Find Academic Supervisors

Jonathan WeareView profile

Professor

• Monte Carlo sampling
• Multiscale analysis
• Randomized numerical linear algebra
• +2 more

Jonathan Weare is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He holds affiliations with the Faculty of Arts and Science and the Graduate School of Arts and Science. His academic journey includes roles as an Associate Professor at the University of Chicago (2014–2019) and Assistant Professor (2011–2014), following postdoctoral work as a Courant Instructor at NYU. He earned his Ph.D. in Mathematics from UC Berkeley in 2007. His research focuses on stochastic algorithms and models, with applications in astrophysics, biophysics, computational chemistry, and climate science. Key areas include Monte Carlo methods, rare event simulation, and machine learning-driven scientific analysis. Collaborations with domain experts ensure his work addresses real-world challenges in diverse fields. Recent publications emphasize advancements in trajectory stratification, rare event prediction using machine learning, and efficient algorithms for high-dimensional problems. Notable contributions include the BAD-NEUS framework and AI-based solar system instability predictions. His group’s interdisciplinary approach bridges computational methods with scientific inquiry. Weare has advised numerous students and mentored postdocs, fostering talent in applied mathematics and computational science. His work on Mercury’s orbital dynamics and extreme weather prediction showcases the societal impact of his research. Current projects explore AI applications in weather modeling and rare event analysis, leveraging cutting-edge machine learning techniques. Labs/Teams: His research group at Courant develops stochastic algorithms and collaborates with interdisciplinary teams in computational chemistry, climate science, and astrophysics. Key collaborations include the University of Chicago and Columbia University.

Qiu, JingjingView profile

Associate Professor

• Advanced Manufacturing
• Nanomaterials Synthesis
• Multifunctional Composites
• +3 more

Dr. Jingjing Qiu is an Associate Professor in the Department of Mechanical Engineering at Texas A&M University (TAMU), leading the Advanced Materials & Manufacturing (AM²) Lab. Her research focuses on advanced manufacturing, nanomaterials, multifunctional composites, sustainable materials, energy harvesting, and healthcare applications. She holds a Ph.D. in Industrial & Manufacturing Engineering from Florida State University (2008), and M.S./B.S. degrees in Materials Science from Beihang University (2004/2001). Prior to academia, she gained 1 year of industrial experience as a Quality Engineer at SAIC Motor. Research interests include AI-driven nanomaterials synthesis, low-carbon manufacturing processes, and biomedical innovations such as drug delivery systems for brain tumors. The AM² Lab emphasizes interdisciplinary collaboration in materials science, data science, and sensor integration for energy and medical devices. Recent work highlights include AI-assisted microplastics removal, thermoelectric energy harvesting via graphene aerogels, and neuromorphic computing systems. Her team actively pursues postdoctoral and PhD candidates for research in energy/healthcare materials, requiring expertise in nanomaterials characterization (e.g., SEM, XPS, electrochemical techniques) and interdisciplinary problem-solving. Lab facilities support cutting-edge fabrication and testing of functional materials. Publications span over 15 years, with recent trends in sustainable manufacturing, soft robotics, and bio-inspired materials. Ongoing projects include DOE-funded initiatives on rare earth recycling and low-carbon ceramic production. No scientific awards are explicitly listed in the provided texts.

Joshua LoftusView profile

Professor

• Algorithmic Fairness
• Causal Inference
• Data Science
• +4 more

Joshua Loftus is a Professor of Statistics and Data Science at the London School of Economics (LSE), Department of Statistics. His research focuses on improving data science practices to reduce bias and enhance fairness in algorithms, particularly addressing social harms and scientific reproducibility. He develops methods for statistical inference post-model selection and uses causality to analyze algorithm fairness and interpretability. His work bridges high-dimensional statistics, causal inference, and ethical AI, with a strong emphasis on practical applications using R in data science education. Before joining LSE, Loftus earned his PhD in Statistics at Stanford University, served as a Research Fellow at the Alan Turing Institute (affiliated with the University of Cambridge), and was an Assistant Professor at New York University (2017–2020). His research interests extend to the societal implications of technology, advocating for systems that prioritize human values over technical efficiency. Key research themes include counterfactual fairness, causal reasoning in algorithmic systems, and disaggregated interventions to reduce inequality. His recent work explores temporal aspects of fairness, model-agnostic auditing, and the integration of ethical frameworks into machine learning pipelines. While no scientific awards are explicitly listed, his contributions to foundational AI ethics and statistical methodology are widely recognized in academic circles. Advising and grant details are not provided in the source text, but his leadership in interdisciplinary research collaborations, such as the Turing Institute affiliation, highlights active engagement in research networks. Loftus is part of the LSE’s vibrant data science community, contributing to both theoretical advancements and applied solutions for equitable technology deployment.

• Quantum Theory of Condensed Matter
• Topological Insulators
• Spin Phenomena
• +7 more

Prof. Jelena Klinovaja is a Professor in the Department of Physics at the University of Basel, affiliated with the Philosophisch-Naturwissenschaftliche Fakultät. She holds leadership roles in research groups focusing on quantum theory of condensed matter, topological systems, and spin phenomena. Her career includes a PhD from the University of Basel (2012), a Harvard Fellowship (2013), and tenure as an assistant (2014) and associate professor (2019) before her current rank. She leads research on topological insulators, graphene, and Majorana fermions, with applications to topological quantum computing. Notable awards include the Swiss Physical Society Prize (2013) and an ERC Starting Grant (2017). Her work combines theoretical physics with experimental collaborations, particularly in nanowires and superconducting systems. She mentors students in the Honors Track program and contributes to interdisciplinary initiatives like NCCR SPIN. Education: Bachelor/Master from Moscow Institute of Physics and Technology (2007-2009); PhD in Theoretical Physics from University of Basel (2012). Research Interests: Topological effects in condensed matter, spintronics, quantum transport, Majorana fermions, and cavity quantum electrodynamics. Publications span over 50 peer-reviewed articles since 2012, focusing on topics like Josephson junctions, topological superconductivity, and hybrid systems. Her work bridges theoretical models with experimental realizations, emphasizing practical applications in quantum technologies. Awards: Swiss Physical Society Prize (2013), ERC Starting Grant (2017). Active in the scientific community, she collaborates with institutions worldwide and advises PhD students in quantum physics and nanoscience. Her research group also explores magnonic systems and topological materials engineering.

Kyle HanquistView profile

Assistant Professor

• Hypersonics
• Aerothermodynamics
• Nonequilibrium Flows
• +11 more

Kyle Hanquist is an Assistant Professor in the Department of Aerospace and Mechanical Engineering at the University of Arizona, where he is also a member of the Graduate Faculty. He directs the Computational Hypersonics and Nonequilibrium Laboratory (CHANL), focusing on advanced simulation techniques for high-speed flows. His academic journey includes a PhD and MSE in Aerospace Engineering from the University of Michigan and a BSE in Mechanical Engineering from the University of Nebraska. PhD, Aerospace Engineering, University of Michigan, Ann Arbor MSE, Aerospace Engineering, University of Michigan, Ann Arbor BSE, Mechanical Engineering, University of Nebraska, Lincoln Dr. Hanquist's research centers on hypersonics, aerothermodynamics, and nonequilibrium flows , with strong emphasis on computational fluid dynamics , low-temperature plasmas , and thermal management systems . His work involves modeling complex physical phenomena such as electron transpiration cooling, plasma-assisted flow control, and high-temperature gas effects in reentry environments. He also investigates molecular gas dynamics and finite-rate chemistry in extreme conditions. His recent publications reveal a strong trend in computational modeling of hypersonic boundary layers , plasma sheaths , and shock-tube validation of thermochemical models . The interdisciplinary nature of his work spans aerospace engineering, plasma physics, and materials response under extreme thermal loads. Much of his research integrates multi-physics simulations to address fluid-thermal-structural interactions critical for next-generation hypersonic vehicles. Dr. Hanquist has received several scientific honors, including: 2020 AIAA Plasmadynamics and Lasers Best Paper Award Editor's Choice, AIP Publishing - Physics of Fluids (Summer I 2020) Featured Article, AIP Publishing - Physics of Fluids (Summer I 2021) Frontiers in Physics – Plasma Physics (Spring 2020) As an advisor and lab director, he mentors graduate students in computational hypersonics and collaborates with institutions like NASA and the University of Michigan. His research is supported by grants from aerospace and defense agencies, though specific funding sources are not listed. He teaches courses in fluid mechanics, numerical methods, and nonequilibrium flows, contributing to both undergraduate and graduate education. He leads the Computational Hypersonics and Nonequilibrium Laboratory (CHANL) , which develops and applies high-fidelity simulation tools for hypersonic applications. The lab focuses on kinetic modeling, plasma interactions, and optimization of thermal protection systems, often using massively parallel CFD codes and multi-fidelity surrogate models.

Ari JantunenView profile

Professor

• Strategy and Management
• Strategic Change and Renewal
• Organizational Cognition
• +8 more

Ari Jantunen is a Professor in Strategy Research at the LUT Business School, LUT University, Lappeenranta, Finland. He is affiliated with the Department of Business Studies and has been actively contributing to academic research in strategic management and organizational behavior. University: LUT University School: LUT Business School Department: Business Studies Position: Professor, Strategy Research Email: Ari.Jantunen@lut.fi He earned his D.Sc. (Econ.) from Lappeenranta University of Technology in 2005, establishing a long-standing academic career focused on strategic change and innovation. Ari Jantunen’s research centers on strategic change and renewal, organizational cognition, dynamic capabilities, dominant logic, and industry dynamics . His work explores how managerial cognition influences strategic decisions and organizational performance, particularly in industries undergoing transformation such as media, energy, and forest sectors. He also investigates sustainability strategies, the circular bioeconomy, and corporate social performance. His recent publications reflect a strong trend in using cognitive mapping, qualitative comparative analysis (fsQCA), and simulation modeling to understand strategic phenomena. Articles on dominant logic, strategic renewal, and cognitive diversity highlight his focus on the cognitive underpinnings of strategic management. Among his notable works are studies on the bioeconomy transition in the pulp and paper industry, innovation races in high-tech sectors, and the interplay between corporate social and financial performance. Jantunen has collaborated extensively with researchers such as Anni Tuppura, Satu Pätäri, Kalevi Kyläheiko, and Anssi Tarkiainen, often co-authoring studies in journals like European Management Journal , Journal of Business Research , and Futures . Ari Jantunen is actively engaged in research and supervision, though no specific students are listed in the provided sources. He does not appear to have received any explicitly mentioned scientific awards, but his consistent publication record in high-impact journals underscores his academic contributions. He has been involved in interdisciplinary research projects, particularly those examining the interface between the energy and forest sectors, the diffusion of energy services, and innovation in cleantech firms. His work often combines theoretical rigor with practical insights, contributing to both academic discourse and industry applications.

Christian PlesslView profile

Professor

• High-Performance Computing
• Reconfigurable Computing
• FPGA Acceleration
• +3 more

Prof. Dr. Christian Plessl is a W3 Professor of High-Performance Computing at the Institute of Computer Science, University of Paderborn. He leads the Paderborn Center for Parallel Computing (PC²), a national HPC center within the NHR alliance. His roles include Director of PC², Board Member of the NHR association, and member of the Sonderforschungsbereich 901. Education: PhD (Dr. sc. ETH) in Computer Engineering, ETH Zürich (2006) MSc in Electrical Engineering, ETH Zürich (2001) Postdoc at ETH Zürich (2007–2011) Research Interests: Architecture and tools for high-performance parallel and reconfigurable computing, FPGA acceleration, quantum chemistry, scientific computing, adaptive systems, and energy-efficient HPC solutions. Key projects include EKI-App (FPGA-based neural networks), FPGA4XPCS (X-ray spectroscopy), and HighPerMeshes (unstructured grid frameworks). Publications: Over 100 peer-reviewed works, focusing on FPGA acceleration, HPC frameworks, and quantum computing. Recent trends emphasize energy-efficient neural networks, FPGA-based quantum computing, and scalable HPC algorithms. Awards: Best Paper Awards at HEART 2023, ReConFig 2012/2014 Paderborn University Research Awards (2018, 2009) SEW-EURODRIVE Student Award (2001) Grants & Projects: Principal investigator in DFG, BMBF, and EU-funded projects. Collaborates with AMD/Xilinx, Intel/Altera, and Fujitsu. Leads initiatives like PerficienCC (custom computing) and HighPerMeshes. Labs/Teams: Directs the High-Performance Computing group at PC², focusing on FPGA supercomputing and HPC infrastructure. Active in the NHR alliance for national HPC coordination.

I. Safak BayramView profile

Senior Lecturer

• Electric Vehicle Grid Integration
• Smart Grids
• Demand-side Management
• +7 more

I. Safak Bayram is a Senior Lecturer (Associate Professor) in the Department of Electronic and Electrical Engineering at the University of Strathclyde, Glasgow, UK. He joined Strathclyde in 2020 as a Chancellor's Fellow, following his role as an Assistant Professor and Scientist at Hamad Bin Khalifa University, Qatar. His research focuses on advancing sustainability and efficiency in intelligent power grids and transportation networks through system-level modeling, control, and management frameworks. Education: PhD in Electrical and Computer Engineering, North Carolina State University (2014) MSc in Telecommunications, University of Pittsburgh (2010) BSc in Electrical and Electronics Engineering, Dokuz Eylul University, Turkey (2007) His research interests center on the integration of electric vehicles (EVs), renewable energy, and energy storage systems into the grid to decarbonize transportation and electricity sectors. He specializes in smart charging, demand-side management, harmonics, power quality, and V2G technologies. His recent publications (2024–2025) emphasize experimental and modeling approaches to EV smart charging impacts on transformers, phase imbalance, and grid compatibility, reflecting a strong focus on real-world deployment and grid resilience. Scientific Awards: Best Paper Award, IEEE SmartGridComm (2024) Best Paper Award, IEEE Workshop on Renewable Energy and Smart Grid (2015) Best Paper Award, IEEE SmartGridComm (2018) Best Readings in Smart Grid Communications (2014) Adjunct Faculty Member Appointment (2020) Dr. Bayram is actively involved in research leadership and academic service. He has secured multiple research grants as Principal Investigator, including projects on V2G hubs and off-grid EV charging. He serves as an Associate Editor for IEEE Transactions on Transportation Electrification and IET Electrical Systems in Transportation, and has organized special issues and conferences such as IEEE SmartGridComm. He regularly delivers tutorials and participates in international conferences, contributing to the global smart grid and electrification community. Labs and Research Teams: His work is supported by active collaborations with industry (e.g., Arnold Clark Automobiles Limited) and research institutions. He leads research on modular EV charging (BumblebeeEV), smart charging algorithms, and grid integration projects, often involving experimental validation and field data analysis.

• Sanitary Engineering
• Wastewater Treatment
• Constructed Wetlands
• +7 more

Priv.Doz.DI Dr.nat.techn. Günter Langergraber is a Professor and Head of the Institute of Sanitary Engineering and Water Pollution Control at the University of Natural Resources and Life Sciences, Vienna (BOKU). He also serves as Deputy Head of the Department of Landscape, Water and Infrastructure since 2025. With expertise in nature-based solutions , constructed wetlands , and resource-oriented sanitation systems , his work integrates modelling and simulation with practical applications for wastewater treatment and urban sustainability. Habilitation in Sanitary Engineering (2012), BOKU PhD in Natural Sciences (2001), BOKU His research focuses on developing advanced wastewater treatment technologies using constructed wetlands , biochar systems , and smart sensors . Key areas include urban water circularity , stormwater management , and climate resilience through nature-based infrastructure . He leads major EU-funded projects like ProCleanLakes and UniNEtZ , emphasizing the role of sustainable sanitation in achieving SDG 6 . Recent publications analyze: Design optimization of vertical flow wetlands using numerical models Implementation frameworks for circular cities via nature-based solutions Hydrological dynamics in Mediterranean and tropical wetland systems Soil water balance quantification via stable isotopes Scientific accolades include IWA Fellow (2014) and the IWA Project Innovation Award (2011) . He has supervised 478 publications and 56 projects, including EU Horizon 2020 initiatives and Austrian Science Fund (FWF) programs. As a keynote speaker at international conferences, he advocates for renaturalized urban water systems and decentralized sanitation . Langergraber contributes to technical guidelines (e.g., DWA-A 272) and policy reports for Austrian ministries. His work bridges academic research , industry collaboration , and public engagement through media appearances and training programs for wastewater plant operators.

Ralf ZimmerView profile

Professor

• Bioinformatics
• Systems Biology
• Machine Learning
• +5 more

Ralf Zimmer is a Full Professor for Practical Informatics and Bioinformatics at Ludwig Maximilian University of Munich (LMU) since 2001, affiliated with the Department of Informatics in the Faculty of Mathematica, Informatics and Statistics. He concurrently serves as Head of Section III and Head of the Research Group Network Regulation and Modeling / Machine Learning at the Leibniz Institute for Food Systems Biology at TUM (Leibniz-LSB@TUM) in Freising, Germany. His academic foundation includes a Diploma with distinction in Computer Science, Applied Mathematics and Operations Research from the University of Bonn (1981-1986), followed by a summa cum laude Doctorate in Computer Science and Applied Mathematics from CAU Kiel in 1990, where he received dual honors: the CAU Dissertation Award and Best Dissertation Award. Zimmer's research pioneers the integration of bioinformatics, systems biology, and machine learning to decode molecular food-consumer interactions. His group develops causal system models for biological networks, validated through in silico simulations and multi-omics perturbation experiments (transcriptomics/proteomics). Core methodologies include network regulation modeling, algorithmic bioinformatics, and database construction linking food compounds to biochemical networks and cellular phenotypes, with translational goals for food and biotech innovation. His 14 most recent publications (2012-2024) reveal dominant trends in multi-omics immunology and cardiovascular research, featuring computational innovations for high-throughput data analysis. Key themes include host-pathogen dynamics (viral infections), inflammatory disease mechanisms (atherosclerosis), and methodological advances in proteomics/transcriptomics, consistently bridging fundamental bioinformatics with clinical applications. Major scientific recognitions include: CAU Dissertation Award and Best Dissertation Award (1990) Director of LMU's Informatics Department (2010-2012) DFG Review Board membership for biomedical foundations (2008-2016) Leadership of the DFG Bioinformatics Munich Center (2001-2008) Academic Senate election at LMU München (2011) Zimmer directs LMU/TUM's joint B.Sc./M.Sc. bioinformatics programs since 2001 as founding architect of the DFG-funded Bioinformatics Munich initiative. His educational leadership spans spokesperson roles for international training groups (IRTG RECESS), collaborative research centers (SFB1123 Atherosclerosis), and elite programs (Data Science, Munich Center for Machine Learning). Grant stewardship includes directing the DFG Bioinformatics Munich Center and shaping national funding policy via the DFG review board. At Leibniz-LSB@TUM, his research group pioneers databases connecting food compounds to cellular phenotypes through molecular networks, collaborating with Munich universities, clinics, and biotech partners to develop high-throughput sequencing/proteomics applications for future food and health innovations.

Arno OnkenView profile

Assistant Professor

• Data Science
• Machine Learning
• Computational Neuroscience
• +7 more

Dr. Arno Onken is a Lecturer (Assistant Professor) in Data Science for Life Sciences at the School of Informatics, University of Edinburgh, where he is also affiliated with the Institute for Adaptive and Neural Computation. He leads a research group focused on developing machine learning and statistical methods for modeling neural activity and analyzing large-scale neuroscience data. His work bridges artificial intelligence and computational neuroscience. His research interests lie at the intersection of machine learning, statistics, and neuroscience. He develops flexible probabilistic models such as copulas and Gaussian processes, deep learning architectures like Vision Transformers for brain activity prediction, and matrix/tensor factorization techniques for dimensionality reduction in neural datasets. His group aims to uncover interpretable structure in complex neural recordings and understand how behavior and cognition are encoded in population activity. The recent publications reflect a strong trend in combining modern deep learning with classical statistical modeling to analyze large-scale neural recordings. His work spans from foundational methods in copula modeling and information theory to applications in predicting visual cortex responses and modeling brainstem-hippocampus interactions across sleep states. The research has been published in top venues including NeurIPS, CVPR, eLife, and PLoS Computational Biology. Dr. Onken actively supervises PhD students and has developed several open-source scientific software packages, including the Mixed Vine Toolbox and Population Spike Train Factorization Toolbox. He teaches core courses in Machine Learning and Pattern Recognition and Data Mining and Exploration at the University of Edinburgh.

Steven CorcelliView profile

Professor

• Theoretical Chemistry
• Computational Chemistry
• Biophysical Chemistry
• +7 more

Steven Corcelli is a Professor and Interim Dean of the College of Science at the University of Notre Dame, with a joint appointment in the Department of Chemistry and Biochemistry. He has held key leadership roles including Department Chair (2022–2025) and Associate Dean for Interdisciplinary Studies (2019–2022). His research is centered in the Computational Molecular Science & Engineering Laboratory (CoMSEL), where he leads a team exploring molecular and biomolecular systems through advanced simulations. Education: Ph.D. in Chemistry, Yale University, 2001 Sc.B. in Chemistry, Brown University, 1997 His research interests bridge theoretical and experimental physical chemistry, with a strong emphasis on aqueous electrolytes, biomolecular binding, and vibrational spectroscopy . He employs GPU-accelerated molecular dynamics and enhanced sampling techniques to study ion transport in aqueous solutions and the mechanisms of protein-DNA and protein-protein interactions, particularly in immunological contexts such as T-cell receptor binding. His work has significant implications for battery technologies and drug design. The 15 most recent publications reveal a consistent focus on molecular simulation, biophysical chemistry, and spectroscopy , with recurring themes in DNA-ligand binding, ion solvation, and immune recognition. His group develops and applies novel computational methods, such as the coupled local mode approach, to interpret vibrational spectra with high accuracy. Scientific Awards: Thomas P. Madden Award (2020) Rev. Edmund P. Joyce, C.S.C. Award for Excellence in Undergraduate Teaching (2019, 2012) Fellow, American Chemical Society (2016) Sloan Research Fellowship (2009) NSF CAREER Award (2009) Camille and Henry Dreyfus New Faculty Award (2005) Kavli Fellow, National Academies of Science (2011) Corcelli has advised numerous graduate students and postdoctoral researchers, many of whom have gone on to successful careers in academia and industry. His lab collaborates extensively with experimental groups, particularly in spectroscopy and immunology. He has secured substantial research funding and published over 85 peer-reviewed articles. His lab, CoMSEL, benefits from high-performance computing resources through the Center for Research Computing at Notre Dame, enabling large-scale simulations of complex molecular systems. Research Labs and Teams: The Computational Molecular Science & Engineering Laboratory (CoMSEL) is a multidisciplinary research group that combines theoretical chemistry, biophysics, and materials science. The team includes graduate students and staff scientists working on projects ranging from fundamental solvation dynamics to applied biomedical simulations.

Olga BarreraView profile

Senior Lecturer

• Mechanical Engineering
• Computational Mechanics
• Biomechanics
• +12 more

Dr. Olga Barrera is a Reader in Mechanical Engineering at Oxford Brookes University, School of Engineering, Computing and Mathematics. She serves as a year tutor for undergraduate engineering programs and has previously held a Research Fellow position at the Department of Engineering Science, University of Oxford (2008–2017), and a consultancy role at China Medical University Hospital, Taiwan. Her academic work spans teaching, supervision, and leading a research lab focused on image-based multi-physics modeling of multi-phase materials. Reader in Mechanical Engineering, Oxford Brookes University (2018–present) Research Fellow, Department of Engineering Science, University of Oxford (2008–2017) Consultant, Department of Medical Research, China Medical University Hospital, Taiwan Her research interests lie at the intersection of computational mechanics, biomechanics, and materials science, with a focus on soft load-bearing tissues such as the knee meniscus. She integrates advanced imaging (micro-CT), experimental testing, and fractional calculus-based modeling to study tissue behavior and bio-inspired materials. Her work also extends to hydrogen embrittlement in metals and innovative finite element methods. Her recent publications (2023–2025) reveal a strong trend in image-driven modeling of biological tissues, fractional viscoelasticity, and bioinspired engineering solutions. Key themes include the mechanical behavior of meniscal tissue, fluid-structure interaction, anomalous transport in porous media, and deep learning applications in tissue mimicry. These works are published in high-impact journals such as Philosophical Transactions of the Royal Society A , Materials & Design , and Acta Biomaterialia . Scientific awards and grants highlight her international recognition and research leadership: Marie Skłodowska-Curie Individual Fellowship (€190K, 2018–2020) EPSRC HemS grant (Co-I, £340K, 2014–2017) Research Excellence Award, Oxford Brookes (2021–2022, £20K) Visiting Professor Scholarship, France (2023, €4K) FNR Luxembourg Crucible Grant (€8K, 2021–2022) She has supervised numerous postgraduate students including PhD and MSc researchers, and has advised over 30 undergraduate final-year projects across Oxford and Oxford Brookes. She has led or co-led significant research grants from EPSRC, FNR, Rolls-Royce, and the Oxford Orthopaedic Engineering Centre. Her lab, the Oxford image-based multi-physics modelling of multi-phase materials, collaborates with institutions in Italy, Luxembourg, and France. She is an active member of the Materials Processing and Modelling (MPM) research group.

Christine CurrieView profile

Professor

• Operational Research
• Simulation Optimisation
• Healthcare Management
• +9 more

Professor Christine Currie is a Professor of Operational Research within the School of Mathematical Sciences at the University of Southampton. She is a Fellow of the Alan Turing Institute and previously served as Director of the Centre for Operational Research, Management Science and Information Systems (CORMSIS). Her research is primarily funded by EPSRC and spans healthcare, disaster relief, and pricing optimisation. Research Interests: Simulation Optimisation Healthcare Management Decision Making Under Uncertainty Disaster Relief Logistics Optimal Pricing and Revenue Management Her recent work focuses on real-time simulation for emergency departments, infectious disease modelling, patient flow optimisation, food relief procurement in Indonesia, and robust pricing models in transportation and leisure sectors. The trend in her publications shows a strong emphasis on applied operational research with societal impact, particularly in digital twin integration and stochastic optimisation under uncertainty. Scientific Awards: Companion of Operational Research (2024) Professor Currie actively supervises PhD students and has secured multiple research grants, primarily from EPSRC. She has led projects such as 'Dial-a-Ride', 'CREST-OR', and 'Designing a resilient food supply network for natural disasters in West Java, Indonesia'. She also collaborates with external organisations and has supervised student projects with industry partners. Leadership and Editorial Roles: Editor-in-Chief, Journal of Simulation (2015–2024) Member, Editorial Board, Royal Society Open Science (2021–present) Co-chair, OR63 National Operational Research Conference (2021) Member, Operational Research Society Research Panel She is actively involved in the operational research community and leads interdisciplinary research teams including the Operational Research group, Institute for Life Sciences, CORMSIS, and the Centre for Healthcare Analytics.

Graeme BraggView profile

Teaching Professor

• Parallel Computing
• Event-driven Systems
• Bioinformatics
• +5 more

Dr Graeme Bragg is a Senior Teaching Fellow at the University of Southampton within the Department of Electronics and Computer Science . His work spans teaching, research, and technical development with a focus on event-driven computing, bioinformatics, and computational modeling. He actively supervises PhD students and collaborates on interdisciplinary projects. Research Interests: Parallel computing, event-driven systems, genotype imputation, Petri net simulations, subglacial hydrology modeling Teaching: Specializes in hardware description languages and computational methods for engineering students Technical Expertise: RISC-V architecture, FPGA acceleration, bespoke compute fabric development His recent publications demonstrate expertise in applying event-driven computing to diverse problems including: 2025: Automated marking systems for SystemVerilog labs 2025: Seasonal dynamics in subglacial hydrology 2023: Genotype imputation using custom hardware 2022: Optimization algorithms and graph analysis Current research explores: Custom RISC-V FPGA clusters for bioinformatics Event-triggered systems for scientific simulations Parallel computing solutions for molecular modeling Contact: gmb@ecs.soton.ac.uk | +44 23 8059 2784