Find Academic Supervisors

Justin LeidwangerView profile

Associate Professor

• Maritime Archaeology
• Mediterranean Archaeology
• Roman and Late Antique Archaeology
• +5 more

Justin Leidwanger is an Associate Professor of Classics at Stanford University with a courtesy appointment in Oceans at the Doerr School of Sustainability, specializing in Mediterranean maritime archaeology through fieldwork in southeast Sicily and southwest Turkey. His educational background includes: Ph.D. in Art and Archaeology of the Mediterranean World from the University of Pennsylvania (2011) M.A. in Nautical Archaeology and Anthropology from Texas A&M University B.A. in History & Classical Studies from Loyola University Chicago Leidwanger's research centers on Mediterranean mobilities, maritime communities, and exchange systems from the Roman period through late antiquity, using shipwrecks and port sites to analyze socioeconomic dynamics. His work integrates ceramic analysis, port network studies, and digital heritage methods to explore ancient technologies of distribution and long-term maritime interactions. Recent publications reveal consistent focus on Roman/late antique maritime economies with growing emphasis on digital documentation (3D modeling, GIS) and contemporary relevance through migration studies. Key trends include transport amphorae standardization, underwater survey methodologies, and the intersection of ancient maritime heritage with modern migration patterns in the central Mediterranean. Leidwanger actively advises students in classical archaeology while leading major field projects including the Marzamemi 'church wreck' investigation (2013-2019) and ongoing 'U Mari research in Sicily. His work combines underwater survey, community-based archaeology, and heritage activism addressing both ancient tuna fishing traditions (mattanza) and contemporary migration routes. He directs the Maritime Archaeology and Digital Heritage Lab (MEDLab) at Stanford's Archaeology Center, which supports advanced digital modeling (photogrammetry, laser scanning, network analysis) and ceramic analysis (petrography, pXRF, computational morphometrics) for field research and museum collaborations.

Zachary E. RossView profile

Professor

• Seismology
• Geophysics
• Machine Learning
• +7 more

Zachary E. Ross is a Professor of Geophysics at the California Institute of Technology (Caltech) and holds the William H. Hurt Scholar distinction since 2021. His research integrates machine learning, computational mathematics, and seismology to analyze earthquakes and fault zones using large seismic datasets. Education B.S., University of California, Davis (2009) M.S., California Polytechnic State University, San Luis Obispo (2011) Ph.D., University of Southern California (2016) His research focuses on high-resolution imaging of fault zones, understanding earthquake sequences in space and time, and applying artificial intelligence to seismic data analysis. He develops scalable algorithms for waveform inversion, ground-motion synthesis, and real-time seismic monitoring. Recent publications highlight his work on neural operators for wave propagation, AI-driven seismicity analysis, and induced earthquake dynamics. He teaches advanced courses including Ge 264 – Machine Learning in Geophysics and Ge 271 – Dynamics of Seismicity . Scientific Awards William H. Hurt Scholar (2021–present)

Simon MooreView profile

Professor

• Computer Architecture
• Computer Security
• Hardware Security
• +3 more

Simon Moore is a Professor of Computer Engineering at the University of Cambridge's Department of Computer Science and Technology. He leads the Computer Architecture research group, focusing on secure processors and subsystems, particularly the CHERI project. His work emphasizes formal verification, hardware-software co-design, and scalable security solutions. He is a Fellow and Director of Studies at Trinity Hall, overseeing undergraduate admissions and mentoring in Computer Science. Research Interests: Moore's primary focus is the CHERI secure processor architecture, integrating RISC-V cores with formal verification. His work spans secure hardware design, memory safety, and embedded systems. Notable contributions include the CHERI-RISC-V microarchitecture, CheriABI, and formal verification frameworks. Key Projects: CHERI, CheriBSD, Morello (ARM collaboration) Recent Achievements: Test of Time Award (IEEE Security & Privacy 2025), finalist for Bhattacharyya Award (2022) Grants: Innovate UK Digital Security by Design, DARPA Mission Oriented Resilient Clouds Publications: Over 200 papers on secure architectures, including influential work on CHERI's capability model, formal verification, and hardware security. Recent focus areas include temporal memory safety, embedded system security, and GPU-based capability systems. Labs/Teams: Directs the Computer Architecture Group and collaborates with industry partners like ARM and Microsoft on CHERI implementations.

• Computational Social Science
• Public Health
• Injury Prevention
• +4 more

Associate Professor Jason Thompson holds an Associate Professor position in the Department of Psychiatry at the University of Melbourne. He is affiliated with the Faculty of Medicine, Dentistry and Health Sciences and previously served as Co-Director of the Transport, Health and Urban Systems (THUS) Research Laboratory at the Melbourne School of Design. He earned a PhD in Medicine (2015) from Deakin University, a Master's in Clinical Psychology, and a Bachelor of Science with Honours. His research focuses on computational social science applied to injury rehabilitation, compensation systems, and healthcare design. He has attracted over $5M in research funding and published over 100 articles. Key areas include agent-based modeling, systems dynamics, and policy analysis for public health challenges such as pandemic response and urban mobility. Thompson currently leads the NHMRC Centre of Excellence in Compensable Injury after Road Crashes. Grants: ARC Future Fellowship (2022), DECRA (2017) Awards: Best Paper Award (Computational Social Science Society of the Americas, 2017) Labs: THUS Research Lab (until 2024) His work bridges epidemiological modeling (e.g., influencing Victoria's 2020 pandemic exit strategy) and complex systems analysis for injury prevention and health system design.

Alexandr LucasView profile

Teaching Professor

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +3 more

Alexandr Lucas is a Teaching Professor in Robotics at the University of Sheffield's School of Computer Science. He joined in September 2019 and holds roles including Deputy Admissions Tutor (General Engineering) and IPE Tutor. His research focuses on developmental neuro-robotics, cognitive assessment via human-robot interaction, and educational robotics applications. He contributes to courses like COM1005 (Machines and Intelligence) and COM3528 (Cognitive and Biomimetic Robotics), developing teaching materials for MiRo robots and simulators. Publications include work on cognitive skill assessment using cloud computing and robotic systems, visual finger-counting for neuro-robotics learning, and public perception analysis of robots in urban environments. He co-founded the SERAI Network CIC and maintains active roles in robotics education and outreach. Lucas has created extensive teaching resources, including guides for MiRoCloud simulation platforms and visual coding tools (MiRoCODE). His work emphasizes practical robotics education and bridging theory with hands-on experiments in undergraduate and postgraduate programs.

Suresh VenkateshView profile

Assistant Professor

• Metamaterials
• Millimeter-Wave and Terahertz Communication
• Antenna Design
• +4 more

Suresh Venkatesh is an Assistant Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He previously served as a postdoctoral research associate at Princeton University (2018–2022) and earned his Ph.D. in Electrical Engineering from the University of Utah in 2017. His academic journey also includes a Master's degree in Electrical Engineering from NC State in 2010. Education: Ph.D. in Electrical Engineering, University of Utah, 2017 Master's in Electrical Engineering, North Carolina State University, 2010 Research Interests: His work focuses on metamaterials and surfaces at GHz-THz frequencies, millimeter-wave phased arrays, and innovative applications in 5G/6G communication systems. Key areas include antenna design, physical layer security, advanced electromagnetic simulations, and reconfigurable systems using CMOS integration. He explores origami-based platforms for adaptive RF imaging and employs spatio-temporal modulation techniques to enhance wireless security and efficiency. Publications Trends: Recent work emphasizes mmWave and THz communication, with a focus on reconfigurable intelligent surfaces, secure low-latency links, and CMOS-based designs for direct detection receivers and cytometers. His research bridges theoretical concepts with experimental validation, particularly in wavefront manipulation and sparse imaging techniques. Awards and Honors: Mistletoe Research Fellowship (2021) Advising and Grants: Venkatesh contributes to research teams like the NC State 6GNC initiative, which spans 6G technologies. He actively organizes conferences such as the World Microwave Congress 2024 as TPC Co-Chair and participates in IEEE technical committees. His grants and collaborations drive advancements in metamaterials, secure wireless systems, and CMOS-integrated solutions. Labs and Teams: He leads efforts in the NC State ECE Department, focusing on labs involving reconfigurable antennas, computational imaging, and integrated systems. His work intersects with the 6GNC team to develop future communication technologies and secure mmWave/THz systems.

Alfred KumeView profile

Senior Lecturer

• Shape analysis
• Directional statistics
• Image analysis
• +1 more

Dr. Alfred Kume is a Senior Lecturer in Statistics at the University of Kent, affiliated with the School of Mathematics, Statistics and Actuarial Science. He has held this position since 2004 and has been involved in examining processes for the Institute of Actuaries. His research focuses on shape analysis, directional statistics, image analysis, and stochastic geometry. Kume obtained his PhD and postdoctoral training at the University of Nottingham after working as an actuary. He has supervised students including Theodoros Gkolias and Justyn Campbell-White. His work spans statistical methodology applied to astronomy (e.g., stellar light observations, HII regions) and computational statistics (e.g., holonomic gradient methods, clustering algorithms). His publications reflect expertise in probability distributions, algorithm development, and interdisciplinary applications. His office is located in Cornwallis South, Canterbury Campus. Research interests emphasize statistical techniques for shape and directional data, with applications in astronomy and biology. Key contributions include saddlepoint approximations for normalizing constants and statistical clustering methods. His work bridges theoretical statistics with practical problems in astrophysics and actuarial science. Publications highlight trends in statistical methodology (e.g., Bingham/Fisher-Bingham distributions), computational algorithms, and interdisciplinary collaborations. While no specific awards are listed, his extensive publication record and academic roles reflect scholarly recognition. Advising focuses on statistical shape analysis and Bayesian methods, with grants possibly tied to collaborative projects. He is part of research teams analyzing molecular clouds and astronomical phenomena. His lab or team activities are integral to interdisciplinary projects, though specific lab names are not mentioned.

Mohsen PourahmadiView profile

Professor

• Time Series Analysis
• Multivariate Statistics
• Covariance Estimation
• +7 more

Mohsen Pourahmadi is a Professor in the Department of Statistics at Texas A&M University, part of the College of Arts & Sciences. His research focuses on developing methodologies for modeling covariance matrices in multivariate and time series data, with applications to financial analysis, longitudinal studies, neuroeconomics, and high-dimensional data. Key tools include graphical lasso algorithms, Cholesky decomposition, and Bayesian approaches. He emphasizes extending generalized linear models (GLM) to covariance matrix estimation, leveraging prediction theory and stochastic processes. Education details are not explicitly provided in the text. His work spans theoretical advancements in covariance estimation, such as sparse VAR models, nonstationary process analysis, and regularized multivariate regression. He has contributed to applications like detecting cyber attacks on infrastructure systems and analyzing breast cancer data through Bayesian networks. Research interests include time series graphical models, antedependence models for longitudinal data, and regularization techniques for high-dimensional covariance matrices. His recent work explores fused-lasso penalties, Bayesian correlation matrix estimation, and stationary subspace analysis. Pourahmadi has authored numerous articles on topics ranging from multivariate volatility modeling to nonparametric covariance estimation, emphasizing both computational efficiency and theoretical rigor.

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.

• Theoretical/computational mechanics of materials
• Computational plasticity
• Multi-scale material modeling
• +4 more

Curt Bronkhorst is the Harvey D. Spangler Professor of Engineering and Professor of Applied Mechanics in the Department of Mechanical Engineering at the University of Wisconsin-Madison. He received his B.S. in Mechanical Engineering and Mathematics (1985), M.S. (1988), and Ph.D. (1991) in Mechanical Engineering from the Massachusetts Institute of Technology. His career includes roles as Senior Scientist at Weyerhaeuser (1991–2002) and Scientist/Project Leader at Los Alamos National Laboratory (2002–2019) before joining UW-Madison. He leads the Army Research Laboratory's Center for Extreme Events in Structurally Evolving Materials and contributes to the Theoretical and Computational Mechanics of Materials Group . PhD (1991) - Massachusetts Institute of Technology MS (1988) - Massachusetts Institute of Technology BS (1985) - University of Wisconsin-Madison Bronkhorst's research focuses on theoretical and computational mechanics of materials , particularly under extreme conditions. Key themes include: Coupled thermo-mechanical deformation Finite elasticity and dislocation slip plasticity Deformation twinning and phase transformations Pore nucleation and adiabatic shear banding Brittle-to-ductile transition mechanisms Multi-scale modeling of damage evolution His 2025–2023 publications emphasize data-driven modeling , void nucleation , and machine learning integration in EBSD analysis. Recent work explores gradient nanostructured metals and low-grain polycrystal stress heterogeneity . 2019: Harvey D. Spangler Professorship 2012: DOE Defense Programs Award (Implosion Predictive Capability) 2009: DOE Outstanding Mentor Award 2007–2008: Los Alamos Distinguished Performance Awards Fellow, American Society of Mechanical Engineers Member, Phi Kappa Phi and Tau Beta Pi Honor Societies Bronkhorst serves as Associate Editor for the International Journal of Plasticity and president of Northland Partners, LLC. He is affiliated with UW-Madison's Nuclear Engineering & Engineering Physics and Materials Science & Engineering departments. No formal advisees are listed, but his computational framework has been adopted in grants like the DMREF collaborative research on grain-interface design.

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

Daniel A LevinthalView profile

Professor

• Organizational Adaptation
• Strategic Management
• Technological Competition
• +2 more

Daniel A Levinthal is the Reginald H. Jones Professor of Corporate Strategy and Professor of Management at the Wharton School, University of Pennsylvania. With extensive publications on organizational adaptation and industry evolution in technological contexts, he serves as Editor-in-Chief for Strategy Science and Organization Science. Research Interests Industry evolution Organizational learning Technological competition His 2024 research examines organizational search strategies, showing how cautious exploitation combines slow belief updating with strong explicit exploitation for effective adaptation. Recent work explores how political coalitions drive organizational change, with hierarchical belief influence structures proving more effective than flat designs in certain environments. Earlier studies developed the "Mendelian executive" framework and advanced Carnegie School decision-making theory. Scientific Awards Fellow of Strategic Management Society Fellow of Academy of Management Distinguished Scholar Awards (3 divisions) Irwin Award as Distinguished Educator 4 Honorary Doctorates Levinthal teaches advanced strategy courses (MGMT9000, MGMT9150) and graduate enterprise management (MGMT6110). His research has established foundational insights about organizational capabilities, knowledge aggregation, and strategic inertia.

Tobias BinningerView profile

Researcher

• Electrochemistry
• Materials Science
• Quantum Mechanics
• +5 more

Dr. Tobias Binninger is a researcher at the Institute of Energy Technologies (IET) within Forschungszentrum Jülich GmbH, Germany. His work focuses on theoretical and computational modeling of materials for electrochemical energy systems , particularly in the context of catalysts and solid-state electrolytes. His research spans topics such as electrochemical interfaces , redox reactions , quantum capacitance , and nanoparticle stability , as reflected in his publications in high-impact journals. He has contributed significantly to understanding the Oxygen Evolution Reaction (OER) mechanisms and solid-state electrolyte materials through advanced computational methods like quantum annealing and density functional theory. Recent studies highlight his focus on electrolyte correlation effects , metal-support interactions , and co-electrolysis cell design for CO 2 reduction. Despite lacking explicit details on awards or mentoring, his work addresses critical challenges in energy storage , catalyst degradation , and quantum modeling of electrochemical systems .

• Agent-Based Computational Economics
• Economic Networks
• Macroeconomics
• +3 more

Giorgio Fagiolo is a Full Professor of Economics at Sant'Anna School of Advanced Studies. His work spans agent-based computational economics, economic networks, and macroeconomic policy analysis. University: Sant'Anna School of Advanced Studies (Scuola Superiore Sant'Anna) Department: Economics Email: giorgio.fagiolo@sssup.it Research interests focus on agent-based modeling , macroeconomic instability , and climate-economy interactions . He develops computational models to study industrial dynamics, financial integration, and policy design in complex systems. Key themes: Endogenous growth cycles, R&D network stability, and green transition policies. Methodological emphasis: Empirical validation of agent-based models and nonlinear economic dynamics. Scientific awards include collaboration with leading institutions like ETH Zurich, Columbia University, and OFCE Sciences Po. His publications appear in journals such as Journal of Economic Dynamics and Control and Ecological Economics .