Courage Krah is a PhD Student at Pharos University , affiliated with the School of Management, People and Organisations . His research focuses on Household Food Waste in Ireland , particularly its Environmental and Economic Burdens , under the supervision of Dr. Anushree Priyadarshini and Dr. Paul Hynds. His work involves Quantifying household food waste via cross-sectional surveys Applying optimized Generalised Linear Models (GLMs) for demographic and geographic profiling Assessing greenhouse gas emissions and resource use with OpenLCA and life cycle costing (LCC) Recent publications and presentations highlight his expertise in Environmental and economic assessment of food waste Machine learning for consumer behavior analysis Pest management in agricultural crops He presented at the 52nd Annual Research Conference (UCD, 2024) and the TU Dublin Graduate Research Symposium (2024), and participated in stakeholder discussions at the Towards Halving Food Waste in Europe Conference (Netherlands, 2024).
Pieter-Ewald Share is an Assistant Professor of Geophysics at Oregon State University's College of Earth, Ocean, and Atmospheric Sciences . His research focuses on understanding active fault zones, particularly along the western North American plate boundary, using integrated geophysical methods including seismology, electromagnetism, and geodesy. He combines multi-scale approaches to explore fault zone structures, fluid dynamics, and earthquake hazards. His work includes studies of the San Andreas and San Jacinto faults in California, leveraging innovative techniques like freight train seismic noise and magnetotelluric imaging. Share emphasizes a holistic approach to geohazard assessment, integrating data from diverse sources to improve societal resilience against earthquakes. Before Oregon State, he conducted postdoctoral research at Scripps Institution of Oceanography and earned his PhD from the University of Southern California. His prior industry experience in deep South African mines provided unique insights into fault mechanics and subsurface imaging. Share actively mentors students and collaborates on projects like the Magnetotelluric Investigation of the Salton Trough (MIST) and the CRESCENT velocity model for Cascadia. His research highlights the importance of multi-method geophysical synthesis, aiming to bridge gaps between academic disciplines for comprehensive tectonic understanding. Current efforts include imaging the Pacific Northwest's plate boundary and refining active fault monitoring through anthropogenic seismic sources.
Alan Ager is a Courtesy Faculty member at Oregon State University's College of Forestry, specifically within the Department of Forest Engineering, Resources & Management. His research focuses on wildfire risk management, fuel treatment optimization, and ecological restoration, particularly in Mediterranean and western U.S. landscapes. Research Interests Wildfire risk modeling and mitigation Fuel treatment optimization (linear breaks, mosaic patterns) Landscape-scale ecological restoration Fire transmission dynamics Socio-ecological fire governance Publication Trends Recent works emphasize spatial optimization models for wildfire risk reduction, with applications in Portugal, Greece, and the western U.S. Key themes include cross-boundary fire impacts, erosion control, and integrating fire management with carbon sequestration strategies. Collaborators Works with John Bailey and Woodam Chung on wildfire management and forest restoration projects.
Dr. Ann Smith is a Senior Lecturer in Data Science at the Department of Computer Science, University of Huddersfield. She is affiliated with the Centre for Efficiency and Performance Engineering and the Centre for Autonomous and Intelligent Systems. Her research focuses on statistical inference applied to industrial contexts, condition monitoring for predictive maintenance, and the reduction of input parameters in predictive classifiers. She is also engaged in promoting e-learning in mathematics and contributes to evidence-based healthcare diagnostics. Dr. Smith holds a PhD in Engineering, MSc in Applied Statistics, BSc in Mathematics, and PGCE(FE). She is a Knowledge Exchange Champion at the Isaac Newton Institute (University of Cambridge) and a Fellow of both the Institute of Mathematics and its Applications and the Higher Education Academy. Her educational background includes advanced degrees in mathematics and engineering, complemented by a PGCE in further education. Her international collaborations include visiting lecturer roles at Fuzhou Normal University (China) and Universität Greiswald (Germany). Key research areas include fault detection in mechanical systems, non-linear systems analysis, and autonomous abnormality assessment techniques. She actively participates in industry-focused initiatives like the Analysis for Innovators scheme and European Study Groups for Industry (ESGI). Dr. Smith’s scientific awards include Advanced Data Science Professional status and prestigious fellowships. Her work contributes to the UN Sustainable Development Goals, particularly in advancing quality education and industry innovation. She supervises PhD students and has published widely on topics ranging from coffee brewing optimization to genetic disorders linked to nasal polyps and bronchiectasis. Her recent articles highlight advancements in medical imaging techniques (e.g., PET/CT), fault detection in renewable energy systems, and mathematical modeling of industrial processes. She has delivered invited talks on predictive maintenance and participated in numerous international conferences, showcasing her interdisciplinary impact.
Ming Xiong is a researcher affiliated with Bell Labs , focusing on real-time systems, temporal consistency, and data freshness in embedded environments. His work spans concurrency control protocols, deferrable scheduling algorithms, and wireless communication systems. Key Research Areas: Real-time databases, XML data integration, location management in mobile networks, IoT semantic communication, and wireless channel modeling. Collaborations: Frequent co-authorship with Song Han, Deji Chen, Kam-yiu Lam, Krithi Ramamritham, and Wenfei Fan. His recent publications (2023-2025) emphasize semantic communication for IoT and wireless systems, temporal consistency in cyber-physical systems, and environmental data analysis via remote sensing. While no explicit awards or educational background are listed, his contributions to IEEE journals and conferences highlight expertise in real-time transaction processing and distributed systems.
Eugene Gartland is a Professor in the Department of Mathematical Sciences at Kent State University, affiliated with the Advanced Materials and Liquid Crystal Institute. His research specializes in mathematical modeling of liquid crystals, focusing on electro-optical properties, stability analysis, and computational methods. Research integrates continuum mechanics, numerical analysis, and statistical physics to investigate phenomena like Fréedericksz transitions, director field instabilities, and phase behavior. Theoretical frameworks include Landau-de Gennes theory and variational methods, with applications to display technologies and soft matter systems. Publications demonstrate consistent methodological innovation in liquid crystal modeling, emphasizing numerical algorithms, bifurcation analysis, and experimental validation. Recent work explores electric-field interactions, circuit-coupled systems, and ferrofluid responses.
Paul S. LaFollette, Jr. MD serves as Associate Professor in the Department of Computer and Information Sciences within Temple University's College of Science & Technology. With a unique dual background in medicine and computer science, he has maintained continuous faculty appointment since 1982 (promoted to Associate Professor in 1987) and served as Department Chair from 2002-2005. His current teaching responsibilities include CIS 2168 (Data Structures) as evidenced by active course materials. Education: B.S. in Mathematics, Duke University (1969) M.D., Temple University School of Medicine (1974) LaFollette's research traverses two distinct domains: early biomedical engineering work in ultrasound diagnostics (1970s-1980s) and sustained contributions to theoretical computer science (1990s-2000s). His primary expertise lies in combinatorial algorithms, particularly loopless generation techniques for trees, permutations, and combinatorial structures. Significant secondary interests include program visualization systems for education and medical imaging physics. This dual trajectory reflects his transition from medical practice to computer science academia. His 15 most recent publications reveal a clear evolution from biomedical engineering (1980s-early 1990s) to pure computer science (mid-1990s onward), with nearly all post-1998 work focusing on combinatorial generation algorithms. The overwhelming majority appear in top theoretical computer science venues, demonstrating sustained contributions to discrete mathematics and algorithm design. Medical imaging research continues to inform his approach to visual representation problems. Scientific Recognition: NIH Post-Doctoral Fellowship (1975-1977) LaFollette secured multiple competitive grants including two Ben Franklin Partnership awards ($40,000 each as PI for Advanced Visual Automata Systems I & II) and NIH funding ($39,800 as Senior Investigator for ultrasound artifact research). While no formal advising records appear in source materials, his program visualization research (1998-2000) directly supported classroom instruction through tools like the Visual Interface for C/C++ animation. His departmental leadership as Chair (2002-2005) further demonstrates institutional commitment. Though no dedicated lab is mentioned, his research manifests through collaborative projects with J. Korsh (algorithms) and R. Sangwan (visualization), suggesting a small research group focused on combinatorial generation and educational tools. Current course development indicates ongoing engagement with computer science pedagogy despite his 1947 birth year.
Milan M. Simic is an Assistant Professor at the Faculty of Electronics in Niš, University of Nis, in the Department of Metrology and Measurement Technology. His academic career includes a PhD in Electrical Engineering and Computer Science (2013), a Master's degree in Technical Sciences (2008), and a Bachelor's in Telecommunications (2002), all from the Faculty of Electronics in Niš. His research focuses on power quality measurement, signal generation for instrumentation testing, wireless sensor networks, and harmonic analysis for nonintrusive load monitoring. He has contributed to the development of specialized systems like computer-based power quality signal generators and data acquisition frameworks for metrology validation. His publications emphasize technical innovation in measurement systems, including thermocouple linearization techniques and long-term complex signal generation for disturbance detection. He currently participates in 2 national research projects and has authored/co-authored over 9 peer-reviewed articles in journals like Measurement and Control (SAGE) and the Turkish Journal of Electrical Engineering. Notable contributions include a software-based experimental system using wireless sensor modules and analysis of measurement uncertainty in distributed power quality systems. His work aims to improve accuracy and reliability in electrical measurement technologies.
Stephen L. Olivier is a prominent researcher in high-performance computing at Sandia National Laboratories, with a distinguished publication record spanning nearly two decades. His work focuses on parallel programming models, performance optimization, and energy-efficient computing across diverse architectures including CPUs, GPUs, and FPGAs. Olivier has made significant contributions to OpenMP standards and Kokkos programming model development, collaborating extensively with Department of Energy national laboratories and international research teams. Olivier's research interests center on task parallelism, memory management in distributed systems, and performance portability across heterogeneous architectures. His work addresses critical challenges in exascale computing, including efficient task scheduling for unbalanced workloads, power management in large-scale systems, and optimization of communication patterns. More recently, he has expanded his research into medical imaging applications, applying high-performance computing techniques to tuberculosis detection in rural healthcare settings. Analysis of Olivier's recent publications (2021-2024) reveals a strong focus on practical performance engineering for next-generation computing platforms. His work spans traditional HPC domains while increasingly incorporating data science applications and medical imaging analysis. The research demonstrates consistent innovation in parallel programming models, particularly around OpenMP tasking and Kokkos abstractions, with growing emphasis on energy efficiency and hardware-specific optimizations for emerging architectures. Olivier has maintained a prolific research output with numerous publications in top-tier conferences including SC, IPDPS, and IWOMP. His collaborative work extends across multiple Department of Energy laboratories and international institutions, reflecting the interdisciplinary nature of modern high-performance computing research. While specific grant information isn't detailed in the publication record, his work on DOE systems suggests significant involvement in national supercomputing initiatives.
Shaunna Morrison is an Associate Professor in the Department of Earth and Planetary Sciences at Rutgers University New Brunswick , with a joint affiliation at the Earth and Planets Laboratory of the Carnegie Institution for Science . Her research integrates mineralogy, data science, and planetary science to explore Earth and extraterrestrial mineral systems. She leads the 4D (Deep Time Data-Driven Discovery) Initiative , co-leads the Deep-Time Data Infrastructure (DTDI) , and serves as a NASA CheMin X-ray Diffraction instrument co-investigator on the Mars Science Laboratory mission. Her work focuses on mineralogical signs of life, data-driven approaches to geosphere-biosphere coevolution, and Martian mineralogy via missions like CheMin . She develops advanced analytics and machine learning tools to analyze mineral networks, mineral evolution, and planetary habitability. Key projects include Mineral Evolution Database (MED) , Mineral Informatics , and open-access platforms like Mindat.org . Morrison’s lab at Rutgers welcomes students interested in Earth and planetary sciences, data science, and geochemistry. She advocates for open science, FAIR data principles, and interdisciplinary collaboration to advance understanding of mineral systems across deep time and space.
M. Lisa Manning is the William R. Kenan, Jr. Professor of Physics at Syracuse University , affiliated with the Department of Physics in the College of Arts and Sciences and the BioInspired Institute for Materials and Living Systems . Her research bridges biophysics, soft matter physics, and statistical mechanics. Education: PhD in Physics (2008) and MA in Physics (2005) from the University of California, Santa Barbara; BS (2002) and BA (2002) in Physics and Mathematics from the University of Virginia Research focuses on mechanical properties of biological tissues , rigidity transitions in disordered solids , and nonequilibrium systems . She develops computational and theoretical models to study phenomena like cellular jamming , tissue morphogenesis , and avalanche dynamics in collaboration with experimentalists globally. Recent publications highlight work on vertex models for tissue mechanics , 3D epithelial modeling , and unjamming transitions in glasses. Her studies reveal universal principles in mechanochemical systems and active matter . Awards: APS Fellow (2021) Syracuse University Chancellor’s Citation for Excellence (2022) She has secured over $10M in grants from NSF , NIH , and Simons Foundation , including the NRT-URoL grant (2024-2029) and Cracking the Glass Problem (2016-2024). Her lab collaborates with institutions like University of Pennsylvania , Max Planck Institute , and UCSF .
Prof. Dr. Zekeriya ALTAÇ is a faculty member at Eskişehir Osmangazi University (ESOGU) since 1993, currently serving as Professor in the Department of Mechanical Engineering within the Faculty of Engineering and Architecture. He has held prominent administrative roles, including Chairman of the Mechanical Engineering Department (2012–2021), Vice President of the University (2007–2011), and Member of the Senate representing Engineering disciplines. His expertise spans Nuclear Reactor Design, Computational Fluid Dynamics (CFD), Heat Transfer, and Radiative Heat Transfer. He teaches advanced courses like Computational Fluid Dynamics and Heat Transfer and Numerical Solution of Partial Differential Equations . Research interests focus on numerical methods for solving transport equations, fluid flow dynamics around cylinders, thermal-hydrolics in nuclear reactors, and radiative transfer in participating media. He has authored over 50 peer-reviewed articles, with notable work on synthetic kernel methods for radiative transfer and CFD-based heat transfer analysis. Awards and scientific recognitions are not explicitly listed in the provided texts. Prof. ALTAÇ has advised numerous graduate students through his research on thermal systems design and fluid mechanics. He actively contributes to academic governance, having served on University Boards and International Technical Advisory Committees (e.g., Von Karman Institute for Fluid Dynamics). His publications emphasize innovative numerical approaches for engineering challenges, particularly in energy systems and reactor physics.
Dominic Robson is a Researcher specializing in Earth and Planetary Sciences , with a focus on geomorphology and dune dynamics . His work employs agent-based modeling and mean-field simulations to study barchan dune systems on Mars and Earth. His research interests include: Barchan Swarm Dynamics - Investigating collective behavior in dune systems through computational models Climate Change Impact - Modeling wind variability and its geomorphological consequences Sediment Transport - Analyzing aggregation, fragmentation, and exchange processes in aeolian environments Planetary Geomorphology - Comparing dune dynamics across terrestrial and Martian landscapes His publications demonstrate interdisciplinary trends combining: Earth Science (Mars-Earth comparisons) Mathematical Modeling (dynamic algorithms and analytical calculations) Environmental Physics (sediment-volume interactions)
Dr. Muhammad Hussain is a Research Fellow at The University of Western Australia (UWA) within the School of Psychological Science, affiliated with the Western Australian Centre for Road Safety Research (WACRSR). He holds a PhD from Tsinghua University, a Master's from the University of Engineering and Technology (Taxila, Pakistan), and a Bachelor's in Civil Engineering from the same institution. His expertise spans road safety, autonomous vehicles, traffic modeling, and pavement engineering. Key research areas include cooperative automated driving, road safety in roadwork zones, and driver distraction impacts on traffic flow. He has contributed to 19 peer-reviewed articles and secured grants such as the Austroads Project on driver distraction. His work aligns with UN Sustainable Development Goals, particularly in advancing safe and sustainable transport systems. Education: PhD in Transportation Engineering, Tsinghua University (2021) Masters in Transportation Engineering, UET Taxila (2014) Bachelor in Civil Engineering, UET Taxila (2011) Research Interests: Focuses on road safety innovation, including autonomous vehicle integration, accident analysis, and traffic simulation. His work combines empirical studies with advanced modeling techniques to address modern transportation challenges. Current projects include evaluating lane-change behaviors in roadwork environments and investigating cross-border tourism through economic corridors. Grants & Projects: Principal Investigator in the Austroads Project National Driver Distraction Roadmap: Stage 3 Implementation , focusing on data harmonization strategies to mitigate driver distraction risks. Labs/Teams: Conducts research through the WACRSR, a multidisciplinary center addressing road safety challenges in Australia and globally. Additional Roles: Adjunct Research Fellow at Queensland University of Technology and contributor to international conferences on transportation safety and policy.
Dr. Bregje van der Bolt is an Assistant Professor in Water Management and Climate Change Adaptation at Wageningen University & Research. She specializes in complex systems dynamics and deep uncertainty in climate adaptation planning. Her research integrates qualitative and quantitative methods to analyze interactions between climate, water, and human systems. She employs system dynamics modeling, time series analysis, scenario planning, and co-creation approaches to develop robust adaptation frameworks. Her expertise spans climate change impacts, dynamic systems analysis, resilience engineering, and adaptation pathways. Key projects include the CASTOR initiative (enhancing resilience in river landscapes) and KLIMAP (practical climate adaptation strategies). She teaches courses like Climate Change Studies and Integrated Water Management , supervising MSc theses on topics like socio-ecological systems and adaptive policy design. Her research focuses on predicting tipping points in environmental systems, early warning signals for critical transitions, and spatial adaptation strategies for water and food security. Notable contributions include frameworks for designing climate services and user engagement methods for capacity building. Dr. van der Bolt is involved in interdisciplinary collaborations across environmental science, policy, and engineering. She actively contributes to global discussions on climate resilience and sustainable futures through initiatives like the Empower Sustainable Futures subgroup at Wageningen.
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