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Ulrich BirkelView profile

Professor

• Wireless Communications
• Mobile Networks
• Indoor Positioning Systems
• +5 more

Prof. Dr.-Ing. Ulrich Birkel serves as a Professor of Communication Technology at the Technical University of Central Hesse (THM) within the Department of Electrical Engineering and Information Technology. His office is located at Wiesenstrasse 14, Building A21 Room 3.16 in Gießen, Germany. He has held this position since 2002 and previously served as Dean of the Department from WS05/06 to SoSe 08. His research focuses on Wireless Communications and Mobile Networks , with specialized expertise in Indoor Positioning Systems using leaky coaxial cables, Narrowband IoT technologies, and RF engineering. Key research areas include: Indoor localization techniques using UMTS and WLAN Leaky feeder cable optimization for positioning systems Narrowband IoT protocol development and QoS analysis Wireless acoustic sensor networks for environmental monitoring Multipath propagation mitigation in indoor environments His publication record spans from 2007 to 2022, demonstrating consistent contributions to wireless communications. Recent work (2020-2022) focuses on Narrowband IoT protocols and smart city applications, while earlier research (2009-2012) established foundational work in leaky coaxial cable positioning systems. Publications appear in IEEE journals, Sensors, and Smart Cities, reflecting interdisciplinary work bridging telecommunications engineering and practical IoT applications. He leads several research facilities including: Information and Communication Technology Working Group Laboratory for Radio and Communication Systems Cisco Networking Academy (Computer Networks 1 and 2) IoT Lab (Internet of Things Laboratory)

Fawaz Y AnnazView profile

Associate Professor

• Robotics
• Unmanned Aerial Vehicles
• Control Systems
• +4 more

Dr. Fawaz Y Annaz serves as Reader in Mechatronics at Birmingham City University, leveraging an international research career spanning the UK, Singapore, Japan, Malaysia, and Brunei. His expertise encompasses mechatronics engineering, robotics, and smart actuation systems, with significant contributions to aerospace, energy, and biomedical applications through leadership of the High Integrity System Laboratory and Mechatronics Group. His academic foundation includes: BSc in Electrical and Electronic Engineering (1987, University of East London) focusing on Electromagnetic Vehicle Levitation Control MSc in Engineering of Dynamic Systems (1989) researching Helical and Planar Induction Actuators PhD in Avionics (1996) addressing Architectures Consolidation in High Integrity Multi-Lane Smart Electric Actuators Dr. Annaz's research integrates robotics, control theory, and energy systems with notable emphasis on unmanned aerial vehicles (including swarm systems), microgrid resilience engineering, and electromechanical actuation. His multidisciplinary approach bridges theoretical control systems with practical applications in aerospace actuation, sustainable energy management, and speech production analysis, demonstrating consistent innovation across diverse engineering domains. Analysis of his publication trajectory reveals evolving research priorities: early work (2000-2015) centered on UAV navigation, actuator monitoring, and speech phoneme signatures, while recent publications (2020-2025) show strategic pivot toward AI-driven microgrid resilience, battery life optimization, and advanced UAV control systems—reflecting growing industry demand for sustainable energy solutions and autonomous systems. Scientific recognition includes: Granted European Patent for electromechanical actuator technology Two international patent applications Over 50 peer-reviewed publications Book and book chapters in mechatronics As an educator and research leader, Dr. Annaz has supervised numerous MSc and PhD students while directing international projects including Japanese Ministry of Education collaborations. His research output includes commercialization efforts for patented actuator technologies and development of educational platforms for robotics training. Current focus areas encompass deep reinforcement learning for energy management and swarm UAV systems. His laboratory initiatives include the High Integrity System Laboratory (operating in Japan and Malaysia) specializing in vibration control, active magnetic bearing systems, and artificial heart development, alongside the Malaysia-based Mechatronics Group advancing industrial robotics and unmanned vehicle technologies.

• Programming Language Design
• Software Engineering
• Formal Methods
• +2 more

Dr Jeremy Lawrence Jacob is a Senior Lecturer in the Department of Computer Science at the University of York, where he has been faculty since 1993. His research focuses on the application of mathematical principles to programming language design and software engineering, with particular emphasis on formal methods and automated verification. His educational background includes a BSc in Mathematics from the University of Hull, followed by an MSc in Computation and DPhil from the University of Oxford. With over 10 years of postgraduate research experience prior to joining York, he brings substantial academic depth to his teaching and research. Dr Jacob's research interests center on bridging theoretical mathematics with practical software engineering challenges. His work explores how formal mathematical frameworks can enhance programming language design, improve software reliability, and enable rigorous verification techniques. This interdisciplinary approach connects abstract mathematical concepts with real-world computing problems. His recent publications demonstrate consistent contributions to formal methods (2021), cybersecurity (2015), and virtualization architecture (2014), showing an evolving trajectory from foundational programming theory toward security-critical systems. The research exhibits strong methodological continuity through mathematical rigor while adapting to contemporary computing challenges. As a member of the Automated Software Engineering research group, he contributes to York's collaborative research environment. His supervisory record includes documented graduate student mentorship through two supervised research projects, though specific student names and details are not publicly listed in available sources. Based in office CSE/043 at Deramore Lane, York, he maintains active research engagement as evidenced by recent publications and his ORCID profile (0000-0003-4806-7426), which catalogs 59 total research outputs including articles, conference papers, and other scholarly contributions.

Joseph NeseView profile

Associate Professor

• Educational Assessment
• Reading Fluency
• Special Education
• +4 more

Joseph Nese serves as a Research Associate Professor in the Department of Education Policy and Leadership at the University of Oregon's College of Education, focusing on data-driven educational interventions and assessment systems to improve student outcomes through evidence-based decision-making. His academic credentials include: Ph.D. in School Psychology, University of Maryland, College Park (2009) M.A. in School Psychology, University of Maryland, College Park (2006) B.A. in Psychology (minor in English), University of California, Santa Barbara (2002) Nese's research integrates psychometrics, statistics, and computer science to bridge assessment and intervention. He pioneered the Computerized Oral Reading Evaluation (CORE) system and the Inclusive Skill-building Learning Approach (ISLA) as alternatives to exclusionary discipline, emphasizing practical tools for educators. Recent work leverages R programming for open science and reproducible research in educational data science. His 60+ publications demonstrate an evolution from foundational assessment validity studies toward AI-enhanced oral reading fluency measurement (using speech recognition and deep learning) and equity-focused discipline interventions, reflecting growing interdisciplinary collaboration across reading education, behavioral science, and computer engineering. Award recognition includes: Institute of Education Sciences Postdoctoral Research Fellowship Nese has secured $3 million in federal funding as PI/Co-PI for projects including CORE (R305A140203) and ISLA (R305A180006). He actively mentors graduate students in research design, statistical analysis, and scholarly publication through hands-on project involvement. His work operates through integrated collaborations with experts in reading instruction, special education, psychometrics, and behavioral outcomes, primarily centered at the University of Oregon's Behavioral Research and Teaching unit.

• Electronics Technology
• Automation Engineering
• Industrial Process Supervision
• +5 more

Joaquín Moreno Marchal is a full Professor at the University of Cádiz in the Department of Automation, Electronics, Architecture and Computer Networks Engineering , specializing in Electronics Technology . His career integrates technical depth in industrial supervision systems with a strong commitment to fostering creativity and innovation in engineering education and practice. Education: Ph.D. in Engineering, University of Seville, 1993. Thesis: Qualitative supervision techniques applied to marine engines , supervised by Dr. Eduardo Fernández Camacho. Research Interests: Professor Moreno Marchal’s research bridges two major domains: (1) qualitative supervision and intelligent monitoring of complex industrial processes—particularly marine engines and turbocharger systems—using expert systems and qualitative simulation; and (2) creativity and innovation management in engineering, encompassing methodologies, organizational systems, interdisciplinary collaboration between arts and humanities, and the design of educational experiences that cultivate innovative mindsets. His work has continuously evolved from foundational studies on knowledge representation for supervision tasks in the 1990s to contemporary explorations of how innovation ecosystems and cultural factors shape engineering creativity. Publication Trends: Across four decades, his scholarly output demonstrates a clear transition from deeply technical studies on qualitative process supervision (early 1990s) toward broader investigations of innovation systems, creative engineering methods, and educational reform (post-2000). Notably, 2017 alone saw five major contributions concentrating on creativity and innovation theory, comparative national innovation systems, and practical handbooks, evidencing a mature research agenda aimed at systematizing and disseminating innovation practices within engineering communities. Awards & Recognition: No specific awards are mentioned in the provided text. Advising & Grants: While the text does not list individual students or funded projects, his extensive authorship of theses-related sections and long-standing professorial role imply significant graduate supervision activity; however, no explicit names or grant details are supplied. Labs & Teams: The text does not specify research laboratories or collaborative teams; affiliations are anchored within the University of Cádiz Department named above.

Frazier BindeleView profile

Associate Professor

• Nonparametric Statistics
• Robust Estimation
• Robust Testing
• +4 more

Frazier Bindele serves as an Associate Professor in the Department of Mathematics and Statistics at the University of South Alabama's College of Arts and Sciences. His academic profile centers on developing advanced statistical methodologies with practical applications across diverse research domains. His educational foundation includes: Ph.D. in Statistics from Auburn University (2012) MS Diploma in Mathematics from the International Centre for Theoretical Physics (ICTP) (2007) M.S. in Mathematics from Marien Ngouabi University (2004) B.S. in Mathematics from Marien Ngouabi University (2003) Dr. Bindele's research specializes in Nonparametric Statistics and Robust Estimation, with particular emphasis on rank-based and signed-rank methodologies. He develops innovative approaches for regression models under complex data scenarios, especially those involving missing responses and covariates. His work bridges theoretical rigor with practical implementation, addressing challenges in single-index models, varying coefficient frameworks, and functional linear modeling where traditional methods fail under non-ideal conditions. Analysis of his publication trajectory reveals a concentrated focus on robust statistical inference for missing data problems (both MAR and MNAR mechanisms), with significant contributions to distribution theory through novel distribution families. His recent work demonstrates increasing sophistication in handling high-dimensional settings and developing computationally efficient algorithms for real-world data analysis, while maintaining theoretical guarantees of robustness.

Mehdi Amiri DarehbidiView profile

Assistant Professor

• Materials Science
• Additive Manufacturing
• Corrosion Engineering
• +3 more

Mehdi Amiri Darehbidi serves as an Assistant Professor in the Mechanical Engineering Department at George Mason University since Spring 2019, where he trains future engineers while advancing materials research. His academic foundation includes a PhD in Mechanical Engineering from Louisiana State University and postdoctoral research at the University of Maryland. Research Focus: Dr. Amiri investigates structural materials' behavior under operational conditions, emphasizing microstructure-performance relationships in engineering alloys and high entropy alloys (HEAs). His work spans additive manufacturing processes, corrosion-fatigue interactions, and multiphysics simulation frameworks. Key themes include defect analysis in additively manufactured components, environmental degradation mechanisms, and predictive modeling of material failure. Recent publications (2023-2025) reveal concentrated efforts on additively manufactured alloys, particularly stainless steel 304L, Haynes 233, and Inconel 718. Research trends show increasing integration of computational methods—probabilistic modeling, machine learning, and multiphysics simulations—with experimental validation for corrosion prediction, fatigue life assessment, and process optimization. Naval applications and automotive corrosion dominate applied contexts. Scientific Recognition: While no major awards are documented, his research secured competitive funding from DoD STTR and AFRL programs. Research Leadership: Dr. Amiri directs the RMF Lab (Reliability, Materials, and Fatigue Laboratory), focusing on: DoD-funded quenching process optimization for large forgings AFRL-supported multiphysics frameworks for metal additive manufacturing Defect-corrosion relationships in additively manufactured alloys Micro-fatigue testing for naval applications His mentoring extends to capstone design projects building naval workforce capabilities. Laboratory Infrastructure: The RMF Lab combines in-situ SEM fatigue testing, electrochemical corrosion analysis, and computational modeling to address material degradation challenges in extreme environments.

• Behaviorism
• Pragmatism
• Behavior Regulation Theory
• +5 more

Kenneth Jacobs is an Assistant Professor in the Department of Psychology at Salem State University . He serves as the Graduate Program Coordinator for the Master of Science in Behavior Analysis Program and leads the Interbehavioral Regulation Lab (IRL) , focusing on behavioral equilibrium, regulation, and the application of experimental and quantitative methods. Ph.D. in Psychology, University of Nevada, Reno Dr. Jacobs’ research centers on behaviorism as a philosophy of science , pragmatism , and behavior regulation theory . His work explores how individuals regulate behavior to maintain preferred activity distributions, termed the "behavioral bliss point," and investigates the effects of disequilibrium on decision-making, social media use, and educational interventions. His recent publications analyze response disequilibrium in social media contexts (2024), replicability in behavioral research (2023), and pragmatic truth theories in behavioral sciences (2020). The IRL employs tools like PsychoPy , GitLab , and OSF for experimental design, coding, and data sharing.

Matthew SalganikView profile

Professor

• Social Networks
• Computational Social Science
• Network-based Statistical Methods
• +4 more

Matthew Salganik is the Alexander Stewart 1886 Professor of Sociology at Princeton University, with affiliations to the Center for Information Technology Policy, Office for Population Research, Center for Health and Wellbeing, and Center for Statistics and Machine Learning. His research bridges computational social science, social networks, and digital methodology, focusing on network-based statistical approaches for studying at-risk populations and innovative web-based data collection techniques. Ph.D. in Sociology from Columbia University (2007) Former Visiting Professor at Cornell Tech and Senior Researcher at Microsoft Research Research interests span computational social science, social network analysis, digital data collection, and the predictability of life outcomes. He explores intersections between technology and society through projects like the Fragile Families Challenge and the development of open-source tools like the Open Review Toolkit. His work has been featured in Science , Nature , and PNAS , addressing issues in algorithmic accountability, digital epidemiology, and reproducibility. Award-winning author of Bit by Bit: Social Research in the Digital Age , which has received multiple translations and honors including the PROSE Award and AAPOR Book Award. His research has been funded by the National Science Foundation, National Institutes of Health, UNAIDS, Sloan Foundation, and tech companies like Facebook and Google. Scientific awards: Outstanding Article Award (ASA), Outstanding Statistical Application Award (ASA), Leo Goodman Award, William Ogburn Mid-Career Award Teaching accolades: Princeton's commendation for outstanding teaching in computational social science Collaborates with interdisciplinary teams across technology policy, AI ethics, and public health. Leads initiatives like the Summer Institute in Computational Social Science, fostering cross-disciplinary methodological training.

Bartolome Jesus Almagro TorresView profile

Professor

• Motivation in Physical Education
• Sports Psychology
• Basketball Training Methodologies
• +5 more

Bartolome Jesus Almagro Torres is a University Professor at the University of Huelva's Faculty of Education, Psychology and Sports Sciences, specializing in the Department of Integrated Didactics with research focus on Didactics of Body Expression. His work bridges physical education, sports psychology, and motor skills development within the Research Center on Contemporary Thought and Innovation for Social Development. He earned his PhD from the University of Huelva in 2012 with the thesis "Motivational factors related to adherence to competitive sports practice in adolescents," supervised by Dr. Pedro Sáenz-López Buñuel and Dr. Juan Antonio Moreno Murcia. His academic foundation centers on understanding psychological mechanisms in sports participation and educational contexts. Dr. Almagro Torres' research investigates motivational dynamics in physical education through Self-Determination Theory, examining how psychological needs, emotional climates, and leadership styles influence physical activity adherence. His work emphasizes gender differences in sports psychology, basketball-specific training methodologies , and emotional climate assessment in educational settings. Recent studies focus on change of direction speed metrics, AI-powered performance assessment, and novelty-seeking behavior in student engagement. Analysis of his 2024-2025 publications reveals consistent focus on quantitative assessment of psychological variables in sports education, with methodological emphasis on observational tools, validation studies, and sport-specific interventions. His basketball research examines position-specific requirements while his educational work develops practical frameworks for improving classroom motivation and emotional climates. No scientific awards were documented in the source material Information about academic advising and research grants was not provided He actively contributes to the HUM643 research group "EDUCATION, MOTOR SKILLS AND ONUBENSE RESEARCH," developing tools like the Emotional Climate Observation (OCE) instrument while investigating practical applications for improving physical activity levels in vocational training and school settings.

• Formal Methods
• Model Checking
• Satisfiability (SAT) Solving
• +4 more

Tommi Junttila serves as a Senior University Lecturer in the Department of Computer Science at Aalto University, Finland, where he conducts cutting-edge research at the intersection of formal methods and computational logic. His academic profile demonstrates sustained contributions to theoretical computer science with practical applications in system verification and blockchain technology. His research program centers on advancing formal verification techniques, with core expertise in: Symmetry reduction algorithms for state space explosion SAT/SMT solving with specialized parity and XOR reasoning Bounded model checking of timed and asynchronous systems Blockchain protocol verification (notably DeFi lending pools) Canonical labeling tools for graph automorphism detection Recent work shows increasing focus on decentralized finance applications while maintaining foundational contributions to solver technology. Analysis of his publication trajectory (2011-2022) reveals consistent innovation in SAT solving methodologies, with symmetry reduction and parity reasoning forming persistent research threads. His 2022 work on DeFi lending pools represents a strategic expansion into blockchain verification, leveraging established formal methods expertise for emerging financial technologies. Tool development (bliss, PySMT) demonstrates commitment to practical research impact. No scientific awards were documented in the source materials. Similarly, no information regarding student supervision, grant funding, or laboratory affiliations was present in the provided text. His independent tool development (including bliss for graph canonical labeling and PySMT for SMT solver interfaces) indicates significant technical leadership within the formal methods community.

Molly AtkinsonView profile

Assistant Professor

• Chemistry Education Research
• Student Understanding of Chemistry Representations
• Assessment Instrument Development
• +3 more

Dr. Molly Atkinson serves as an Assistant Professor in the Department of Chemistry at the University of North Texas (UNT), specializing in Chemistry Education Research (CER). She joined UNT in August 2020 following a postdoctoral fellowship at Miami University (2019-2020). Her academic credentials include: B.S. in Chemistry and Biology from Piedmont College (2012) Ph.D. in Chemistry from the University of Georgia (2018) Postdoctoral Research Fellowship at Miami University (2019-2020) Dr. Atkinson's research employs mixed-methods approaches to investigate chemistry learning across three core domains: Student comprehension of chemical representations (molecular structures, spectra) Design and validation of assessment instruments STEM identity formation and affective factors in chemistry education This work drives evidence-based instructional innovations for undergraduate and graduate chemistry curricula. Her publication trajectory (2018-2025) reveals expanding focus on assessment validity, spectroscopy reasoning, and identity studies, featuring novel educational tools like Quantimon and SymmSpec alongside longitudinal attitude analyses. The Atkinson Research Group secures significant funding from the Alfred P. Sloan Foundation (Grant #G-2022-19496) and National Science Foundation (Grants #CHE-1757946, #CHE-2447861), supporting graduate and undergraduate researchers in chemistry education. Her laboratory integrates qualitative and quantitative methodologies to explore chemistry cognition, maintaining active collaborations across institutional boundaries through multi-institutional studies.

• Science Education
• Chemistry Education
• Educational Technology
• +4 more

Sibel SADİ YILMAZ serves as an Assistant Professor in the Basic Education Department at Kafkas University's Faculty of Education, where she has held a full-time academic position since 2014. Her academic foundation includes a PhD in Chemistry Education from Atatürk University (2005-2013), two Master's degrees in Chemistry and Chemistry Education from Kafkas University, and a BSc in Chemistry from Atatürk University. PhD: Chemistry Education, Atatürk University (2005-2013) MSc: Chemistry Education (non-thesis), Kafkas University (2003-2005) MSc: Chemistry (thesis), Kafkas University (2001-2003) BSc: Chemistry, Atatürk University (1997-2001) Her research spans science education with particular emphasis on chemistry instruction, educational technology integration, and context-based learning methodologies. Recent work focuses on Web 2.0 tools like Kahoot and Quizlet for formative assessment in online chemistry courses, demonstrating her commitment to adapting teaching methods for digital learning environments. She has investigated curriculum development across multiple educational frameworks including analysis of Turkish chemistry curricula using Bloom's Taxonomy. Her publication trends reveal consistent exploration of practical classroom applications, with recent articles examining technology-enhanced assessment tools, context-based learning approaches, and interdisciplinary connections between science education and regional cultural contexts. The research demonstrates methodological diversity including experimental studies, curriculum analysis, and action research approaches. SADİ YILMAZ has supervised at least one master's thesis and taught numerous courses including General Chemistry, Science Laboratory Applications, Educational Technologies, and Measurement and Evaluation. She has participated in three research projects focusing on historical-cultural education, biodiversity instruction, and context-based chemistry teaching. Her collaborative network includes researchers from multiple Turkish universities with frequent collaborations with Ali Yıldırım and Nail İlhan across various educational research domains.

• Control Systems
• Machine Learning
• Networked Systems
• +3 more

Siva Seetharaman is an Assistant Professor in the Department of Industrial Engineering at Purdue University's College of Engineering, joining the faculty in 2022. His research bridges control theory, machine learning, and networked systems with critical applications in energy infrastructure and transportation electrification. Affiliated with Purdue's top-ranked engineering programs, he focuses on safety-critical control solutions for real-world cyber-physical challenges. His educational trajectory includes a Ph.D. in Electrical Engineering from the University of Notre Dame, followed by postdoctoral research at Texas A&M University. This foundation supports his interdisciplinary approach to complex system dynamics. Dr. Seetharaman's research centers on risk-aware control synthesis for safety-critical systems, with three core thrusts: (1) Developing risk-tunable control barrier functions for human-robot collaboration and autonomous systems; (2) Creating data-driven energy management frameworks for virtual power plants and grid reliability; (3) Advancing distributed learning methods for stability assessment in large-scale networked systems. His work uniquely integrates formal verification techniques with machine learning to address nonlinear dynamics in transportation electrification and decarbonized energy grids. Analysis of his 15 most recent publications (2021–2025) reveals a decisive shift toward causal safety engineering —evident in risk-tunable control barrier functions and sampling-based safe reinforcement learning—and energy-transportation convergence , particularly in electric roadway charging and heavy-duty vehicle grid impacts. Key technical trends include compositional verification of neural networks (ECLipsE), multi-scale energy datasets, and dissipativity-based modeling for nonlinear systems. His work consistently targets real-world deployment challenges in Texas grid case studies and transportation networks. No scientific awards were documented in the provided materials. No student advisement records or grant funding details were included in the source texts. His collaborative publication pattern suggests engagement with interdisciplinary teams across control theory, machine learning, and power systems domains, though specific mentoring activities remain unreported. While no dedicated laboratory is specified, his research on cyber-physical systems, electric roadways, and grid-transportation integration implies active participation in Purdue's energy and transportation research ecosystems. His focus on synthetic Texas case studies indicates strong ties to regional energy infrastructure initiatives.

• Energy Economics
• Energy Policy
• Technology Diffusion Economics
• +5 more

Reinhard Madlener serves as University Professor of Economics, specializing in Energy Economics, at RWTH Aachen University's Faculty of Business and Economics. He directs the Institute for Future Energy Consumer Needs and Behavior (FCN) within the E.ON Energy Research Center and holds the position of Vice-Director of JARA Energy since May 2014. His academic foundation includes studies in Business and Economics at Vienna University of Economics and Business (1987-1994) complemented by Economics training at Vienna's Institute for Advanced Studies (1992-1994), culminating in a PhD in Social and Economic Sciences from WU Vienna in 1996. Professor Madlener's research integrates energy economics with behavioral and ecological dimensions, focusing on technology diffusion dynamics, policy evaluation, and sustainable energy systems. His work bridges theoretical economic frameworks with practical energy transition challenges, emphasizing interdisciplinary approaches to market design and consumer behavior in decarbonizing economies. Analysis of his 2012-2016 publications reveals consistent methodological sophistication through agent-based modeling, spatial econometrics, and stochastic analysis. His research portfolio demonstrates evolving emphasis from foundational energy rebound theory toward applied investigations of renewable integration economics, storage solutions, and policy mechanisms for accelerating clean energy adoption across residential, industrial, and agricultural sectors. As FCN Director, Madlener leads interdisciplinary research on energy consumer behavior within the E.ON ERC framework. His leadership extends to JARA Energy, the strategic collaboration between RWTH Aachen and Forschungszentrum Jülich, where he shapes large-scale energy research initiatives including participation in the upcoming IAEE International Conference 2025 in Paris.