جست‌وجوی استاد و پژوهشگر

Changsheng Wuمشاهده پروفایل

استاد

• Wireless Bioelectronics
• Energy Harvesting
• Advanced Manufacturing
• +۴ مورد دیگر

Dr. Changsheng Wu is a Professor at the National University of Singapore (NUS), leading the Lab for Intelligent Sensing, Harvesting and Actuation (LISHA). He holds a Bachelor's from NUS and a PhD from Georgia Tech, with postdoctoral research at Northwestern University. His work focuses on wireless wearables, bioelectronics, energy harvesting, and advanced manufacturing for sustainable solutions. Education: Bachelor in Engineering Science (First Class Honours), NUS PhD in Materials Science and Engineering, Georgia Institute of Technology Postdoctoral Research, Querrey Simpson Institute for Bioelectronics, Northwestern University Research Interests: Wireless bioelectronics for clinical health monitoring Energy harvesting via nanogenerators Soft skin-electronics interfaces using metastructures Programmable materials for adaptive systems Advanced manufacturing techniques for wearable devices Key Achievements: Over 50 publications and 5 patents Recipient of TechConnect 2018 Innovation Award and 56th R&D 100 Award Developed wireless implantable sensors for tissue monitoring and bioresorbable medical devices Teaching: MLE5220: Finite Element Method in Materials MLE5238: Bioelectronics Laboratory: His LISHA lab pioneers innovations in self-powered systems, wearable health monitoring, and biohybrid robots. Current projects include metamaterial-based sensors and sustainable energy conversion materials.

Pedro R. M. Inácioمشاهده پروفایل

دانشیار

• Cybersecurity
• Information Security
• Computer Simulation
• +۷ مورد دیگر

Pedro R. M. Inácio is an Associate Professor at the University of Beira Interior (UBI) , where he teaches information assurance, cybersecurity, and computer simulation courses in undergraduate and graduate programs. He serves as Pro-Rector for the Digital University and Data Protection Officer at UBI, and leads the Cross Cutting Skills Lab and the Network Security research group at Instituto de Telecomunicações. His work bridges academia and industry, including a PhD at Nokia Siemens Networks Portugal.

Gareth Pierceمشاهده پروفایل

استاد

• Robotics
• Non-Destructive Testing & Evaluation (NDT&E)
• Ultrasonics
• +۷ مورد دیگر

Professor Gareth Pierce is a leading academic at the University of Strathclyde, serving as Co-Director of the Centre for Ultrasonic Engineering and Academic Director of the UK Research Centre in Non-Destructive Evaluation (RCNDE). He specializes in robotics, autonomous systems, and non-destructive evaluation (NDT&E), with a focus on structural health monitoring (SHM) and advanced manufacturing. His work integrates robotics, AI, and ultrasonics to address challenges in aerospace, energy, and healthcare sectors. He holds a Spirit Aerosystems/Royal Academy of Engineering Research Chair and leads the £50M SEARCH (Sensor Enabled Automation, Robotics & Control Hub), which spans manufacturing and asset management applications. Education: BSc (Hons) in Pure and Applied Physics from the University of Manchester (1989), PhD in Fibre-Optic Interferometers for Laser-Generated Ultrasound from UMIST (1993). Additional qualifications include City & Guilds certifications in electrical installations and a PGDip in Psychological Wellbeing. Research Priorities Autonomous robotic inspection for manufacturing and asset management Integration of AI/machine learning with NDT&E systems In-process inspection for additive manufacturing and welding Ultrasonic and guided wave technologies for defect detection Key Achievements 2023 Anne Birt Award for NDT innovation Leadership roles in SRPe Robotics & UK HVM Catapult initiatives Over 270 research outputs, 86 projects, and a £50M research portfolio Teaching Course organiser for EE312 (Instrumentation & Microcontrollers) and contributes to advanced systems engineering education. Supervises student projects across engineering disciplines. Labs & Collaborations SEARCH Hub operates from Royal College R2.41 (manufacturing applications) and Technology Innovation Centre TIC 7.14 (asset management). Collaborates with global industry partners like Spirit Aerosystems and Högskolan Väst (Sweden).

Paul Scherzمشاهده پروفایل

استاد

• Moral Theology
• Christian Ethics
• Bioethics
• +۷ مورد دیگر

Paul Scherz is the Our Lady of Guadalupe Professor of Theology at the University of Notre Dame, holding appointments in the Department of Theology within the College of Arts and Letters. His interdisciplinary work bridges theology, science, medicine, and technology, focusing on virtue ethics—particularly Stoic ethics—in moral theology. Dr. Scherz earned a BA in molecular and cell biology from UC Berkeley (2001), a PhD in genetics from Harvard (2005), and completed a postdoctoral fellowship at UCSF. He later obtained an MTS and PhD in moral theology from Notre Dame (2010, 2014). Prior to his current role, he taught at the Catholic University of America and the University of Virginia. His research interests include bioethics (genetic technologies, end-of-life ethics), technology ethics (AI governance, algorithmic risk), and the historical influence of Stoic philosophy on Christian ethics. Notable publications include The Ethics of Precision Medicine (2024) and Tomorrow’s Troubles (2022), exploring risk ethics and algorithmic governance. He co-edits the Encountering Artificial Intelligence series with the Holy See’s Dicastery for Culture. Current projects address AI ethics, particularly virtue ethics frameworks for military AI and the anthropological implications of algorithmic systems. He critiques depersonalization in healthcare AI and advocates for ethical integration of scientific advancements with moral prudence. His work examines intersections between science and theology, including Laudato Si’-inspired ecological ethics and the moral formation of scientists in big data contexts. He has contributed to debates on CRISPR technology, brain death criteria, and the commodification of human tissue in vaccine development.

Luca Sterponeمشاهده پروفایل

استاد

• Reconfigurable computing
• Computer-aided design algorithms
• Fault tolerance and reliability
• +۷ مورد دیگر

Luca Sterpone is a Full Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He serves as Head of the Control and Computer Engineering Department (2023-2027), coordinates the Aerospace and Safety Computing Lab, and is a member of the Academic Senate and Power Electronics Innovation Center (PEIC). His research spans reconfigurable computing, fault tolerance, and radiation effects analysis in electronic systems. Professor since 2021 Department Head (DAUIN) since 2023 Coordinates international collaborations with ESA, AMD Xilinx, NVIDIA, and Thales Alenia Space Develops radiation-hardened FPGA tools (SETA, VERI-Place, PyXEL) 2007 EDAA Outstanding Dissertation Award and 2005 IEEE Best Paper Award Research Focus : Designing radiation-tolerant systems for aerospace, including fault-tolerant AI accelerators, FPGA reliability, and software-based error mitigation. He investigates soft error propagation in nanoscale circuits and develops tools for radiation sensitivity analysis in VLSI. His work integrates hardware-software co-design for mission-critical applications. Awards : EDAA Outstanding Dissertation Award (2007) IEEE European Test Symposium Best Paper (2005) SMACD Best EDA Tool Award (2018) ARC Best Paper candidate (2018) Teaching : He leads courses in Reconfigurable Computing (PhD level), GPU Programming , and Operating Systems . He has formal responsibility for teaching roles across 9 bachelor's and 7 master's years, and mentors multiple PhD students. Collaborations : Coordinates with the European Space Agency (ESA), University of Bielefeld, Universidad de Sevilla, and industrial partners like AMD Xilinx, NVIDIA, and General Motors. He leads projects such as RESCHIP4EU, VEGAS, and TERRAC for radiation-hardened computing solutions.

Jay Ryuمشاهده پروفایل

استاد

• Public Policy and Administration
• Public Budgeting and Finance
• Program Evaluation
• +۷ مورد دیگر

Jay Ryu is a Professor in the Department of Political Science at Ohio University's College of Arts and Sciences, where he also serves as Graduate Director. He is based in Bentley Annex 237 and can be contacted via email at ryu@ohio.edu or by phone at 740-593-1993. Education: Ph.D., Public Administration, University of Georgia, 2003 MPA, George Washington University, 1998 MPA, Seoul National University, 1988 B.A., Political Science, Seoul National University, 1986 Dr. Ryu specializes in public policy and administration, with a strong focus on public budgeting and finance, program evaluation, and fiscal equity. His research increasingly integrates advanced data science techniques such as R, Python, and transformer-based text analysis to study education finance, school aid policies, and monetary policy. He teaches courses in quantitative research methods, policy implementation, taxation, public sector accounting, and financial management in the public sector. His recent scholarly output centers on the impacts of school aid design on efficiency, equity, and student outcomes, with several articles published in journals like Public Budgeting and Finance , Journal of Education Finance , and Public Finance and Management . He has also explored the diminishing effectiveness of U.S. monetary policy and the price puzzle. His working papers reflect a deep engagement with neural network analysis of court cases and longitudinal studies on school funding reforms. Scientific Awards: No awards listed in the provided text. Dr. Ryu is actively involved in research and mentorship, supervising graduate students and contributing to academic discourse through publications and conference presentations. He leads research initiatives analyzing big data in public finance and education policy. While no formal lab or research center is mentioned, his work suggests leadership in data-driven policy analysis within the department.

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Maxime CORDY is a Research Scientist at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) , University of Luxembourg, within the Security, Design and Validation group (SerVal) . He holds a PhD from the University of Namur (Belgium, 2014) and specializes in software engineering, applied artificial intelligence, and cybersecurity. His work focuses on adversarial machine learning, deep learning robustness, and model checking for critical systems. Research interests include adversarial attacks on tabular data , energy system optimization , code understanding models , and software quality assurance . Recent projects address challenges in secure AI deployment, automated test generation, and fault detection in large language models. Publications emphasize empirical studies on adversarial defenses, data augmentation for code models, and energy consumption forecasting. He contributes to tools like Daedalux (variability-aware model checking) and benchmarks like Tabularbench for adversarial robustness evaluation. Current affiliations include leadership within the SerVal group and collaborations on interdisciplinary projects such as MALETSQUE (Machine Learning Techniques for Software Quality Evaluation). His work bridges theoretical computer science with practical applications in energy systems, medical imaging, and space program design.

Torsten Steinhoffمشاهده پروفایل

استاد

• Writing Didactics
• Vocabulary Didactics
• Digital Communication in Education
• +۷ مورد دیگر

Torsten Steinhoff is a Professor of Didactics of the German Language at the Department of Germanic Studies, University of Siegen, Faculty of Arts and Humanities. His research and teaching focus on theoretical, methodological, and empirical aspects of language acquisition and instruction from elementary to university levels. His primary research interests include: Writing didactics (Schreibdidaktik) Vocabulary didactics (Wortschatzdidaktik) Language-specific and disciplinary learning (Sprache im Fach) Digital communication and AI in education Development of complex learning arrangements (Lernarrangements) Steinhoff investigates how digital tools like ChatGPT can be integrated into writing instruction, promoting argumentative writing through structured learning tasks. His recent work (2023–2025) analyzes human-AI collaboration in writing, proposing models such as GPT as Ghost, Partner, or Tutor. He emphasizes a post-digital didactic approach, balancing traditional literacy with digital competencies. His publications reflect a strong trend in digital transformation of writing, multilingual education, and empirical interventions in secondary classrooms. He leads research projects funded by BMBF and MKW NRW, including the "AI Writing Arrangements" project tested in 8th-grade classes. Scientific contributions and collaborations: Co-editor of research handbooks on empirical writing didactics Collaborator with scholars like Nicole Marx, Katrin Lehnen, and Joachim Grabowski Active contributor to journals such as Didaktik Deutsch , BiSS-Journal , and Waxmann publications Hosts a research team at lernarrangements.de He advises on academic language development, text procedures, and vocabulary transfer across modalities and subjects. His lab develops open educational resources (OER) for digital writing and communication, contributing to platforms like Twillo.

Richard Allenمشاهده پروفایل

استاد

• Working Memory
• Long-term Memory
• Forgetting
• +۳ مورد دیگر

Professor Richard Allen holds the position of Professor of Cognitive Psychology at the University of Leeds, School of Psychology. He joined the university in 2008 as a Lecturer, became Associate Professor in 2015, and was promoted to full Professor in 2025. His academic journey includes a BSc and PhD in Psychology from the University of York, followed by postdoctoral research at the University of Bristol and University of York with renowned psychologists Alan Baddeley and Graham Hitch. He is an Associate Editor of Psychonomic Bulletin & Review (2019–2024) and previously served at Memory (2013–2019). He organized the 4th International Conference on Working Memory (2024) and is involved in international memory conferences. His research focuses on memory function across populations, including mechanisms of binding in working memory, attentional control, and aging. Key projects include ESRC-funded work on cognitive ageing and ARC-funded studies on cognitive offloading in children. He leads the Working Memory and Cognition (WoMCog) and Psychology of Ageing at Leeds (PAL) research groups, and his work is supported by grants from ESRC, ARC, and others. He has supervised over 20 PhD students and teaches at all levels in the School of Psychology. Research interests emphasize memory binding, attention-memory interactions, and applications to education/clinical settings. His work explores how information is encoded, maintained, and retrieved across modalities, with a focus on lifespan development and neurodegenerative conditions. Recent studies include detecting long-term forgetting in epilepsy and improving memory strategies for older adults. He has pioneered concepts like 'visuospatial bootstrapping' and 'strategic prioritization' in memory research.

• Natural Language Processing
• Computational Linguistics
• Language Models
• +۳ مورد دیگر

Kentaro Inui is a distinguished researcher at Tohoku University , specializing in Natural Language Processing , Computational Linguistics , and Machine Learning . His work focuses on advancing language model behavior through rigorous empirical analysis, including mechanisms for detokenization , entity identification , and numerical reasoning . Inui has pioneered methods to rectify spurious beliefs in LLMs via unlearning techniques and explored the dynamics of reasoning strategies in neural models. His research addresses chat translation quality through metrics like MQM-Chat and investigates repetition neurons responsible for text generation patterns. Inui also contributes to argumentation analysis with annotation frameworks like LPAttack and develops resources such as COPA-SSE for commonsense reasoning. His work on universal graph-based relation extraction and cross-stitching architectures has established new benchmarks in NLP task performance. Inui's publications span top-tier conferences including ACL , EMNLP , and LREC , often involving collaborations with researchers like Benjamin Heinzerling and Jun Suzuki. His methodological innovations in semi-structured explanation generation , position embedding (e.g., SHAPE), and zero pronoun resolution demonstrate his focus on both theoretical and practical NLP challenges. While no direct awards or student mentorship data appear in the provided corpus, his extensive publication record (over 20 papers between 2021-2025) underscores significant contributions to NLP education tools , knowledge base integration , and dialogue system consistency . Current projects like ReCall mechanisms and numerical property encoding directions highlight his ongoing impact on model interpretability and reasoning accuracy.

Daniel Ventusمشاهده پروفایل

پژوهشگر

• Sexual Health
• Psychology
• Intervention Development
• +۳ مورد دیگر

Daniel Ventus is a Project Leader at Åbo Akademi University's Faculty of Education and Welfare Studies, specializing in interdisciplinary research across Psychology, Sexual Health, and Educational Technology. He leads the Experience Lab Health-related solutions and contributes to EU-funded projects like INTAKT and APOLLO2028 , focusing on academic procrastination interventions and healthcare worker resilience. Key research areas: Premature Ejaculation, High-Intensity Interval Training, Resilience Processes, Educational Robotics, and Mental Health interventions Recipient of the 2024 Best Poster Presentation Award at SWESrii for internet interventions His recent publications (2024-2025) examine: HIIT's impact on ejaculation control Real-time resilience assessment tools LLM-powered language learning systems for vulnerable children Physiological and psychological factors in sexual dysfunction As a peer reviewer for journals including Andrology and Scientific Reports , he contributes to multiple disciplines. Media visibility includes coverage in Finland-Swedish educational initiatives and sexual health research outreach (2018-2025).

Sean Robsonمشاهده پروفایل

استاد

• Military Personnel Policy
• Workforce Development
• Occupational Training
• +۱۳ مورد دیگر

Sean Robson is a Professor of Policy Analysis at the RAND School of Public Policy and a Senior Behavioral/Social Scientist at the RAND Corporation. He serves as Associate Director of the Workforce, Development, and Health Program within RAND Project AIR FORCE, where he leads research on manpower, personnel, training, and readiness issues for the U.S. military. Robson holds a Ph.D. in industrial-organizational psychology from the University of Tulsa and a B.S. from James Madison University. His research expertise lies in the scientific validation of assessment and selection systems, physical and psychological fitness standards, and workforce development in military contexts. His research interests span military education and training, operational readiness, gender integration in the military, workforce diversity, enlisted personnel management, leadership, and competency modeling. He has led numerous projects to establish evidence-based physical fitness tests for Air Force Special Warfare and combat specialties in the Army, and has contributed to reforms in recruiting, classification, and resilience programs. Recent publications highlight a strong trend in applying data science, machine learning, and policy analysis to improve human resource management in the Air Force and Department of Defense. His work increasingly integrates artificial intelligence and optimization models to modernize workforce systems, while maintaining a core focus on human performance, resilience, and readiness. Assessment and selection for special operations Physical and behavioral fitness standards Military workforce development Machine learning in HR STEM talent in defense Robson has made significant contributions through RAND’s research portfolio, with over 37 research publications and multiple expert insights. His scientific work informs high-level defense policy and operational practices, particularly in the U.S. Air Force and Army. He has also advised on diversity initiatives, abuse prevention in training, and energy-sector workforce development. He is actively involved in current defense research, with recent and forthcoming publications in 2024 and 2025, indicating ongoing leadership and scholarly impact. He is based at RAND and can be contacted at Sean_Robson@rand.org.

Remco M. Dijkmanمشاهده پروفایل

استاد

• Business Process Management
• Data-Driven Process Optimization
• Supply Chain Management
• +۳ مورد دیگر

Remco M. Dijkman serves as Full Professor in Information Systems at Eindhoven University of Technology (TU/e), chairing the Information Systems group within the Industrial Engineering and Innovation Sciences school. He additionally holds a Full Professor position at EAISI High Tech Systems and acts as research director for high-tech supply chains at the European Supply Chain Forum—a network of over 50 multinational companies. His research centers on Business Process Management with emphasis on data-driven optimization of business processes. His academic background includes both PhD and Master's degrees in Computer Science from the University of Twente. Publications span Information Systems, Computers in Industry, and Transactions on Software Engineering and Methodology, with over 100 papers and service on the editorial board of Information Systems. He has held visiting positions at New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. Dijkman's research interests focus on detecting, diagnosing, and predicting optimal execution scenarios in business processes, developing mathematical models for quantitative process analysis , and resource assignment optimization . These are primarily applied in transportation logistics and high-tech supply chains, where he investigates data-driven predictions for transport order assignment and supply chain planning. His work bridges artificial intelligence with practical business applications. Recent publications (2024-2025) reveal concentrated efforts in deep reinforcement learning for resource allocation, process pattern discovery, and software library development (GymPN, SimPN). Key trends include predictive process monitoring for healthcare applications, event data enrichment frameworks, and uncertainty handling in logistics planning—demonstrating strong interdisciplinary integration. Scientific recognition includes: Best Demo Award (2019) Best Reviewer Award (2016) Test of Time Award (2019) He has supervised 150 students, including Lotte Vugs who received the Dow Chemical Best OML Master Thesis Award in 2020. Grant leadership spans eight projects: NXTGEN Smart Industry (2023-2030), CollChain (2023-2029), CERTIF-AI (2020-2025), FENIX (2019-2023), and DynaPlex (2021-2024), focusing on digital twins, federated networks, and AI-driven supply chain solutions. Dijkman directs the Information Systems group at TU/e and leads the European Supply Chain Forum's high-tech supply chain research. His work integrates with semiconductor manufacturing and transportation logistics through collaborations with industry partners, while his 2023 invited talks at Technical University of Munich and Humboldt University Berlin highlight his international engagement.

Martin Henzمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Artificial Intelligence
• +۸ مورد دیگر

Martin Henz is an Associate Professor at the National University of Singapore , affiliated with the School of Computing and its Department of Computer Science . His academic journey includes an M.Sc. in Computer Science from Stony Brook University (1993) and a Dr.rer.nat. in Computer Science from Saarland University (1997). He has also worked as a Research Scientist at the German Research Centre for Artificial Intelligence. Research Focus : Scalable Experiential Learning, Systems for Teaching/Learning, AI in Education, Programming Languages, Algorithms, and Constraint Programming. Key Projects : Source Academy (immersive programming environment), Deep Teaching (LMS enhancements), and NUS Seafarers (maritime experiential learning). Publications span education technology, programming languages, and sustainable engineering, with recent works focusing on JavaScript-based pedagogy, automated question generation, and electric vehicle conversions. He supervised Rahul Singhal 's PhD, leading to the educational startup Cerebry, and co-founded Workforce Optimizer Pte Ltd with Alan Sevugan. Awards : NUS Annual Digital Education Award (2021) NUS Annual Teaching Excellence Award (2016/17) Fulbright Scholarship (1990) Startup @ Singapore Champion (2001)

Mourad Zeghalمشاهده پروفایل

استاد

• Geotechnical Engineering
• Soil Mechanics
• Seismic Response Analysis
• +۳ مورد دیگر

Dr. Mourad Zeghal is a Professor in the Department of Civil and Environmental Engineering at Rensselaer Polytechnic Institute (RPI). His research focuses on computational geomechanics, seismic response monitoring, and geotechnical system identification. He leads projects addressing liquefaction mitigation, multiscale modeling of geosystems, and development of advanced computational tools for geotechnical analysis. Dr. Zeghal collaborates with RPI's Center for Network for Earthquake Engineering Simulation (CEES), Scientific Computation Research Center (SCOREC), and Inverse Problems Center (IPRPI). His work emphasizes reducing risks from natural hazards through improved design tools and model validation. Key projects include the Liquefaction Experiments and Analysis Projects (LEAP), which use centrifuge testing and machine learning to analyze soil behavior under seismic loads. Dr. Zeghal's research integrates experimental data with numerical simulations to enhance understanding of soil-structure interaction and lateral spreading during earthquakes. Research Interests: Soil liquefaction, multiscale modeling, inverse problem methods, computational geomechanics Key Collaborations: CEES, SCOREC, IPRPI, and global research networks Focus Areas: Centrifuge testing, model validation, seismic hazard mitigation His recent publications (2023–2025) highlight advancements in quantifying uncertainty in soil response, analyzing LEAP centrifuge experiments, and developing machine learning approaches for model calibration. Dr. Zeghal actively engages with industry and government labs to translate research into practical engineering solutions.