جست‌وجوی استاد و پژوهشگر

Ammar Kamoonaمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۲ مورد دیگر

Dr. Ammar Kamoona is a Researcher at the School of Engineering, RMIT University, specializing in Artificial Intelligence, Machine Learning, and their applications in energy systems, manufacturing, and computer vision. His work focuses on anomaly detection, energy demand prediction, and optimization algorithms. He is open to supervising Masters and PhD students in AI for clean energy and sustainability. His research outputs span 14 peer-reviewed articles and reports between 2018–2024, including notable contributions to smart grid technologies, photovoltaic power prediction, and defect detection in manufacturing using advanced machine learning frameworks. Notable collaborations involve projects like the 'Optimisation of Behind the Meter DER Generation Assets' funded by C4NET. Dr. Kamoona’s articles demonstrate a strong trend in applying deep learning and optimization techniques to solve real-world challenges in energy systems and manufacturing safety. His work bridges theoretical advancements in AI with practical industrial applications, emphasizing sustainability and safety. He holds an ORCID identifier (0000-0002-7441-9344) and can be contacted at ammar.kamoona@rmit.edu.au for supervision or collaboration inquiries.

• Computer Science Education
• Software Security
• Trust Models
• +۵ مورد دیگر

Dr. Charles Thevathayan is an Associate Professor in the School of Science at RMIT University, Australia. His academic focus spans Computer Science Education, Software Security, Trust Models, and Model Checking. He actively contributes to curriculum design and pedagogical innovation in computing education. His research explores areas such as algorithmic reasoning, constructivist learning tools, and service-oriented frameworks for social data analysis. Dr. Thevathayan is open to supervising PhD/Masters students in these domains. Research interests include Big Social Data Analysis, educational technology, and software engineering methodologies. His work emphasizes reducing cognitive load in programming education and enhancing industry-relevant skills through innovative pedagogical approaches. He collaborates with industry partners to bridge theoretical and practical aspects of computing education. Recent publications highlight his contributions to algorithmic reasoning tasks, UML sequence diagram learning tools, and adaptive remediation systems for novice programmers. His research has been presented at conferences like ACM SIGCSE, ITiCSE, and IEEE TrustCom. Dr. Thevathayan holds expertise in mentoring diverse student cohorts and evolving project-based learning frameworks. He is committed to advancing educational practices in computing disciplines through evidence-based approaches.

Tomasz Tkoczمشاهده پروفایل

دانشیار

• Analysis
• Probability
• Convex Geometry
• +۵ مورد دیگر

Tomasz Tkocz is an Associate Professor in the Department of Mathematical Sciences at Carnegie Mellon University (CMU), affiliated with the Mellon College of Science. He holds a Ph.D. from the University of Warwick and has held postdoctoral positions at Princeton University and the Mathematical Sciences Research Institute (MSRI). His research focuses on analysis, probability, and convex geometry, with emphasis on high-dimensional phenomena, geometric inequalities, and information theory. Tkocz has taught courses ranging from undergraduate calculus to graduate-level topics in complex analysis, functional analysis, and probability. Notable contributions include work on Gaussian inequalities, convex body sections, and entropy-related problems. Education: Ph.D. in Mathematical Sciences, University of Warwick Postdoctoral Fellowships: Princeton University, MSRI Research Interests: Analysis of high-dimensional geometric structures Probabilistic methods in convex geometry Entropy and concentration inequalities Random matrices and log-concave distributions Recent Publications Trends: Tkocz’s recent work explores geometric stability phenomena (e.g., simplex and polydisc slicing), entropy interpretations of anti-concentration, and sharp inequalities for random variables. His 2025 papers extend tail bounds for uniform sums and reverse Hölder inequalities, reflecting ongoing contributions to probabilistic and geometric analysis. Teaching & Outreach: Tkocz has instructed over a decade of courses at CMU, including Complex Analysis, Functional Analysis, and Real Analysis. His materials emphasize rigorous problem-solving and applications of abstract mathematical concepts.

• Formal Verification
• Model Checking
• Sensor Systems
• +۳ مورد دیگر

Ivaylo Valkov is a Lecturer in the School of Computing Science at the University of Glasgow, having joined the academic staff in June 2024. He completed his PhD in Computing Science at the University of Glasgow in 2024 under Prof. Alice Miller, focusing on formal analysis of wireless sensor systems. Prior to this, he earned a Master's degree in Computing Science and Mathematics from the same university in 2018. His research emphasizes rigorous mathematical analysis of software and hardware systems, particularly through model checking techniques. Key areas include system verification, sensor networks, combinatorial problems, and probabilistic model checking. Valkov has contributed to advancements in overtaking planning algorithms, symmetry reduction methods, and optimization of scheduling problems like the social golfer problem. His publications (6 items) span peer-reviewed journals like Science of Computer Programming and Symmetry , as well as conferences such as SPIN 2024 and FMAS 2021. While no specific awards are listed, his work reflects sustained engagement with formal methods and their applications in real-world systems. Valkov teaches Algorithms and Data Structures at the Master's level and co-teaches Software Engineering and Research Methods courses. His teaching aligns with his research focus on logical problem-solving and systematic analysis.

James Lockerbieمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Goal Modelling
• Creativity Support Tools
• +۳ مورد دیگر

James Lockerbie is a Research Fellow in the Faculty of Management at Bayes Business School (City, University of London). He holds a Master's degree in Electronic Business Systems from the same institution and has been active in research since 2005. His work focuses on goal modeling, creativity support tools, and AI applications for professional domains like sports coaching and healthcare. Education: MSc in Electronic Business Systems from City, University of London (2005). Research Interests: Goal modeling and analysis, AI-driven creativity tools, and digital innovation in professional work contexts. His projects include AI systems for elite sports coaches, design project creativity, and dementia care support systems. Recent work explores generative AI for software opportunity discovery and health-and-safety solutions in manufacturing. Publications span AI applications in creativity, healthcare, and industrial settings. His 2025 article in IEEE Software highlights AI-driven software innovation, while 2024 work in Digital Health addresses quality-of-life tools for aging populations. Collaborations include projects with sports organizations, manufacturing firms, and healthcare institutions. His research emphasizes human-centered design principles and practical tool implementation across diverse sectors.

Hans Spadaمشاهده پروفایل

استاد

• Cognition and Emotion
• Computer-supported Collaborative Learning
• Environmental Psychology
• +۳ مورد دیگر

Prof. Dr. Hans Spada is a Full Professor of Psychology at the University of Freiburg, Germany. His academic career includes roles as Vice-Director of the Educational Science Department at the University of Kiel (1973-1980) and Assistant Professor at the University of Vienna (1969-1973). He is affiliated with the Department of General Psychology at the Institute of Psychology, focusing on cognition-emotion interactions, computer-supported collaborative learning, and environmental psychology. Research interests span cross-cultural emotion studies, collaborative learning technologies, and risk perception in environmental contexts. Notable contributions include work on cognitive determinants of emotions in Tonga and Germany, collaborative problem-solving frameworks, and the design of effective computer-mediated learning environments. Key Awards: Landeslehrpreis Baden-Württemberg (1994), Honorary Membership at Humboldt University (1997), and Academia Europea membership (1994). Leadership Roles: Chairman of Leibniz Gemeinschaft Senate Committee (2010), and International Advisor to the Max Planck Institute for Human Development (2011). Publications emphasize innovative methods in collaborative learning assessment and cross-cultural psychological research. His work bridges cognitive science, educational technology, and environmental decision-making, with a focus on practical applications in teaching and policy.

Ahmad Abdelfattahمشاهده پروفایل

عضو هیئت علمی

• High Performance Computing
• Parallel Numerical Algorithms
• GPU Computing
• +۳ مورد دیگر

Dr. Ahmad Abdelfattah is a Research Assistant Professor at the University of Tennessee's Innovative Computing Laboratory (ICL). He holds a PhD in Computer Science from KAUST (2015), an MS in Computer Engineering from Ain Shams University (2010), and a BS in Computer Engineering (2006). His research focuses on high-performance computing, parallel numerical algorithms, and GPU acceleration, particularly in dense and sparse linear algebra libraries. He leads the MAGMA library and has contributed to NVIDIA's cuBLAS and AMD's rocBLAS libraries. His work emphasizes exascale computing, mixed-precision arithmetic, and optimizing batched operations on GPUs. His research spans algorithm design for GPUs, including batched matrix operations, sparse linear algebra, and high-order finite element methods. He has developed libraries like libCEED and SLATE, targeting exascale systems. His contributions address challenges in memory-bound computations, irregular patterns in matrices, and efficient use of tensor cores. Key trends in his publications include optimizing GPU kernels for small matrices, exploring mixed-precision techniques for solving linear systems, and enabling portable performance across diverse architectures. His work bridges theoretical numerical methods with practical implementation on modern hardware, aiming to accelerate scientific applications. Awards and recognitions include acknowledgments from NVIDIA and AMD for contributions to their BLAS libraries. His advising and grants involve advancing exascale computing through collaborations with ECP (Exascale Computing Project), focusing on CEED-enabled applications and performance tuning. He leads initiatives to enhance software tools for high-order discretizations and scalable linear algebra solutions. Abdelfattah is affiliated with the Innovative Computing Laboratory, contributing to both academic and industrial partnerships. His research impacts fields like computational science, computer vision, and robotics through optimized algorithms and libraries.

• Supply Chain Management
• Operations Management
• Business Analytics
• +۴ مورد دیگر

Iddrisu Awudu is an Associate Professor of Management at Quinnipiac University and serves as the Muslim Chaplain. He holds a PhD in Industrial and Manufacturing Engineering from North Dakota State University (NDSU), an MSc in Industrial Mathematics from Kwame Nkrumah University of Science and Technology (KNUST), and a B.S. in Computer Science and Physics from the University of Ghana. His research focuses on supply chain management, operations management, business analytics, and renewable energy, with an emphasis on sustainable practices, risk hedging, and policy-driven strategies in emerging economies. Prof. Awudu has extensive industry experience with organizations like Navteq, Nestlé, and Afripa Telecom across the USA, UK, and Ghana. He teaches courses such as Supply Chain Management, Operations Management, and Decision Making in Business at both graduate and undergraduate levels. His work integrates theoretical frameworks with practical applications, including project management pedagogy and ERP systems like SAP for advanced planning. His publications span journals like Energy Economics, International Journal of Production Research, and Renewable and Sustainable Energy Reviews, with topics ranging from biofuel supply chains to pharmaceutical logistics in Ghana. He has also been a Carnegie African Diaspora Fellow (2015, 2017) and participated in Harvard’s Case Study Workshop. His consulting projects include engagements with the Veteran Association (VA), MTN Ghana, and WAEC Ghana, emphasizing real-world problem-solving in supply chain optimization and organizational performance. Prof. Awudu’s research trends highlight interdisciplinary approaches, combining operations research with sustainability, AI integration, and cultural studies. His work often bridges academic theory with practical industry challenges, particularly in developing economies. Key themes include leveraging data-driven strategies for supply chain resilience and promoting inclusive economic policies through supplier engagement. In addition to academic contributions, he has developed innovative teaching methods using project-based learning and advanced scheduling models for healthcare and audiology clinics. His professional designations include SAP Super User for ERP systems, reflecting his technical expertise in logistics optimization.

Aaron R. Warrenمشاهده پروفایل

دانشیار

• Physics Education Research
• Computational Astrophysics
• Mathematical Physics
• +۳ مورد دیگر

Aaron R. Warren is an Associate Professor of Physics at Purdue University Northwest (PNW), serving as Director of the Science Interdisciplinary Research Center (SIRC). He holds a Ph.D. in Physics from Rutgers University (2006) and a B.A. in triple majors (Physics, Mathematics, Astronomy) from Vassar College (2000). His research focuses on physics education research (PER) and computational astrophysics, including Bayesian-based teaching strategies and numerical simulations of binary neutron star mergers. He has received awards such as the PNW Teaching Incentive Award (2018) and the Goldwater Scholarship (1999). Warren’s teaching emphasizes student-centered learning, integrating practical applications and critical thinking. Professional roles include PNW Physics Lab Coordinator (2007–2016), Astronomy Club Advisor (2011–2016), and dual credit program liaison. His grants include a $597,781 NSF IUSE grant (2017–2021) exploring lab activity effectiveness and COES-funded research on neutron star mergers. Key research interests span PER methodologies, gravitational wave modeling, and student epistemology development. He collaborates on projects like ‘Mass Ejecta in Binary Neutron Mergers’ and ‘Quantitative Critical Thinking’ curricula. His work bridges theoretical physics with educational innovation, addressing both astrophysical phenomena and classroom pedagogy.

• Algebraic Combinatorics
• Spectral Properties
• Probability Theory
• +۳ مورد دیگر

Nadia Lafrenière is an Assistant Professor with a limited-term appointment at Concordia University . She holds a Ph.D. in Combinatorial Mathematics from Université du Québec à Montréal (UQAM), under the supervision of Franco Saliola. Previously, she was a John Wesley Young Research Instructor at Dartmouth College. Her research focuses on algebraic combinatorics , particularly spectral properties of combinatorial structures, card shuffling dynamics, and dynamical algebraic systems. She is also deeply engaged in mathematics outreach, designing activities for diverse audiences through radio shows, walking tours, and educational workshops. Education : Ph.D. in Combinatorial Mathematics (2019), UQAM M.Sc. in Complexité palindromique des mots et des arbres (2016), UQAM Research Interests : Her work explores spectral properties of random walks, combinatorial actions on permutations, and homomesy in dynamical systems. She has contributed to studies on interval-closed sets, toggle groups, and Markov chain mixing times. Her methods bridge algebraic combinatorics with probability theory, often involving eigenvalue analysis and poset theory. Outreach Contributions : Lafrenière co-hosted the French radio show L’oeuf ou la poule , presenting monthly math segments for four years. She co-created Maths in the city walking tours in Montreal, Chicago, and Trois-Rivières, using urban landscapes to illustrate mathematical concepts. For schools, she offers workshops on Braess’s paradox, magic tricks, and mathematical problem-solving, tailored for K-12 audiences. Grants & Collaborations : Supported by the Institut des Sciences Mathématiques, she delivers talks on applied combinatorics (e.g., traffic modeling, relationship optimization). Her collaborations span North America, with co-authors like Joel Brewster Lewis, Jessica Striker, and Rosa Orellana. Labs & Future Work : Her research continues to investigate combinatorial dynamics, particularly homomesy phenomena and eigensystem analysis of shuffle operators. She actively promotes mathematics through accessible public engagement initiatives.

Ulrike Wallrabeمشاهده پروفایل

استاد

• Microsystems Engineering
• Nanotechnology
• Adaptive Optical Systems
• +۴ مورد دیگر

Prof. Ulrike Wallrabe is the Head of the Institute of Microsystems Engineering (IMTEK) at Albert-Ludwigs-University of Freiburg. Her research focuses on microsystems engineering, adaptive optical systems, and energy harvesting technologies. She leads projects such as ECOSENSE, developing distributed sensor networks for environmental monitoring. Her work integrates MEMS, nanotechnology, and wireless power transfer to advance applications in biomedical imaging, renewable energy, and smart materials. Key research interests include cooperative microactuator systems, multistable magnetic actuators, and optomechanical devices. She has pioneered adaptive lenses and prisms for high-resolution microscopy and scanning systems. Her contributions to sensor networks and energy-efficient systems address challenges in environmental science and biomedical engineering. Publications highlight breakthroughs in triboelectric nanogenerators, acoustic wireless power transfer through metal barriers, and real-time light field deconvolution. Her research emphasizes interdisciplinary approaches, combining physics, materials science, and computational modeling to solve complex engineering problems. Affiliations: IMTEK, Albert-Ludwigs-University of Freiburg Notable Projects: ECOSENSE, LivMatS Colloquium series

Dan Johnsonمشاهده پروفایل

استاد

• Cognitive Science
• Data Science
• Creativity Assessment
• +۳ مورد دیگر

Dan Johnson is the David G. Elmes Term Professor of Cognitive and Behavioral Science at Washington and Lee University. He has worked there for 14 years as of 2023, teaching courses like Introduction to Data Science: Mind Analytics and Cognition . His research focuses on computational creativity assessment, leveraging machine learning to evaluate creativity in narratives, STEM education, and interdisciplinary contexts. He developed the Creativity Assessment Platform (CAP) for automated scoring of creative outputs across languages and disciplines. Johnson’s work bridges cognitive science and education technology, with a focus on measuring creativity through semantic analysis, multilingual computing, and educational design. His projects include evaluating poetic creativity, analyzing thematic influences on creative ideas, and understanding how engineering prompts affect student innovation. He emphasizes collaborative learning, stating his courses bring together diverse perspectives to solve complex problems. His research trends highlight interdisciplinary approaches to creativity assessment, with recent work emphasizing AI applications, cultural context analysis, and cross-linguistic methodologies. While no specific awards are listed, his contributions to computational creativity metrics are notable. Johnson also co-founded initiatives like the CAP platform, reflecting his commitment to advancing tools for creativity measurement in academia and industry. His advising and grants history is not detailed here, though his courses suggest active engagement with student research projects. He is affiliated with the Department of Cognitive and Behavioral Science within The College, and his work extends beyond academia through collaborations with tech and educational institutions.

Matti Stenroosمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Applied Physics
• Computational Neuroscience
• +۵ مورد دیگر

Matti Stenroos is a Senior Lecturer at Aalto University's Department of Neuroscience and Biomedical Engineering , where he also serves as Vice Head of the Department . His research focuses on biomedical engineering, neuroimaging, and electromagnetic field applications. Doctoral degree in Engineering and Technology (2008), Helsinki University of Technology Licentiate degree in Engineering and Technology (2005), Helsinki University of Technology Master's degree in Engineering and Technology (2002), Helsinki University of Technology Stenroos specializes in Transcranial Magnetic Stimulation (TMS) , Magnetoencephalography (MEG) , and Electromagnetic Field Modeling . His work improves brain stimulation devices , neural source localization , and biomedical signal analysis , contributing to depression treatment and pain management. Recent articles focus on Pulse-Width Modulation and multi-locus stimulation systems . Stenroos received the IFMBE Young Investigator Competition award in 2005. He has organized international conferences like the Science Factory: TMS-EEG Summer School and participates in editorial activities. As principal investigator for the Device-Independent Real-Time MEG/EEG Source Localization project (2015-2016), he pioneered adaptive neuroimaging techniques. His laboratory collaborates globally on biomedical electromagnetic modeling and clinical neuroengineering applications .

• Evolutionary Algorithms
• Swarm Robotics
• Optimization
• +۳ مورد دیگر

Prof. Ben Paechter is a leading academic at the School of Computing Engineering and the Built Environment , Edinburgh Napier University, specializing in evolutionary algorithms and swarm robotics. As a Professor , he has shaped research directions in computational optimization and adaptive systems for over two decades. Research Themes : Evolutionary Swarm Robotics, Multi-Objective Optimization, Hyper-heuristics, Neural Architecture Search Key Projects : FOCAS (European Commission), KTP: Intelligent Agents (Innovate UK), PerAda (Self-Aware Systems) Collaborations : CAVES Research Group, Centre for Algorithms, Visualisation and Evolving Systems His article trends demonstrate expertise in cross-domain hyper-heuristics, swarm behavior tree evolution, and neural network architecture optimization. Recent works (2023-2024) focus on GPU-accelerated evolutionary algorithms and hierarchical swarm control systems. Scientific Awards : Fellow of the British Computer Society (FBCS) Chartered IT Professional (CITP) GECCO Best Paper Nomination (2018) Advising & Grants : Supervised 5 PhD students including Paul Lapok (planar mechanisms) and Andreas Steyven (swarm diversity). Secured £2.2M+ in funding across 13 projects, including EU FOCAS (£639,999) and Innovate UK grants.

• Collective Intelligence
• Collaboration & Group Processes
• Network Analysis
• +۲ مورد دیگر

Nikolas Zöller is a research scientist at the Max Planck Institute for Human Development 's Adaptive Rationality department. His work focuses on collective intelligence, human-AI collaboration, and computational modeling of social systems. He combines methods from physics, computer science, and psychology to study decision-making processes in both natural and artificial collectives. Ph.D. candidate at Constructor University Bremen (2020-2024) Research Associate at Potsdam University of Applied Sciences (2015-2022) Master of Science in Physics from Freie Universität Berlin (2014) Bachelor of Science in Physics from Freie Universität Berlin (2010) His research spans: Collective intelligence frameworks Human-AI collaborative diagnostics Agent-based modeling of social networks Technological co-diffusion patterns Thermodynamic optimization in physical systems Recent publications highlight his work on: Diagnostic accuracy in human-AI collectives GitHub collaboration topology Affect control theory in group dynamics Co-diffusion of complementary technologies Scientific recognition includes: European Press Prize (2022) as part of a team Springer Best Masters Award (2014)