Find Academic Supervisors

Siddhartha DattaView profile

Research Fellow

• Distributed Machine Learning
• Model Adaptation
• Cybersecurity
• +4 more

Siddhartha Datta is a Researcher at the University of Oxford's Department of Computer Science, specializing in distributed machine learning and adaptive systems. His research develops end-to-end solutions for model training, security, and deployment. Key research areas include: Adaptive learning algorithms for dynamic environments Defense mechanisms against adversarial attacks Human-centered AI interfaces and tools Cross-reality systems blending digital/physical spaces Efficient model compression techniques Current projects investigate prompt engineering for generative models, online learning under data drift, and 3D object detection refinement. His work combines theoretical frameworks with practical implementations, resulting in tools like GreaseTerminator for digital sovereignty and DeepObfusCode for source protection. Datta has collaborated with Google and Cornell University during his doctoral studies. His open-source contributions include neurocogpy (ECoG processing) and Polysemy Word Tagging Tool, demonstrating commitment to accessible research tools.

• Wireless Communications
• Information Theory
• Network Security
• +6 more

Stephen B. Wicker is a Professor at Cornell University's College of Engineering with a distinguished research career spanning over three decades. His work has significantly impacted the fields of wireless communications, information theory, privacy, and security. Wicker has published extensively in top-tier journals and conferences, demonstrating consistent scholarly productivity from the early 1990s through 2021. His research interests include: Wireless network security and privacy Information theory and error control coding Location-based services and privacy implications Digital rights management and consumer protection Blockchain applications for IoT environments Ethical considerations in technology development Legal implications of digital technologies Wicker's recent publications reveal a strategic evolution in his research focus, increasingly addressing the intersection of technical systems with legal and ethical considerations. His work on smartphone privacy and the Fifth Amendment, eBook surveillance, and zero-day exploits demonstrates his unique ability to bridge technical expertise with societal implications. This interdisciplinary approach has positioned him as a thought leader in understanding how technological capabilities intersect with constitutional rights and civil liberties. His scholarly impact is evident through his extensive collaboration network, with significant work alongside researchers like Kolbeinn Karlsson on blockchain for IoT applications, Dipayan P. Ghosh on eBook privacy issues, and Shion Guha on social surveillance in location-based networks. His research has appeared in prestigious venues including Communications of the ACM, IEEE Proceedings, and IEEE Transactions on Information Theory. Wicker has mentored numerous students who have become productive researchers in their own right, including Xiao-an Wang, Hazer Inaltekin, and Kolbeinn Karlsson, who frequently appear as co-authors on his publications. His work continues to address emerging challenges at the intersection of technology, law, and society, making significant contributions to both academic discourse and public policy discussions.

Sebastian GiesenView profile

Research Professor

• Monetary Economics
• Applied Econometrics
• Macroeconomics
• +3 more

Sebastian Giesen is a Research Professor at the Deutsche Bundesbank, affiliated with the Research Centre and the Directorate General Economics. His research focuses on Monetary Economics and Applied Econometrics, with a particular emphasis on macroeconomic modeling, monetary policy analysis, and structural breaks in economic data. He has contributed extensively to understanding interest rate dynamics, forward guidance effectiveness, and the impact of model misspecification on economic forecasts. His publications span topics such as DSGE models, TANK models, and the analysis of structural breaks in time series data. Recent work includes studies on interest-rate pegs, make-up strategies in incomplete markets, and the quantitative implications of forward guidance. Giesen collaborates frequently with researchers like Rafael Gerke and Daniel Kienzler, producing influential papers in journals like the Journal of Money, Credit and Banking and the European Economic Review . His research contributes to the evaluation of monetary policy rules, the assessment of central bank asset purchases, and the development of economic projection frameworks such as the Halle Economic Model. Despite no listed academic awards, his work has advanced methodological approaches in macroeconomic analysis and policy design.

Antonella MallozziView profile

Associate Professor

• Epistemology
• Metaphysics
• Modal Logic
• +3 more

Antonella Mallozzi is an Associate Professor of Philosophy at Providence College's Department of Philosophy. Her research focuses on the epistemology of modality, essence theories, and modal knowledge. She holds a Ph.D. from CUNY - The Graduate Center, specializing in essence, explanation, and modal knowledge. Her work bridges metaphysics and epistemology, particularly exploring how modal concepts (possibility/necessity) are justified through conceptual analysis, imagination, and explanatory frameworks. Key themes include essential properties' explanatory role, the distinction between analytic and synthetic modality, and the relationship between metaphysical grounding and epistemic access. Mallozzi has contributed to foundational debates in modal epistemology through both original articles and edited volumes like the Synthese special issue on new directions in the field. Her publications emphasize methodological rigor and interdisciplinary integration between analytic philosophy and modal logic. Current research trends show sustained engagement with essentialist explanations, counterfactual reasoning, and the philosophical implications of modal anti-reductionism. Though no specific awards are listed, her work demonstrates significant influence in contemporary metaphysical discourse.

• Bayesian Statistics
• Actuarial Science
• Econometrics
• +3 more

Emilio Gómez Déniz is a Professor at the University of Las Palmas de Gran Canaria, affiliated with the Department of Quantitative Methods in Economics and Management and the IU of Tourism and Sustainable Economic Development research group. His academic rank is University Professor, and he is actively involved in Bayesian statistical techniques and decision-making methodologies in economics and business. His research focuses on actuarial science, econometrics, Bayesian methods, health economics, tourism economics, and risk analysis. He has contributed to projects funded by national and regional bodies, including studies on health economics Bayesian solutions, tourism sustainability, and risk analysis using actuarial data. Key projects include 'Economic Evaluation and Meta-Analysis: Bayesian Solutions in Health Economics' (2022–2026) and 'Laboratory of Tourism Experiences and Sustainability in the Multimedia Environment' (2019–2022). His publications span topics like distribution modeling, Bayesian credibility theory, and tourism expenditure analysis. Awards and grants are not explicitly mentioned in the provided text.

François OrieuxView profile

Assistant Professor

• Inverse Problems
• Bayesian Methods
• Signal Processing
• +5 more

François Orieux is an Assistant Professor at the University Paris-Saclay, affiliated with the Laboratoire des Signaux et Systèmes (L2S) within CentraleSupélec. His research focuses on Bayesian methods for inverse problems, computational imaging, and signal processing, with applications in astronomy, microscopy, and embedded AI systems. He holds a PhD in Astrophysical Instrumentation (2009) and an HDR in Computational Imaging (2024). Key research areas include: Development of optimization algorithms for hyperspectral and multispectral fusion High-dimensional sampling techniques for large-scale data GPU-accelerated convolution methods for real-time processing Instrument modeling for radio astronomy and terahertz spectroscopy Recent work emphasizes hardware-aware AI implementations on embedded systems and radio interferometric imaging pipelines. He collaborates with institutions like the Institut d'Astrophysique de Paris and leads projects funded by ANR and EU initiatives. Teaching activities include computational imaging and signal processing courses at CentraleSupélec. His open-source contributions include the Q-MM Python toolbox for optimization algorithms.

Jean VaillancourtView profile

Academic

• Probabilities
• Stochastic Equations
• Random Games
• +2 more

Jean Vaillancourt is an Affiliated Professor at the Department of Decision Sciences, HEC Montréal. He holds a PhD in Mathematics from Carleton University. His research focuses on stochastic processes, probability theory, and data mining applications in social media analysis. Key areas include martingale theory, random walks in random environments, and social network dynamics. He has contributed to methodologies for estimating multi-modal histograms and predicting network restructuring following node removals. His work integrates mathematical rigor with computational techniques, appearing in venues like Stochastic Analysis and Applications and Neural, Parallel and Scientific Computations . Active on platforms like Academia.edu and ResearchGate, his research bridges theoretical probability with practical applications in data science and network analysis. Education: PhD in Mathematics, Carleton University Research Interests: Probabilities, stochastic equations, social media analysis, data mining, and network science. His work emphasizes statistical methods for pattern extraction, centrality-based network prediction, and measure-valued processes. Articles Overview: Recent publications explore martingale convergence theories, random walk periodicity detection, and cascading removals in social networks. These studies highlight his dual focus on foundational probability theory and applied data-driven analysis. Grants & Advising: Supervision activities span the last five years, though specific grants or advisees aren't detailed here. His work on road database automation and edge detection showcases interdisciplinary impact. Labs & Teams: Collaborates across disciplines, integrating mathematical modeling with computational tools. Active in HEC's research ecosystem, contributing to formal concept analysis and SAR imagery processing initiatives.

• Statistical Methodology
• Machine Learning
• Parametric Inference
• +7 more

Claudia Di Caterina is an Associate Professor of Statistics at the University of Verona's Department of Economics. Her research focuses on statistical methodology, including likelihood asymptotics, pseudo-likelihoods, anytime-valid inference, and bias reduction techniques. She holds a PhD in Statistical Sciences from the University of Padova and has conducted research at University College London and the University of Toronto. She teaches courses such as Machine Learning for Economics and Statistics for Business Analysis across various programs. Her academic roles include membership in the Economics Department Council and involvement in committees like the Comitato per le Ricerche con Dati sull'Individuo (CORDI) and Commissione Paritetica Docenti-Studenti. She contributes to research laboratories like VELE (Verona Experimental Lab in Economics) and collaborates with centers such as CRIEP and CIDE. Her publications span topics in high-dimensional data analysis, confidence sequences, and causal inference. She actively engages in public events and third mission activities, including workshops on climate risk and cyber security survey methodologies.

Nicolas HalbwachsView profile

Researcher

• Embedded Systems Verification
• Synchronous Programming
• Formal Methods
• +3 more

Nicolas Halbwachs is a Research Director at CNRS and Director of the Verimag Laboratory, affiliated with the University of Grenoble. His work focuses on formal methods for embedded systems, synchronous programming, and verification techniques. He co-developed the Lustre language, which forms the basis of the industrial tool Scade, and contributed to Linear Relation Analysis for program verification. Halbwachs has held positions including Invited Professor at Stanford University (1992-93) and has been recognized with the 2004 Michel Monpetit Award. He has supervised 10 PhD theses and contributed to major research projects like the SYRF Esprit project and the ASSERT initiative. His research spans verification of real-time systems, abstract interpretation, and automated invariant discovery in array-manipulating programs. Education: State Thesis in Mathematics (Grenoble, 1984), Third Cycle Thesis in Computer Science (Grenoble, 1979) Research Highlights: Synchronous Programming Foundations, Linear Relation Analysis, Lustre Language Development Leadership: Editor of Formal Methods in System Design, Program Committee Chair for CAV'99, TACAS'05, and EMSOFT'09 His recent work addresses invariant discovery in array-based programs, extending abstract interpretation techniques to handle complex data structures.

• Quantum Physics
• High-Energy Physics
• Theoretical Physics
• +4 more

Alexander Karl Rothkopf is affiliated with the University of Stavanger (UiS), where he holds a position in the Department of Mathematics and Physics under the Faculty of Science and Technology. His research focuses on quantum systems, particularly real-time dynamics of strongly coupled systems like the quark-gluon plasma. He employs lattice QCD, Bayesian inference, and machine learning techniques for non-perturbative studies. Key projects include developing discretization schemes, machine-learning enhanced spectral extraction, and real-time simulation strategies. Rothkopf teaches courses on mechanics, quantum mechanics, and lattice-based simulations. His work bridges theoretical physics with computational methods, addressing challenges in heavy quark dynamics and open-quantum systems. Recent research highlights include exact symmetry conservation in numerical methods, novel discretization techniques for quantum systems, and machine learning applications for complex Langevin simulations. He collaborates internationally with institutions like Brookhaven National Laboratory (BNL) and Linköping University. His contributions span journals such as Journal of Computational Physics and Physical Review D , emphasizing computational physics and high-energy theory. Presentations include talks at the International Symposium on Lattice Field Theory and Nordic Lattice Meetings. Despite no explicit awards listed, his prolific publication record underscores his impactful research in theoretical and computational physics. Education: Advanced training in theoretical physics, likely including a PhD in a related field (details not explicitly provided). Grants/Advising: Leads projects funded by UiS collaborations; advises students on lattice simulations and real-time dynamics (specific grant details not listed). Labs/Teams: Involved in interdisciplinary teams focusing on lattice QCD, computational methods, and open-quantum systems at UiS and partner institutions.

Sebastian AndersenView profile

Assistant Professor

• Structural Engineering
• Computational Modeling
• Real-Time Simulations
• +6 more

Sebastian Andersen is an Assistant Professor at the Department of Civil and Mechanical Engineering, specializing in Structures and Safety at the Technical University of Denmark (DTU). His research focuses on computational modeling, real-time simulations, material science, and structural engineering. He has led and collaborated on projects such as Next Generation of 3D-printed Concrete Structures and AwaPave, emphasizing innovation in construction materials and pavement analysis. He has supervised numerous PhD students, including Zafar Hussan and Andrés Caballero Arcos, and contributed to datasets like ALVA for layered viscoelastic analysis. Andersen received the Sund & Bælt Hackathon 2019 award and has published extensively on topics ranging from hybrid simulations to asphalt pavement mechanics. His research interests include structural optimization, 3D printing technologies, and advanced numerical methods for civil engineering applications. Notable contributions include developing the ALVA MATLAB package for pavement analysis and pioneering work on thermoset formworks for complex concrete structures. He has also been involved in activities such as supervising projects on suspension bridge submodelling and optimization techniques for structural longevity. Key Projects: Next Generation of 3D-printed Concrete Structures, AwaPave Supervised Students: Zafar Hussan, Andrés Caballero Arcos, Jesper Waldbjoern Key Awards: Sund & Bælt Hackathon 2019 Labs/Teams: Construct Lab (www.construct.dtu.dk), Structural Analysis Team

Radu-Mihai COLIBANView profile

Associate Professor

• Digital Signal Processing
• Digital Systems Design
• Hyperspectral Image Processing
• +4 more

Radu-Mihai COLIBAN is an Associate Professor at the Department of Electronics and Computers, Faculty of Electrical Engineering and Computer Science, University of Technical Education of Braila. His research focuses on digital signal processing, digital systems design, and hyperspectral image processing with applications in remote sensing, FPGA implementations, and image segmentation. He has contributed to projects like the ATLAS New Small Wheel detector electronics and developed novel methods for hyperspectral visualization and fractal analysis. Education: PhD in Electronics/Computer Science (inferred from academic rank) Advanced training in FPGA design and signal processing techniques Research Interests: Signal Processing: Digital systems, FPGA-based implementations, and real-time signal analysis Image Analysis: Hyperspectral/multispectral data processing, segmentation algorithms, and color texture characterization Applications: Agricultural monitoring, medical imaging, and high-energy physics instrumentation Publications Trends: Recent work emphasizes hyperspectral image processing (e.g., band selection, segmentation) and FPGA-accelerated algorithms (e.g., modular arithmetic, 8b/10b encoding). His 2023-2025 publications show a focus on agricultural datasets (DACIA5), polarization-based analysis, and environmental monitoring. Lab/Teams: Involved in interdisciplinary projects combining signal processing with remote sensing and hardware design. Likely collaborates with the ATLAS experiment team and local/ international research groups in fractal analysis and image denoising.

• Materials Science
• Polymer Engineering
• Biomedical Materials
• +3 more

Fabio Bignotti is an Associate Professor in Materials Science and Engineering at the University of Brescia. His research focuses on three core areas: (1) thermal/mechanical properties of polymers and nanocomposites, (2) stimuli-responsive materials, and (3) biodegradable polymers for biomedical applications. He has authored over 50 peer-reviewed articles and holds multiple patents. Education: Ph.D. in Materials Science (inferred from academic rank). Research interests emphasize structure-property relationships in polymers, 4D printing applications, and radiation-resistant materials. Recent work includes studies on shape memory auxetics, hydrophobically-modified hydrogels, and fracture mechanics of polymer cellular structures. Publications span advanced materials characterization techniques and biomedical material development. No specific awards listed. Advises PhD students in materials science domains. Labs/Teams: Part of MASTLab (Materials for Advanced Science and Technology Laboratory) as indicated by Google Scholar profile redirection.

Hope Xu YanView profile

Assistant Professor

• Health Inequalities
• Family Demography
• Social Stratification
• +3 more

Hope Xu Yan is an Assistant Professor in the Department of Sociology at Louisiana State University's College of Humanities and Social Sciences. Her research examines health disparities, family dynamics, and social stratification through quantitative methods including structural equation modeling and causal inference techniques. Education includes a Ph.D. from University of Maryland (2024) and experience working with large-scale social surveys like the American Time Use Survey and China Family Panel Studies. Research focuses on how racial-ethnic, gender, and socioeconomic inequalities manifest within families, with current investigations into motherhood impacts, time-use disparities, and women's well-being in cross-cultural contexts. Her work spans multiple countries including the U.S., China, and India. Recent publications explore themes of gender gaps in household labor, maternal stress during COVID-19, and healthcare disparities in rural China. Teaching responsibilities include SOCL 2201: Introduction to Statistical Analysis.

Daniela BortolettoView profile

Professor

• Particle Physics
• Experimental High-Energy Physics
• Silicon Detectors
• +5 more

Professor Daniela Bortoletto is Professor and Head of the Particle Physics subdepartment at the University of Oxford, holding a Nicholas Kurti Senior Research Fellowship at Brasenose College. She leads the UK ATLAS collaboration and serves as Deputy Scientific Coordinator of the EU Network AIDA. Her academic journey includes distinguished professorships at Purdue University prior to joining Oxford in 2013. Her research focuses on experimental particle physics within the ATLAS experiment at CERN's Large Hadron Collider. Bortoletto was a key member of the team that discovered the Higgs boson in 2012 and continues to investigate Higgs boson properties, dark matter couplings, and higher-mass Higgs-like particles. Her expertise spans silicon detector development, particularly for the ATLAS inner tracking system upgrade, and she has made significant contributions to Higgs physics through precision measurements of production mechanisms and decay channels. Bortoletto's recent publications demonstrate leadership in cutting-edge detector technology (MALTA2 sensors), novel statistical methods (neural simulation-based inference), and comprehensive Higgs boson characterization. Her work addresses fundamental questions in particle physics through both experimental innovation and sophisticated data analysis techniques. Fellow of the Institute of Physics (2015) Fellow of the American Association for the Advancement of Science (2013) Fellow of the American Physical Society (2004) Alfred P. Sloan Fellow (1994-1996) Ruth and Joel Spira Award for Excellence in Undergraduate Education (2004) Bortoletto maintains extensive leadership in international collaborations, serving on numerous advisory committees including the UK STFC LBNF DUNE PIP-II Oversight Committee and the Scientific Advisory Panel for Belgium's be.h Excellence of Science program. Her editorial work for Nuclear Instruments and Methods reflects her commitment to advancing detector physics methodology. She actively participates in major detector upgrade projects for the High-Luminosity LHC, focusing on silicon pixel technology that will handle the increased collision rates from 2022 onward.