical research on care home medication review), MSc in Clinical Pharmacy, PGCert in Learning and Teaching, and BPharm (Hons). Professional memberships include Fellowships of the Royal Pharmaceutical Society and the Higher Education Academy. Research focuses on improving medication use for older adults in care homes and underserved populations, employing systematic reviews, qualitative studies, and RCTs. Notable projects include the CHUMS study (Department of Health-funded medication error analysis in care homes) and leadership roles in NIHR Programme Grants like CHIPPS and CHARMER. He collaborates with NHS England to implement medicines optimisation programs and co-designed multilingual medication review resources to reduce health inequalities. Awards include the Pharmacy Practice UK Research Award (2015) and NIHR Senior Investigator status (2025). His work emphasizes translating evidence into clinical practice, with over 150 publications and supervising NIHR-funded doctoral students in critical care, diabetes, cystic fibrosis, and geriatrics. Led the Care Homes' Use of Medicines Study (CHUMS), contributed to NICE guidelines for care home medicines management, and developed interventions like the Medicines at Transitions Intervention (MaTI) for heart failure patients. His research themes address polypharmacy reduction, medication safety across care transitions, and pharmacist-led deprescribing strategies.

• Hydrogeology
• Groundwater flow and transport modelling
• Contaminant hydrogeology
• +۵ مورد دیگر

Thomas Rüde is Universitätsprofessor for Hydrogeology at RWTH Aachen University , Germany, where he leads the Hydrogeology group within the Faculty of Georesources and Materials Engineering. Holding the chair since 2005, he also serves as Managing Director of the Vereinigung Aachener Geowissenschaftler e.V. and has previously been Vice-President (2008-2014) and Executive Council member (2000-2008) of the International Mine Water Association (IMWA). Education 2004 – Privatdozent (Dr. rer. nat. habil.), University of Munich 1995 – Dr. rer. nat., University of Karlsruhe 1991 – Diplom-Geologe, University of Karlsruhe Research focus Professor Rüde’s work centres on understanding and modelling flow and reactive transport in complex aquifer systems . Key themes include: Contaminant hydrogeology – behaviour of geogenic arsenic and uranium in groundwater Groundwater protection and remediation – risk assessment and mitigation strategies Mine-water management – acid mine drainage, dewatering-well clogging, post-mining landscapes Tracer and hydraulic testing – field experiments to quantify subsurface heterogeneity Numerical modelling – high-performance simulation of multi-aquifer systems and karst His research spans Europe (Germany, Austria, Netherlands), Latin America (Mexico, Indonesia) and South-East Asia, frequently in close collaboration with local universities and industry partners. Publication trends Since 2010, Rüde has published extensively on geogenic contamination (As, U, F) in sedimentary and volcanic aquifers, mine-water impacts , and karst hydraulics . Recent work (2022-24) highlights advanced environmental tracers (gadolinium), transboundary groundwater issues, and the sustainable management of post-mining landscapes under climate change. Numerical models range from site-scale dewatering optimisation to catchment-scale coupled flow-transport simulations. Scientific awards & recognition Best Teaching Award 2010 – RWTH Aachen University Best Teaching Award 2012 – RWTH Aachen University Best Teaching Award 2014 – RWTH Aachen University Supervision & academic service Since 1998 he has taught hydrogeology through lectures, seminars, laboratory and field courses, and computer-based modelling labs. To date he has supervised: 13 PhD candidates 34 Diploma students 57 MSc students 63 BSc students He is Chairman of the Study Commission for the BSc programme in Georesources Management at RWTH Aachen, ensuring curriculum development and quality assurance. Laboratory & field infrastructure His group operates modern hydrochemical laboratories for trace-element analyses and maintains field stations for tracer experiments in Germany, Mexico and Indonesia. High-performance computing resources (in collaboration with the Jülich Supercomputing Centre) enable large-scale groundwater modelling and Monte-Carlo uncertainty assessments.

Elina Rönnbergمشاهده پروفایل

استاد

• Discrete Optimisation
• Mathematical Optimisation
• Scheduling
• +۱۸ مورد دیگر

Elina Rönnberg is a Professor and Deputy Head of Department at the Department of Mathematics, Linköping University, where she leads research in discrete optimisation and intelligent decision-making. Her work bridges theoretical method development and real-world applications in sectors such as healthcare, aviation, mining, and transportation. She is actively involved in the Wallenberg AI, Autonomous Systems and Software Program (WASP) and has collaborated with industry leaders like Saab and Scania. Her research focuses on advanced optimisation techniques including Dantzig-Wolfe decomposition, Lagrangian relaxation, column generation, branch-and-price, and logic-based Benders decomposition. She also explores hybrid methods combining mathematical programming with constraint programming and machine learning. Applications span nurse rostering, electric vehicle routing, aircraft arrival scheduling, and underground mine planning. Recent publications highlight a strong trend toward integrating AI and machine learning—particularly graph neural networks—with classical optimisation frameworks to accelerate solution methods. Her work emphasizes practical impact, robustness, and scalability in solving complex scheduling and resource allocation problems. Nurse Rostering with Strategic Planning of Skills for Sick-Leave Robustness (2024) Pricing for the EVRPTW with Piecewise Linear Charging (2024) Speeding Up Logic-Based Benders Decomposition with Graph Neural Networks (2024) Elina supervises several PhD students and has co-supervised doctoral research at international institutions including Makarere University (Uganda) and the University of Exeter (UK). She has contributed to applied projects through student theses in collaboration with Scania and Saab, focusing on electric vehicle routing and search-and-rescue optimisation. She previously served as a Specialist in Optimisation at Saab Aeronautics (2014–2020) and co-founded Schemagi, a scheduling tool aimed at improving quality in healthcare. She teaches courses such as Introduction to Optimization (TAOP07) and Project - Applied Mathematics (TATA62). Her research group, 'Mathematics and algorithms for intelligent decision-making,' operates within the Division of Applied Mathematics (TIMA) at the Department of Mathematics. The team develops decision support tools that enhance efficiency and sustainability in complex systems, particularly under the growing demands of electrification and digitalisation in transport and logistics.

• Computational Mathematics
• Geophysical Fluid Dynamics
• Numerical Software
• +۳ مورد دیگر

Prof. David Ham is a Professor of Computational Mathematics at the Department of Mathematics, Faculty of Natural Sciences, Imperial College London. His research focuses on high-level abstractions for scientific computation, particularly in geophysical fluids and numerical software. He leads the Firedrake project and co-developed the dolfin-adjoint framework, which received the 2015 Wilkinson Prize for Numerical Software. Ham holds a BSc (Mathematics) and LLB from The Australian National University, and a PhD from TU Delft. His career includes roles as a NERC Independent Research Fellow and Grantham Research Fellow at Imperial College. He is affiliated with the Grantham Institute, Mathematics of Planet Earth, and Software Performance Optimisation groups. His research spans computational science, including finite element methods, adjoint-based inversion, and parallel computing. Recent work emphasizes differentiable programming integration with machine learning and geophysical modeling. Ham has contributed to numerous grants and projects, including EPSRC and NERC-funded initiatives. He leads development of software tools like Firedrake and Thetis, advancing computational methods for oceanography and geodynamics.

• Multi-criteria decision analysis
• Operations research
• Fuzzy sets and fuzzy numbers
• +۷ مورد دیگر

Matteo Brunelli is Associate Professor of “Mathematical Methods of Economics and Actuarial and Financial Sciences” at the University of Trento , Department of Industrial Engineering, and Adjunct Professor (docent) at Lappeenranta University of Technology , Finland. He is nationally habilitated as Full Professor in Italy and has held long-term visiting positions at Berkeley, Turku, Auckland, JAIST and Binghamton. Education: Ph.D. (Doctor of Science) in Information Technologies, Åbo Akademi University, Finland, 2011 – graded Eximia cum laude approbatur M.Sc. in Economics, University of Trento, 2007 – grade 110/110 cum laude B.Sc. in Economics, University of Trento, 2005 Research focus: Brunelli’s work sits at the intersection of multi-criteria decision analysis , operations research and computational optimisation . He develops axiomatic foundations and algorithms for pairwise comparison matrices , consistency indices , the best-worst method and fuzzy preference relations , and applies them to energy planning, sustainable inventory, maintenance scheduling, 3-D printer selection, and blockchain governance. His 2023-2025 articles reveal intensified interest in uncertainty modelling (Dempster-Shafer theory), bi-objective optimisation of inventory and maintenance, and group decision protocols that integrate probabilistic or active-learning components, demonstrating both methodological depth and practical relevance. Scientific awards & grants: Academy of Finland Postdoctoral Researcher grant (€254 670, 2014-2017) Claudio Dematté Research Grant (€19 000, 2008) Teacher of the Year Award, Aalto University (2013 – both Spring & Autumn semesters) Bernard Roy Award 2021 for outstanding contribution to Multiple Criteria Decision Aiding (under-40 category) Supervision & funding: While specific doctoral students are not listed, Brunelli currently supervises graduate theses at Trento and has continuously held competitive national grants. His Academy of Finland project “Consistency of valued preference relations for decision analytics methods” financed three years of full-time research and international collaboration. Editorial & community roles: He serves on the editorial boards of International Journal of General Systems and Mathematical and Computational Applications , and acts as area editor for Journal of Multi-Criteria Decision Analysis , positioning him among the key gatekeepers of the MCDA community.

Pierre Flenerمشاهده پروفایل

استاد

• Artificial Intelligence
• Constraint Programming
• Discrete Optimization
• +۵ مورد دیگر

Pierre Flener is a Professor at the Department of Information Technology, Division of Computing Science at Uppsala University. He leads the Optimisation Group and is a member of the Centre for Interdisciplinary Mathematics. His work focuses on constraint programming and discrete optimization, addressing complex scheduling, routing, and resource allocation challenges. Flener is an Officer of the Order of Merit of Luxembourg and co-founder of NordConsNet, the Nordic Network for Constraint Programming researchers. Research Interests: Flener’s research spans constraint programming, combinatorial optimization, and algorithm design. He develops models and tools for automated decision-making in domains like air traffic management, sensor networks, and industrial robotics. His work emphasizes practical applications, leveraging constraint satisfaction techniques to solve real-world puzzles such as vehicle routing and personnel allocation. Key Contributions: Flener has authored over 100 publications on constraint solving, symmetry breaking, and CP-based approaches to industrial problems. Notable projects include airspace sectorization optimization, energy-efficient sensor networks, and financial portfolio design. He has led initiatives like Auto-Tabling for MiniZinc and collaborated on CP applications in bioinformatics and image processing. Labs & Teams: He heads the Optimisation Group at Uppsala, fostering research in CP and its applications. NordConsNet, co-founded by Flener, connects Nordic researchers and practitioners in constraint technology.

Estela Suarezمشاهده پروفایل

استاد

• high performance computing (HPC)
• heterogeneous HPC system architectures
• modular supercomputing architecture (MSA)
• +۴ مورد دیگر

Prof. Dr. Estela Suarez is a Professor of High Performance Computing at the Institute for Computer Science, University of Bonn (W2 in the Jülich Model) and Joint Lead of the Division "Novel System Architecture Design" at the Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH. She also leads the Research Group "Next Generation Architectures and Prototypes" at JSC and serves as Spokesperson of Helmholtz Information Program 1, Topic 2. Currently on sabbatical during the 2024/2025 and 2025 academic years, she remains active in research leadership roles. 2010: PhD in Physics from University of Geneva, Switzerland 2004: Master in Physics, Specialization in Astrophysics, University Complutense of Madrid, Spain Professor Suarez specializes in high performance computing with particular expertise in heterogeneous HPC system architectures and modular supercomputing architecture (MSA). Her research spans hardware prototyping and evaluation, system software development, operational data analysis, and co-design methodologies. She has pioneered approaches to address hardware heterogeneity through system-wide orchestration of diverse computing resources, enabling more efficient scientific computing across multiple domains. Her work bridges theoretical computer architecture with practical implementation challenges in exascale computing environments, focusing on real-world applications that require specialized hardware configurations. Professor Suarez's publication record shows a clear evolution from foundational work on the DEEP project (2016) through the development of modular supercomputing concepts (2019-2021) to current applications across diverse scientific domains (2022-2024). Her recent publications demonstrate how modular architectures can be effectively applied to climate modeling, neuroscience simulations, quantum chemistry calculations, and other computationally intensive fields. This trend highlights her focus on practical implementation challenges and the growing importance of adaptable computing architectures in modern scientific research. 2023/2024 Lehrpreis der Universität Bonn: UniBonn teaching award Professor Suarez has secured significant research funding through major projects including NUMERIQS (Projects A05, B02, and Z02), European Processor Initiative (EPI), DEEP-SEA (Software for Exascale Architectures), IFCES2 (optimization of simulation algorithms for exascale supercomputers), and AIDAS (virtual laboratory between Forschungszentrum Jülich and CEA on AI and data analytics). While currently not accepting new students due to sabbatical, she has previously mentored graduate students in high performance computing techniques and has delivered numerous invited lectures at international conferences. Professor Suarez leads the "Next Generation Architectures and Prototypes" research group at JSC and serves as Joint Lead of the "Novel System Architecture Design" division. She chairs the Research and Innovation Advisory Group (RIAG) from EuroHPC Joint Undertaking since 2024. Her work involves close collaboration with international research teams on advancing supercomputing architectures, including contributions to the University of Bonn's new HPC system "Marvin" which ranks on both the TOP500 and GREEN500 lists.

Shu-Jung Sunny Yangمشاهده پروفایل

استاد

• Supply Chain Resilience
• Sustainable Operations
• Data-Driven Operations
• +۳ مورد دیگر

Shu-Jung Sunny Yang is a Professor and Chair in Operations Management at the School for Business and Society, University of York. He has held faculty positions at institutions including the University of Melbourne, University of Essex, and National Taiwan University, alongside administrative roles such as department head and research centre director. He earned his PhD in Management from the Australian Graduate School of Management (AGSM) at the University of Sydney and University of New South Wales. His research focuses on Supply Chain Resilience, Sustainable Operations, and Data-Driven Operations, combining formal theory, data science, and operational research. Recent work includes modeling supply chain collaboration for medical mask distribution during disruptions and exploring altruistic venturing through community-based approaches. His book Building Resilience: Consistent Re-rationalisation in Digital Transformation and Business Inheritance won the 2022 Golden Book Award in Taiwan. Awards: 2022 Golden Book Award (Taiwan) 2004 Sasakawa Young Leader Fellow (Japan) 2019 Ta-Yu Wu Memorial Award (Taiwan) Yang leads the Human futures in the digital transformation interdisciplinary cluster. His teaching includes Operations Management and Supply Chain Management. He currently serves as a guest editor for Transportation Research Part E and holds editorial roles at Journal of General Management and Journal of Management and Systems . Research grants include the British Academy-funded project on Optimising Product Line Design in Professional Service Operations . He actively collaborates with industry and academia, emphasizing practical applications of operations strategy.

Francisco Benitaمشاهده پروفایل

مدرس

• Data Science & Analytics
• Optimisation & Decision Science
• Economics & Public Policy
• +۱ مورد دیگر

Francisco Benita is an Adjunct Lecturer at the Engineering Systems and Design (ESD) Pillar of Singapore University of Technology and Design (SUTD). He holds a PhD in Engineering Sciences from Monterrey Tech (2016) and an MSc in Industrial Economics from Universidad Autónoma de Nuevo León (2012). Prior to SUTD, he was a postdoctoral fellow at SUTD’s Architecture and Sustainable Design Pillar and a Senior Advisor at the ITESM-BMGI Lean Six Sigma Program. His research focuses on urban systems, optimization, data science, and their intersections with economics and public policy. Key areas include transportation networks, spatial livability indices, and pandemic impacts on urban environments. Benita’s interdisciplinary work spans fields like sustainable urban design, carbon emissions modeling, and global trade dynamics. Recent publications highlight trends in transportation innovation (e.g., ride-sharing impacts, aircraft routing frameworks), climate-resilient urban planning (e.g., walkway thermal comfort), and pandemic analysis. His projects often integrate quantitative methods with real-world data, emphasizing actionable insights for policymakers and urban planners. Though no scientific awards are explicitly mentioned, his extensive international collaborations—including research visits to TU Berlin, Vrije Universiteit Brussel, and Supélec—reflect his global academic engagement. Students and grants are not listed in the provided texts. Benita’s work is anchored in labs/teams within SUTD’s ESD Pillar, though specific lab affiliations are not detailed. His research bridges theoretical optimization with practical urban challenges, contributing to both academic discourse and applied solutions in smart cities.