جست‌وجوی استاد و پژوهشگر

Paul Ralphمشاهده پروفایل

استاد

• Software Engineering
• Empirical Software Engineering
• Human-Computer Interaction
• +۱۷ مورد دیگر

Dr. Paul Ralph is a Professor in the Faculty of Computer Science at Dalhousie University , where he leads the Dalhousie Software Engineering Lab (DalSEL) . His work bridges software engineering, human-computer interaction, and project management, with a focus on empirical research and social sustainability in software development. Education: PhD in Computer Science, University of British Columbia BSc in Computer Science, Memorial University BComm in Business, Memorial University Dr. Ralph's research centers on the sociotechnical aspects of software engineering , particularly how team dynamics, ethics, and human factors influence software success. He rejects pseudoscientific models like Waterfall and SDLC, and avoids AI/ML/data science, instead emphasizing rigorous qualitative and quantitative human-participant studies. His lab is known for its work on socially sustainable software engineering and evidence standards in computing research. His recent publications reflect a strong trend toward methodological rigor, ethical computing, and human-centered practices . Themes include empirical standards, agile methods, requirements engineering, and the social impact of technology. He publishes in top venues like IEEE TSE and ICSE , and has authored over 80 scholarly works. Scientific Awards and Recognition: Award-winning scientist (multiple unspecified awards) Editor-in-Chief, SIGSOFT Empirical Standards for Software Engineering Research Dr. Ralph is actively involved in mentoring and funding graduate students , particularly through external scholarships like NSERC, Killam, and Banting. He prioritizes applicants from underrepresented groups and emphasizes original, non-AI-generated work. His lab offers strong industry connections, professional development, and support for tenure-track aspirations among postdocs. Labs and Research Groups: Dalhousie Software Engineering Lab (DalSEL) : Focuses on empirical, human-centered software engineering research, with active projects in social sustainability and evidence standards.

• Orthodontic Biomechanics
• 3D Craniofacial Imaging
• Ultrasound Imaging
• +۳ مورد دیگر

Paul Major is Professor and Chair of the School of Dentistry, Senior Associate Dean (Dental Affairs), and ACFD Project Lead at the University of Alberta's Faculty of Medicine & Dentistry. He leads the Orthodontic Biomechanics Research Group and co-founded the Inter-disciplinary Airway Research Clinic (I-ARC), driving innovation across dental academia and clinical practice. His educational background includes a Doctorate of Dental Surgery (DDS) from the University of Alberta (1980) followed by MSc and Orthodontic Specialty training at the same institution (1988). He joined the academic staff in 1989 and served as Director of the TMD/Orofacial Pain Program (1991-2001) and Orthodontic Graduate Program (2001-2010). Dr. Major's research centers on Orthodontic Biomechanics , 3D Craniofacial Imaging , and Ultrasound Imaging . His Orthodontic Biomechanics Research Group developed the OSIM system for 3D force measurement on dental appliances, while his imaging work pioneers reconstruction of craniofacial structures and periodontal ultrasound diagnostics. Through the I-ARC, he leads interdisciplinary studies on pediatric sleep-disordered breathing, examining craniofacial morphology and orthodontic interventions. Analysis of his 190+ publications reveals consistent innovation in biomechanical analysis of orthodontic appliances, machine learning for dental image processing, and hydrogel development for intraoral imaging. Recent work bridges dentistry with engineering through projects on dental aerosols, clear aligner mechanics, and airway measurement software. Dr. Major has supervised over 75 graduate students while maintaining clinical teaching duties despite administrative leadership roles. His research is supported by grants enabling the OSIM system development and interdisciplinary I-ARC projects. He directs the Orthodontic Biomechanics Research Group's experimental biomechanics work and the I-ARC's clinical research team, which integrates pediatric ENT, pulmonology, radiology, and biomedical engineering specialists to advance treatment of pediatric sleep apnea through craniofacial analysis and innovative imaging techniques.

• Earthquake Geology
• Tectonic Geomorphology
• Structural Geology
• +۳ مورد دیگر

Ramon Arrowsmith is a Professor at Arizona State University's School of Earth and Space Exploration (SESE). His research focuses on earthquake geology, tectonic geomorphology, and active faulting, with a particular emphasis on leveraging high-resolution topography through initiatives like OpenTopography. He has over 35 years of experience in paleoseismology, geomorphic mapping, and fault zone analysis. Arrowsmith has held administrative roles such as Deputy Director of SESE and associate directorships in graduate studies and geological sciences departments. His work integrates remote sensing, lidar technology, and robotics to address geological hazards and landscape evolution. Key projects include the QUAKES mission for topographic data collection and the development of low-cost seismic tools like ShakeBot. His research spans global regions, including the San Andreas Fault, Pamir-Tien Shan collision zone, and volcanic fields in Arizona and Mexico. Arrowsmith's recent publications highlight advancements in fault slip modeling, seismic hazard assessment, and open-access geospatial data platforms. His contributions to education include courses on field geology and computational methods in earth sciences. Collaborations with international teams and interdisciplinary projects underscore his commitment to advancing geoscience through innovation and accessibility.

• Fault-Tolerant Computing
• Storage Systems
• Erasure Coding
• +۳ مورد دیگر

James S. Plank is a Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee. He holds a PhD from Princeton University (1993) and has been at UT since 1993. His research focuses on fault-tolerant computing, erasure coding, distributed systems, and neuromorphic computing. He teaches programming courses from introductory to graduate levels and has won multiple teaching awards, including seven departmental awards, the College of Arts and Sciences Senior Faculty Teaching Award, and the Chancellor’s Citation for Excellence in Teaching. Plank is a member of the IEEE Computer Society and has contributed to open-source software like JGraph and Jerasure. His recent research emphasizes neuromorphic computing systems, including projects like NeuroPong and RISP Neuroprocessor. He collaborates with industry and academia on storage systems, checkpointing, and hardware-software co-design. Plank advises numerous graduate and undergraduate students, evident in his annual summer student gallery. He has secured grants such as the NSF-funded "Ground-roaming autonomous neuromorphic targeter" (2020). His lab, Neuromorphic UT, explores applications in control systems, vision, and robotics. Plank’s contributions to erasure coding and storage reliability include seminal works like the RAID-6 Liberation Code and SD codes for mixed failure modes.

Peter Bishopمشاهده پروفایل

استاد

• Software Reliability
• Software Fault Tolerance
• Design Diversity
• +۱۰ مورد دیگر

Peter Bishop is a Professor at the Centre for Software Reliability, City St George's, University of London, where he holds a joint chair in Systems and Software Dependability with Robin Bloomfield. He is also Chief Scientist at Adelard, part of NCC Group, providing consultancy and research in computer safety and dependability. He holds BSc and MSc degrees in Physics and is a Chartered Engineer and Member of the IET. University: City St George's, University of London School: College of Engineering, Design and Physical Sciences Department: Centre for Software Reliability Academic Rank: Professor Email: p.bishop@citystgeorges.ac.uk Research Interests: Peter Bishop's research spans software fault tolerance, design diversity, software reliability prediction, statistical testing, system safety and security, assurance case methodologies, and their application in industrial contexts including autonomous vehicles and nuclear systems. He has led research for the UK nuclear industry on smart device assessment and participated in European projects on critical control system safety. Publication Trends: His recent publications focus on conservative confidence bounds for software reliability, safety assurance under uncertainty, integration of testing and formal proof, and security-informed safety. A recurring theme is the development of rigorous, evidence-based methods to justify software dependability in safety-critical domains, particularly where operational and test profiles differ or failure data is scarce. Scientific Awards and Recognition: While specific awards are not listed, his long-standing contributions are evident through his professorship, leadership at Adelard, and active role in safety-critical research. He is a Chartered Engineer and Member of the IET. Advising and Grants: Although specific students are not named, his leadership in major research projects such as DISPO and DIRC (2000–2006) indicates significant supervisory and mentoring roles. He has secured funding from sources including the Leverhulme Trust (UnCoDe project) and a consortium of nuclear industry stakeholders (EDF Energy, NDA, AWE, etc.) under the CINIF Nuclear Research Programme. Labs and Research Teams: He is a key member of the Centre for Software Reliability at City St George's and leads research activities at Adelard. He collaborates extensively with Robin Bloomfield, Lorenzo Strigini, Bev Littlewood, and others on software dependability and safety assurance research.

• Security Engineering
• Privacy Enhancing Technologies
• Cryptography
• +۳ مورد دیگر

Professor Steven J. Murdoch is a faculty member at the University College London (UCL) in the Department of Computer Science . He holds a Royal Society University Research Fellow position and leads the Information Security Research Group . He is affiliated with Christ’s College as a bye-fellow, and is a Fellow of the Institution of Engineering and Technology (IET) and the BCS . His work bridges security engineering , privacy-enhancing technologies , and legal-technical intersections . Academic Leadership : Program chair and general chair for major conferences like Privacy Enhancing Technologies Symposium and Financial Cryptography . Research Contributions : Notable for exposing vulnerabilities in EMV protocols , designing blockchain-based fair exchange protocols , and analyzing malware delivery ecosystems . Scientific Awards : Received the IRTF Applied Networking Research Prize 2020 for internet-wide scanning methodologies. Professional Impact : Active in Tor Project and critical infrastructure analysis, including the Post Office Horizon scandal . Email: s.murdoch@ucl.ac.uk .

Hye-Chung Kumمشاهده پروفایل

استاد

• Health Informatics
• Data Science
• Privacy-Preserving Record Linkage
• +۴ مورد دیگر

Hye-Chung Kum is a Professor in the Department of Health Policy & Management at Texas A&M University, where she pioneers Population Informatics to transform digital data into evidence-based health policy solutions. Her work bridges computer science, public health, and social work to address critical data challenges in healthcare systems. Education: PhD, University of North Carolina at Chapel Hill (UNC-CH), 2004 MSW (Master of Social Work), UNC-CH, School of Social Work, 1998 MS, UNC-CH, Department of Computer Science, 1997 BS, Yonsei University, Seoul, Korea, Department of Computer Science, 1995 Research Vision: Dr. Kum develops privacy-preserving human-computer hybrid systems for cleaning and integrating chaotic real-world data (e.g., EHRs, administrative records). Her Population Informatics framework enables ethical large-scale analysis while addressing data genocide in marginalized communities through innovations like the Secure Decoupled Linkage (SDLink) system. Publication Trends: Recent work (2024-2025) reveals three dominant threads: (1) Mental health service utilization dynamics during/post-pandemic, (2) Racial/ethnic disparities in emergency department use and cancer outcomes, and (3) Ethical data sharing frameworks for vulnerable populations. Her Texas-focused studies on Medicaid payment models and AI-driven record linkage demonstrate practical policy applications. Research Infrastructure: As director of the Population Informatics Lab, she leads cross-disciplinary teams developing Privacy-by-Design tools that balance public health needs with data sovereignty—particularly for American Indian and Alaska Native communities. Her grant-funded work consistently addresses Medicaid transformation and healthcare cost drivers through secondary data analytics.

• Earth Physics
• Applied Geophysics
• Paleomagnetism
• +۳ مورد دیگر

Prof. Turgay İşseven is a Professor at the Department of Geophysical Engineering, Faculty of Mining, Istanbul Technical University. He holds a PhD in Geophysical Engineering from the same institution. His primary research interests include Earth Physics, Applied Geophysics, and Paleomagnetism, with a focus on tectonic evolution, volcanic rock analysis, and gravity modeling in regions like Eastern Anatolia and Thrace Basin. He has led multiple projects funded by TÜBİTAK and BAP, investigating topics such as the paleomagnetic properties of volcanic rocks and the structural analysis of sedimentary basins. Prof. İşseven has advised numerous graduate students and contributed to over 20 publications in peer-reviewed journals. His work integrates advanced geophysical techniques like Ground Penetrating Radar (GPR) and deep learning for subsurface imaging and object detection. Key projects include the investigation of Lake Van's volcanic formations and the development of software for gravity data processing. He is also involved in teaching courses on Geomagnetism and Paleomagnetism. Educational Background: PhD in Geophysical Engineering, Istanbul Technical University (2001) MSc in Geophysical Engineering, Istanbul Technical University (1995) BSc in Geophysical Engineering, Istanbul Technical University (1991) Research Interests: Gravity anomalies and structural modeling Paleomagnetic studies of volcanic rocks Geophysical exploration techniques (GPR, resistivity) Tectonic evolution of Anatolia and the Eastern Mediterranean Projects: Investigation of Miocene-Quaternary volcanic rocks in Lake Van using paleomagnetic methods Gravity modeling of sedimentary basins in Eastern Anatolia Development of GravPack, a MATLAB-based gravity data processing tool Advising and Labs: Advisor to 7+ graduate students (e.g., Nedim Aydın, Orhan Apaydın) Collaborations with institutions like the Eurasian Geosciences Institute His research contributes to UN Sustainable Development Goals related to climate action and sustainable cities, through studies on earthquake hazard mitigation and geological resource management.

Emilia Mendesمشاهده پروفایل

استاد

• Software Engineering
• Empirical Software Engineering
• Human-Centric Software Engineering
• +۱۲ مورد دیگر

Emilia Mendes is a Full Professor in the Department of Electrical and Computer Engineering at Aarhus University . Her research focuses on Empirical Software Engineering , particularly human-centric approaches, evidence-based decision-making, and the application of machine learning and statistical techniques in software development. Current research themes: Human-Centric Software Engineering, Evidence-Based Research, Statistical/Machine-Learning Techniques, and Value-Based Software Engineering. Developed tools for team climate forecasting, capability measurement, and value-based decision-making. Research Trends: Her work bridges software engineering with psychology (personality traits, team dynamics), machine learning (effort estimation, dementia prognosis), and value-based frameworks for decision-making. She emphasizes industrial applications, including agile methodologies, cross-company predictions, and Bayesian network modeling. Scientific Impact & Awards: 10,018 citations, h-index 58. Ranked #32 in Empirical Software Engineering Scholars (Google Scholar). Ranked #20 in Top Computer Science Scientists in Sweden (2023). Top 2% scientist in the world (2019, 2020, 2022; only female in Sweden for SE in 2022. Nine best paper awards at international conferences. Editorial board member: Information and Software Technology , ACM Computing Surveys , former roles at IEEE Transactions on Software Engineering and others. Grants & Leadership: Awarded €11.921.603 in research grants. Held leadership roles as General Chair (EASE 2017), PC Co-Chair (EASE 2012, ESEM 2012), and active participant in 200+ academic events.

Manos Athanassoulisمشاهده پروفایل

دانشیار

• Data Systems
• Cloud Data Management
• Database Systems
• +۷ مورد دیگر

Manos Athanassoulis is an Associate Professor in the Department of Computer Science at the College of Arts and Sciences, Boston University. He is the Founder and Director of the BU Data-intensive Systems and Computing (DiSC) lab and a member of the BU MiDAS group. His research focuses on data systems, particularly cloud data management, hybrid transactional/analytical workloads, and integration with emerging hardware such as non-volatile memory and heterogeneous computing. His educational background includes a PhD from EPFL (2014), an MSc in Computer Systems Technology, and a BSc in Informatics and Telecommunications from the University of Athens, Greece. Prior to BU, he was a Postdoctoral Researcher and Research Associate at Harvard University, supported by a SNSF Postdoc Mobility Fellowship. His research interests span data systems, database architectures, LSM trees, indexing, storage systems, and performance optimization. He explores how novel hardware can be leveraged to improve data management efficiency and scalability, especially in cloud environments. His recent publications (2021–2025) predominantly focus on LSM trees, covering topics such as compaction policies, Bloom filter tuning, DPU offloading, adversarial resilience, and sustainable caching. Earlier works include foundational contributions on access methods (RUM Conjecture) and optimal key-value stores (Monkey). The trend shows a consistent focus on data system efficiency, adaptability, and robustness under varying workloads and hardware constraints. Scientific Awards: NSF CAREER Award (2022) Facebook Faculty Research Award (2020) NSF CRII Award (2019) Best of VLDB 2017 and Best of SIGMOD 2017 SIGMOD Most Reproducible Paper Award (2017) Multiple ACM SIGMOD Distinguished PC Member recognitions (2018–2025) VLDB 2023 Best Demo Award RedHat Collaboratory Research Incubation Awards (multiple, 2021–2023) SNSF Postdoc Mobility Fellowship (2015–16) IBM PhD Fellowship (2011–12) Dr. Athanassoulis has advised numerous students and collaborators, evident from his co-authorship on works with researchers such as Niv Dayan, Stratos Idreos, and A. Ailamaki. His grants include major awards from NSF, Facebook, and RedHat, supporting research in robust data systems, hardware-software co-design, and learned cost models. He has also been recognized for teaching excellence at Harvard University. He leads the DiSC lab at Boston University, which focuses on data-intensive computing and systems research. The lab explores next-generation data architectures, particularly in cloud and hardware-aware environments. Collaborations with the BU MiDAS group enhance interdisciplinary research in data science and AI.

• Software Quality
• Quantum Computing
• Information Systems
• +۵ مورد دیگر

Mario Piattini is a Full Professor at the School of Computer Science of the University of Castilla-La Mancha (UCLM) in Spain, where he has served since 2002. He is the founder of the Alarcos research group and has held leadership roles including Director of the Mixed Center for Software Research and Development UCLM-Indra and Director of the Institute of Technologies and Information Systems (ITSI) at UCLM. He has also served as an associate professor at Universidad Complutense and Universidad Carlos III de Madrid. His educational background includes a PhD and degree in Computer Science from Universidad Politécnica de Madrid, a Psychology degree from UNED, and a Doctor Honoris Causa from Universidad de La Plata (Argentina). He holds multiple master's degrees in IT Audit, Human Resources Management, and Project Management, along with professional certifications including CISA, CISM, CRISC, CGEIT, PMP, and data governance certifications from DAMA. Professor Piattini is a leading expert in software quality, information systems, and security, with a recent strong focus on quantum computing and quantum software engineering. His research spans software engineering methodologies, data quality, AI systems, and the emerging field of quantum software development. He has been recognized as one of the top 15 scholars in systems and software engineering (2004-2008) and among the most active software engineering researchers (2010-2017). His recent publications reveal a significant shift toward quantum computing, with numerous articles on quantum software engineering, quantum-classical hybrid systems, quantum testing frameworks, and quantum software architecture. His work bridges theoretical foundations with practical engineering approaches for the emerging quantum computing paradigm. His scientific recognition includes multiple prestigious awards: Premio Nacional a la Trayectoria Profesional del Ingeniero Informático Premio Gabriel Alonso Herrera from JCCM for research trajectory Premio Grace Hooper from COIICLM Premio Aritmel from SCIE Premio FIUM from Universidad de Murcia Premio a la Trayectoria Profesional de ISACA Madrid As an academic leader, Piattini has founded several spinoff companies including Cronos Ibérica (now Alten), Kybele Consulting, Lucentia Lab, DQTeam, AQCLab (the first ENAC-accredited laboratory for software product quality and data evaluation), and I2SC. He serves as secretary of CTN71/SC7 and is a member of various ISO/IEC and UNE standardization committees, contributing significantly to software quality standards development. His research group has established AQCLab, which has been evaluating software quality for 25 years, demonstrating his long-term commitment to practical applications of software engineering research. Through his leadership in both academic and industrial contexts, Piattini has created a robust ecosystem connecting theoretical research with real-world software quality practices.

• Bioinformatics
• Computational Biology
• Pharmaceutical Drug Discovery & Development
• +۱۳ مورد دیگر

Leonard Wesley is an Associate Professor in the Department of Computer Science at the College Of Science, San Jose State University. His research spans interdisciplinary domains at the intersection of Bioinformatics , Computational Biology , and Machine Learning , with specific applications in Pharmaceutical Drug Discovery , Genomic Data Analysis , and Autonomous Robotics . Education: Ph.D. in Computer Science, University of Massachusetts M.S. in Computer Science, University of Massachusetts B.A. in Physics and Math, Northeastern University Research Interests include Approximate Reasoning (probabilistic, evidential, and fuzzy logic), Agent-Oriented Systems , and Sensor Fusion . His work applies these methodologies to Drug Portfolio Management , Protein Structure Scoring , and Medical Diagnostics . Publication Trends show a consistent focus on Computational Biology , Robotics , and Uncertainty Quantification over four decades. Early work in Computer Vision evolved into modern applications in Pharmaceutical Analytics and AI in Aerospace . Key Projects include SVM-based drug affinity prediction, evidence-driven decision support systems for biopharma, and real-time agent development frameworks like ROADS. He has contributed to CFD code control and Mobile Network Congestion solutions. Collaborations with institutions like NASA, Los Alamos National Laboratory, and international conferences (WMSCI, ICINCO, AIAA) highlight his cross-disciplinary impact. His teaching includes Artificial Intelligence and Bioinformatics courses.

• Systematic Review Automation
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Lena Schmidt is a Research Fellow at the University College London (UCL) Social Research Institute , specializing in methods development for systematic reviews , evidence maps , and living evidence syntheses . She leverages machine learning and neural networks to optimize data mining and classification during the screening process. Her work emphasizes automation tools for large-scale literature analysis and addressing reproducibility in evaluations. MSc Applied Health Sciences , Furtwangen University (2018) NIHR Systematic Reviews Fellowship (2018–2020) Predoctoral Fellowship in Living Reviews and Automation Her research focuses on enhancing systematic review efficiency through NLP , AI , and data engineering , particularly for grey literature in health research. Recent publications address pandemic impacts on mental health , automation in evidence synthesis , and knowledge graph development for toxicology. Scientific awards include the NIHR Fellowship and Intelligent and Adaptive Systems Certification from the University of Sussex. She actively collaborates with organizations like the Campbell Collaboration and ICASR , co-organizing automation workshops and contributing to methodological frameworks.

• Applied Statistics
• Optimization
• Data Visualization
• +۷ مورد دیگر

Zhongyuan (Annie) Yu is a Teaching Associate Professor in the Department of Systems and Enterprises at Stevens Institute of Technology. She holds a PhD in Systems Engineering (2014), and two MS degrees in Operations Research (2012) and Industrial Engineering (2010), both from Georgia Institute of Technology. Her research bridges applied statistics, optimization, data visualization, and socio-economic systems analysis. Key focus areas include healthcare systems engineering, defense acquisitions, and interactive decision support systems. She leads software engineering education initiatives, including serving as Program Director for the Software Engineering Program (2022-2024). Yu has secured major grants from DoD DASD(SE) and NIH, focusing on mega-project management, digital engineering integration, and healthcare policy simulations. Her 2023-2024 research explores HIPAA compliance challenges in software engineering and patient trust in electronic health records. Her publications span health informatics, portfolio optimization networks, and systems engineering methodology. Notable works include developing policy flight simulators for healthcare interventions and semantic integration frameworks for digital engineering interoperability. Teaching responsibilities include courses like Agile Methods for Software Development, Data Analysis & Visualization, and Engineering Economics. She advises capstone projects and maintains active roles in curriculum development for systems and software engineering programs.

• Control Theory
• Applied Mathematics
• Computational Mechanics
• +۷ مورد دیگر

Goong Chen is a Professor at Texas A&M University (TAMU) within the College of Arts & Sciences. His research focuses on Control Theory, Applied Mathematics, and interdisciplinary applications in computational mechanics, fluid dynamics, and quantum systems. He holds a Ph.D. from the University of Wisconsin (1977) and a B.S. from National Tsing-Hua University (1972). His research interests span computational biomechanics, forensic modeling, nanofluidics, and mathematical physics. Recent work includes modal analysis of animal motion, crash mechanics of aircraft, and forensic reconstruction of disasters. He has contributed to theoretical advancements in PDEs, nonlinear dynamics, and quantum computing. Chen’s articles address cutting-edge topics like thermoelastic plates, Volterra equations, and DFIM systems. He has pioneered numerical methods for complex systems using OpenFOAM and finite element techniques. His computational models have been applied to real-world scenarios such as submarine implosions and chemical warfare forensics. No academic awards are explicitly listed, but his extensive publication record reflects significant contributions to applied mathematics and engineering. He leads research teams focused on interdisciplinary challenges in computational science and engineering.