Find Academic Supervisors

Aziza MahomedView profile

Professor

• Engineering Education
• Generative Artificial Intelligence
• Feedback and Assessment in Higher Education
• +7 more

Aziza Mahomed is a Professor in Engineering Education and Deputy Head of the School of Engineering at the University of Birmingham, where she is affiliated with the Department of Mechanical Engineering. She holds a PhD in Mechanical Engineering (Biomaterials) from the University of Birmingham and an MEng from Durham University. She has held academic positions progressing from Teaching Fellow (2015) to Lecturer (2017), Senior Lecturer/Associate Professor (2019), and Professor (2024). Education: PhD in Mechanical Engineering (Biomaterials), University of Birmingham, 2009 MEng in Mechanical Engineering, Durham University, 2005 Postgraduate Certificate in Academic Practice, University of Birmingham, 2017 Her research spans two major domains: biomaterials and biomechanics , focusing on elastomers for joint replacements, accelerated aging, and wear/friction in orthopaedic implants; and engineering education , where her current work centers on generative artificial intelligence, digital feedback tools, and student self-regulated learning. She has published over 20 peer-reviewed articles in journals such as Journal of Biomechanics , Medical Engineering & Physics , and Advances in Engineering Education . Her recent publications show a clear shift toward educational technologies and pedagogical innovation, particularly in feedback systems and inclusive teaching methods. Scientific Awards and Honors: Senior Fellow of the Higher Education Academy (Advance HE), 2020 Fellow of the Institution of Mechanical Engineers (FIMechE), 2019 Chartered Engineer (CEng), 2011 Fellow of the Higher Education Academy (FHEA), 2017 HEFi Education Innovation Award, 2017 Aziza has secured funding from the Royal Academy of Engineering and internal university sources (HEFi). She serves on the academic standards committee of IMechE and is an Ethics Ambassador for the Engineering Professors’ Council. She also acts as an external examiner for UK institutions. She has contributed to public engagement through drama-based STEM outreach and inclusive design projects, such as an aircraft wheelchair seat. Laboratories and Research Teams: Her early research was conducted in biomechanics and biomaterials laboratories at the University of Birmingham, focusing on polymer testing and implant simulation. Currently, her work is associated with engineering education research groups, likely within the School of Engineering, exploring digital learning tools and AI applications in pedagogy.

• Parallel Computing
• Systolic Arrays
• Matrix Operations
• +4 more

Емина И. Миловановић је редовни професор на Електронском факултету у Нишу, Универзитета у Нишу, где је изабрана 2002. године. Припада Катедри за рачунарство и ради у области рачунарства и информатике. Њена образовна позадина укључује: Докторат из рачунарства и информатике (1993, Електронски факултет у Нишу) Магистратура из рачунарства и информатике (1989, Електронски факултет у Нишу) Диплома из аутоматике (1981, Електронски факултет у Нишу) Професорка Миловановић се бави истраживањима у области паралелног рачунарства, са посебним нагласком на систоличке низове, матричне операције и хардверске имплементације. Њена радови показују систематски приступ оптимизацији алгоритама за специјализоване рачунарске архитектуре. Последњих година, њена истраживања су се проширила на Грид рачунарство и FPGA имплементације. Анализом њених научних радова може се закључити да њена истраживања еволуирају од основних алгоритама за матричне операције (1990-их) ка комплекснијим системима за обраду графова и реорганизације података (2000-их). Посебан допринос представљају њена истраживања у области систоличких низова за ефикасну имплементацију линеарне алгебре. Професорка Миловановић је објавила укупно 25 радова у часописима са IMPACT фактором. Најзначајнији радови обухватају: Радове о систоличким низовима за матричне операције Истраживања у области паралелне обраде графова Грид рачунарство и суперрачунарске платформе Фаулт-толерантне системе за матричне операције Тренутно учествује на националном пројекту. Њена научна активност укључује менторство младих научника и сарадњу на развоју нових паралелних алгоритама за хардверску имплементацију. Иако текст не наводи експлицитно име лабораторије, њена специјализација указује на рад у лабораторији за паралелно рачунарство и хардверску оптимизацију на Електронском факултету.

• Urology
• Interventional Pulmonology
• Anesthesiology
• +4 more

Peter Rose Zepernick is a Clinical Professor at Aalborg University's Faculty of Medicine and serves as Chief Physician in the Department of Urology at Aalborg University Hospital since June 1, 2024. Previously, he held the position of specialist consultant in the Department of Anaesthesiology and Intensive Care at the same institution. His professional email is prz@rn.dk. His research spans Urology, Interventional Pulmonology, Anesthesiology, and Radiation Oncology, with core expertise in lung biopsy techniques, apneic oxygenation protocols, fiducial marker development for radiation therapy, and respiratory motion management during interventions. His work frequently employs porcine models to simulate human physiological conditions and advance preclinical validation of medical devices. Publication analysis reveals consistent focus on image-guided procedural innovation, particularly CT-guided biopsies under apneic conditions, NiTi stent applications as radiation fiducials, and real-time tumor tracking systems. These contributions bridge anesthesiology support with precision oncology interventions, emphasizing translational solutions for respiratory and urological pathologies.

Joel S. EmerView profile

Professor

• Accelerator Architectures for Sparse Computation
• Accelerator Architectures for Deep Learning
• Spatial Processing Architectures
• +5 more

Joel S. Emer is a Professor of the Practice in MIT's Department of Electrical Engineering and Computer Science (EECS) and a Senior Distinguished Research Scientist at NVIDIA. His research focuses on computer architecture, processor micro-architecture, and performance modeling. He has contributed to advancements in simultaneous multithreading, cache optimization, and reliability analysis. Emer holds over 25 patents and has published over 60 papers, earning awards like the IEEE Rau Award and induction into the National Academy of Engineering. Education: Ph.D., Electrical Engineering, University of Illinois Urbana-Champaign, 1979 M.S., Electrical Engineering, Purdue University, 1975 B.S., Electrical Engineering, Purdue University, 1974 (highest honors) Research interests include accelerator architectures for sparse computation and deep learning, spatial processing, memory hierarchy design, and reliability analysis. His work on Eyeriss and other accelerators has shaped energy-efficient neural network hardware. Recent projects explore hierarchical structured sparsity (HSS) and compute-in-memory (CIM) techniques. Key awards include the ISCA Best Paper Session (2024), IEEE Micro Top Picks (2024), and the SIGMICRO Test of Time Award (2022). He co-advises students with Prof. Vivienne Sze, focusing on sparse tensor acceleration and energy-efficient designs. Awards: 2023 IEEE Rau Award 2022 IASED Lifetime Achievement Award 2020 National Academy of Engineering Membership 2009 Eckert-Mauchly Award Grants and collaborations span industry partnerships (e.g., NVIDIA) and academic initiatives. Emer leads the Emze Group, exploring hardware-software co-design for emerging architectures. Current work includes sparse tensor accelerators (e.g., HighLight, Tailors) and modeling tools like Sparseloop and Accelergy.

Malte von SchevenView profile

Researcher

• Adaptive structures
• Fluid-structure interaction
• Software Engineering
• +3 more

Malte von Scheven is a Senior Researcher and Deputy Director at the Institute of Structural Analysis and Dynamics at the University of Stuttgart. He holds a Dr.-Ing. degree (2009) and specializes in adaptive structures, fluid-structure interaction, and computational mechanics. Research Focus: Redundancy matrices for structural assessment, high-performance computing, actuator placement optimization Teaching: Finite element methods, computational mechanics, nonlinear structural analysis Leadership: Deputy Director since 2006, conference organizer for ECCOMAS and SMART symposia His work bridges structural mechanics with bio-inspired design, including studies on sea urchin skeletons as models for segmented shells. He has supervised numerous theses on SFRP composites, topology optimization, and adaptive systems. Scientific Engagement: Published 15+ papers on redundancy matrices and FSI Organized mini-symposia at international conferences (ECCOMAS 2024, SMART 2023) Active in university governance through Faculty Council and TIK committee Recent research investigates mechanical modeling of adaptive structures, with applications in civil engineering and architectural geometry. His redundancy matrix framework provides novel performance indicators for robust design and assemblability assessment.

Samira Shirzaei NicholsView profile

Assistant Professor

• Operations Research
• Public Health
• Gender Equity
• +4 more

Samira Shirzaei Nichols serves as an Assistant Professor in the Department of CISA (Computer Information Systems and Analytics) at the College of Business, University of Central Arkansas (UCA), with contact details including email sshirzaei@uca.edu, office COB 305D, and phone (501) 450-5331. Her academic role integrates quantitative analytics with real-world problem-solving across public health, social equity, and business operations. Her research spans Operations Research, Public Health, and Gender Equity, employing machine learning, statistical modeling, and simulation to address epidemiological forecasting (HIV/COVID-19), gender pay disparities in academia/business, and service system optimization. Key methodologies include ARIMA/SARIMA time-series analysis, RNN neural networks, mixed-methods approaches, and Society 5.0 simulation frameworks, demonstrating interdisciplinary rigor in translating theoretical models to societal challenges like refugee health access and grocery store operational efficiency. Analysis of her 15 publications (2014-2025) reveals an accelerating focus on public health crises since 2020, with 60% of recent work dedicated to pandemic response modeling and gender equity analysis. While early research centered on supply chain optimization (2014-2018), post-2020 outputs pivot toward urgent health applications—evidenced by 5 COVID-19 forecasting studies—and structural inequities, using comparative data (2018 vs. 2021) to quantify gender pay gaps across academic disciplines. Her work consistently bridges technical analytics with human-centric outcomes. No information is available regarding student advising, grant funding, laboratory facilities, or research teams from the provided sources, though her prolific publication record indicates active scholarly engagement.

Hans WeiseView profile

Professor

• Superconducting Accelerators
• X-ray Free Electron Lasers
• Particle Accelerator Physics
• +3 more

Hans Weise serves as a Lead Scientist at Deutsches Elektronen-Synchrotron (DESY), a premier German research center within the Helmholtz Association. He currently leads the European XFEL project at DESY and coordinates the XFEL accelerator consortium, which includes multiple institutes from XFEL partner countries contributing to the European XFEL construction through material and personnel resources. Dr. Weise's research focuses on the operation and further development of superconducting accelerators. His career at DESY spans over three decades, beginning with his doctorate studies at the Technical University of Darmstadt. He has held progressively responsible positions including Coordinator of the TESLA Test Facility Linac, PostDoc in the TESLA Test Facility & SRF Technology division, and Group Leader for the DESY MIN department covering Linear Accelerator, Sources, Kicker & Septa, and FLASH Operation. As the current DESY Project Manager for the European XFEL and Coordinator of the XFEL Accelerator Complex since 2010, Dr. Weise oversees one of the most advanced X-ray laser facilities in the world. His work bridges fundamental accelerator physics with practical large-scale implementation of superconducting technology for scientific applications across multiple disciplines including materials science, chemistry, and biology. Dr. Weise's laboratory and team responsibilities include managing the European XFEL accelerator consortium and coordinating the technical development of superconducting linear accelerator systems. His leadership extends to international collaboration among multiple European research institutions contributing to the XFEL project.

• Data Visualization
• Computational Biology
• Tumor Modeling
• +3 more

Rafał Wcisło serves as a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. His academic profile combines teaching responsibilities with active research in computational methods for data visualization and biomedical simulation, contributing to the university's reputation in computer science and interdisciplinary applications. Dr. Wcisło's research centers on innovative approaches to visualizing high-dimensional data and modeling complex biological systems. He has pioneered GPU-accelerated techniques for embedding large datasets and developed the Particle Automata Model (PAM) for simulating tumor dynamics and pathogen expansion. His work in medical applications extends to stroke rehabilitation, where he has designed multimedia holistic methods for patient recovery. These diverse interests reflect a commitment to solving real-world problems through computational innovation. Analysis of his publication record from 2012-2020 reveals a consistent focus on efficiency and interactivity in visualization tools, with a strong emphasis on GPU parallelism. His research trajectory shows increasing integration of computational biology, particularly in oncology, where his models address tumor progression under anti-tumor treatments. The recurring theme across his work is the development of robust, scalable methods that balance computational demands with practical utility in medical and scientific contexts.

• High Energy and Particle Physics
• General Physics
• Accelerator Detector Physics
• +3 more

Prof. Dr. Ahmet Tolga TAŞÇI is a faculty member at Kastamonu University's Faculty of Engineering and Architecture, Department of Electrical-Electronics Engineering, since 2018. Previously, he served as Associate Professor (2013-2017) and Assistant Professor (2008-2013) in Physics at Kastamonu University's Faculty of Science and Letters. His academic career began as a Research Assistant at Abant İzzet Baysal University (1998-2008). PhD in Physics (2008), Abant İzzet Baysal University MSc in Physics (2002), Abant İzzet Baysal University BSc in Physics (1998), Gazi University His research spans High Energy Physics , Particle Physics , and Accelerator Detector Physics , with recent work on ZnO nanorods for photodetectors and MOS diodes. Key projects include anomalous Higgs couplings at LHeC and fourth-generation quark production at CLIC. Selected Awards: TÜBİTAK Yayın Teşvik Ödülü (2009-2014) He has supervised 7 master's theses on topics like ZnO nanostructures and heavy quark production , collaborating with researchers across Turkey. His publications (447* citations) focus on Standard Model extensions and semiconductor materials .

• Mathematical Foundations of Machine Learning
• Explainable Artificial Intelligence
• Online Convex Optimization
• +4 more

Tim van Erven is an Associate Professor of Machine Learning at the Korteweg-de Vries Institute for Mathematics within the Faculty of Science at the University of Amsterdam. His research focuses on the mathematical foundations of machine learning, with particular expertise in online convex optimization, statistical learning theory, and explainable AI. He leads a research group dedicated to developing mathematically rigorous machine learning methods that work effectively without manual fine-tuning. His research interests span the mathematical foundations of machine learning, with emphasis on explainable machine learning, adaptive methods in online convex optimization, faster-than-minimax rates for 'easy data' in statistical learning, PAC-Bayesian concentration inequalities, and statistical learning theory with frequentist analysis of Bayesian methods. His work bridges theoretical guarantees with practical applications, recently shifting toward formal mathematical analysis of explainability methods for black-box AI systems. His recent publications reveal a clear evolution from foundational work in online learning and statistical theory toward explainable AI, with increasing focus on theoretical guarantees for concept learning and algorithmic recourse. The publications demonstrate strong methodological rigor while addressing practical challenges in interpretability and robustness of machine learning systems. Scientific Awards: VICI grant by the Dutch Research Council (2025) VIDI grant by the Dutch Research Council (2019) TOP grant by the Dutch Research Council (2016) NIPS 2014 outstanding reviewer award Rubicon grant by the Dutch Research Council (2011) Van Erven serves in significant academic leadership roles including as a member of the board of directors for COLT, co-chair for the AI & Mathematics initiative, and organizer of the thematic seminar on machine learning. He has successfully secured multiple competitive research grants and leads a research group working on the Mathematical Foundations for Explainable AI project, with several PhD and Postdoc positions currently open.

• Computer Graphics
• Physics-Based Simulation
• Fluid Dynamics
• +3 more

Prof. Dr. Jan Bender holds a professorship in Computer Animation at RWTH Aachen University's College of Engineering. As a leading researcher in physics-based simulation methods, his work focuses on developing advanced numerical techniques for fluid dynamics, deformable solids, and multi-physics interactions through Smoothed Particle Hydrodynamics (SPH) and Finite Element Methods (FEM). Key Contributions: Invented PF-FLIP for two-phase flows, developed SymX symbolic framework for energy-based simulations, created STARK unified solver for robotics applications, and introduced implicit boundary handling for SPH Methodologies: Specializes in hybrid Eulerian/Lagrangian approaches, differentiable physics, adaptive discretization, and machine learning integration for simulation acceleration Research Impact: 2023 & 2024 Best Paper Awards in VMV and SCA conferences. His work enables billion-particle fluid simulations and realistic multi-body interactions for robotics, with applications in welding, thermal spraying, and soft robotics. Collaborations: Works extensively with robotics institutes (Gazebo Fluids extension) and materials science departments (TIG welding, thermal spray modeling). Maintains open-source code repositories for simulation frameworks.

• Medical Physics
• Radiation Therapy
• Dosimetry
• +3 more

Paul Henry Charles is a researcher at the Queensland University of Technology, specializing in Medical Physics and Radiation Therapy. His work focuses on small field dosimetry, Monte Carlo simulations, and 3D printing applications in medical devices. His research interests include: Medical Physics Radiation Therapy Dosimetry Biomedical Engineering Monte Carlo Simulation 3D Printing in Medicine His 15 most recent publications address topics like HDR brachytherapy planning, lung phantom dose correction factors, custom shielding thickness prediction, and QA for 3D printed bolus. Trends in his work emphasize precision in radiation dose measurement, correction-free detector design, and additive manufacturing for tissue-equivalent phantoms. He has collaborated extensively with Scott Crowe, Tanya Kairn, Jamie Trapp, and others, contributing to journals such as Medical Dosimetry , Medical Physics , and Physical and Engineering Sciences in Medicine .

Andrew John George CairnsView profile

Professor

• Mortality and longevity risk modelling and management
• Stochastic mortality modelling
• Securitisation of mortality risk
• +7 more

Andrew John George Cairns is a Professor at Heriot-Watt University, where he is affiliated with the School of Mathematical and Computer Sciences and the Department of Actuarial Mathematics & Statistics. He is well known both in the UK and internationally for his research in financial risk management for pension plans and life insurers, with a particular focus on longevity risk modeling, measurement, and management. His work extends to statistical analysis of mortality and health inequalities, understanding their drivers, and modeling interest rate risk and quantitative risk management for renewable energy operators. Editor of Insurance: Mathematics and Economics since 2023 Editor-in-Chief of ASTIN Bulletin from 2007-2017 Fellow of the Royal Society of Edinburgh since 2016 Member of the Advisory Board of the Academy for the Mathematical Sciences since 2014 Director of the Actuarial Research Centre of the Institute and Faculty of Actuaries from 2016-2020 Cairns' research interests center on risk management, particularly its impact on pension plans and life insurers. His current work focuses on three main themes: modeling and management of longevity risk and its transfer to capital markets; mortality inequalities and their drivers; and using cause-of-death mortality data to understand mortality trends and inequalities. He has made significant contributions to the field through his development of innovative stochastic mortality models, including being a co-inventor of the CBD stochastic mortality models and author of the LifeMetrics open source R code for modeling, measurement, and management of longevity risk. His recent publications demonstrate a strong focus on mortality modeling, particularly in relation to socio-economic factors, cause-of-death analysis, and the impacts of events like the COVID-19 pandemic. His work spans public health, actuarial science, and statistical modeling, with particular emphasis on mortality inequalities at neighborhood levels and the development of advanced modeling techniques like the Common Cohort Effect Model and local linear regression approaches. Edinburgh Mathematical Society Impact Prize (2021) Fellow of the Royal Society of Edinburgh (2016) Robert I. Mehr Award (2016) Halmstad Prize for 'Pricing Death: Frameworks for the Valuation and Securitization of Mortality Risk' (2008) Cairns actively supervises PhD students, with current projects focusing on mortality and longevity risk modeling and management. He has been instrumental in the ARC Longevity, Mortality and Morbidity Research Programme funded by the Actuarial Research Centre. His work contributes to UN Sustainable Development Goals, particularly in areas related to health and well-being. As an active member of the UK and international actuarial profession, he has served in numerous editorial and leadership roles, including as a Fellow of the Faculty of Actuaries since 1993 and as a corresponding member of the Swiss Association of Actuaries. His research has significant practical applications, with his CBD mortality models adopted by the international insurance and pensions industry. The improved understanding of population and mortality data generated through his work benefits both the UK and international pensions and insurance sectors, demonstrating the real-world impact of his academic contributions.

• Applied Dynamical Systems
• Ergodic Theory
• Scientific Computing
• +6 more

Nisha Chandramoorthy serves as an Assistant Professor in the Department of Statistics and the Committee on Computational and Applied Mathematics (CCAM) at the University of Chicago, with her office located in Jones 122B. She can be contacted at (773) 834-1916 or via email at nishac@uchicago.edu, and maintains a professional website at https://ni-sha-c.github.io. Educational background: PhD, Massachusetts Institute of Technology (MIT) Master's degree, Massachusetts Institute of Technology (MIT) B. Tech., Indian Institute of Technology (IIT) Roorkee Her research program integrates applied dynamical systems, ergodic theory, and computational statistics to develop rigorous algorithms for scientific computing. Current work focuses on accelerating Bayesian posterior sampling within dynamical systems and advancing linear response theory for invariant measures. She actively explores dynamical systems approaches to optimization and learning algorithms, targeting applications in geosciences through sensitivity analysis, model selection, data assimilation, and PDE-based model order reduction.

• Algorithms and Data Structures
• Big Data
• High-Performance Computing
• +12 more

Francesco Silvestri is an Associate Professor in Computer Engineering at the Department of Information Engineering , University of Padova . He has held previous roles as Assistant Professor (2016-2019), Post-Doc (2015-2016 at IT University of Copenhagen; 2009-2014 at University of Padova), and Part-Time Lecturer (2013-2014 at IT University of Copenhagen). He earned a Ph.D. in Computer Engineering from the University of Padova (2009). Research Focus: Algorithms and data structures for big data processing, high-performance computing, similarity search, graph mining, I/O-efficient algorithms, mobility algorithms, and differential privacy applications. Teaching: Courses include Big Data Computing and Algorithm Design (University of Padova), Advanced Algorithms Seminar (IT University of Copenhagen). Scientific Contributions: ICDT Best Paper Award (2023) for subgraph enumeration ACM SIGMOD Research Highlights (2020) for fair similarity search Developed patented MapReduce methods for triangle enumeration Collaborations and Supervision: Current PhD students: Mariafiore Tognon (2024), Linghan Zeng (2023), Fabrizio Boninsegna (2022). Collaborators include Ninh Pham (University of Auckland), Gianfranco Bilardi, and Rasmus Pagh. Personal Interests: Active in Dottor Clown Padova for hospital clowning, family life with wife Elisa Salvagnin and three children, and cycling advocacy in Padova.