جست‌وجوی استاد و پژوهشگر

• Microelectronics
• Nanotechnology
• Semiconductor Device Reliability
• +۷ مورد دیگر

Daniel M. Dankovic is a Full Professor at the Faculty of Electronics, University of Niš, Serbia, where he also obtained his B.Sc., M.Sc., and Ph.D. degrees. He is affiliated with the Department of Microelectronics and heads both the department and the Laboratory for Practical Teaching in Electronic Components and Microsystems. He is actively involved in national and international research projects and contributes to academic publishing as an assistant editor of Microelectronics Reliability and editor of Facta Universitatis, Series: Electronics and Energetics . Ph.D. in Nanotechnology and Microsystems, Faculty of Electronics, University of Niš (2009) M.Sc. in Microelectronics, Faculty of Electronics, University of Niš (2006) B.Sc. in Electronics and Telecommunications, Faculty of Electronics, University of Niš (2001) His research focuses on the reliability of semiconductor devices, particularly Negative Bias Temperature Instability (NBTI) in p-channel power VDMOSFETs, radiation effects, degradation mechanisms, and microsystem design. He also contributes to engineering education, especially in PCB design and hands-on training. His work bridges theoretical modeling, experimental validation, and practical teaching methodologies. The recent publications (2012–2020) reflect a strong thematic consistency in semiconductor device reliability, with emphasis on NBTI, radiation interactions, and measurement techniques. Additionally, he explores IoT-based smart monitoring systems and innovative approaches in engineering education, demonstrating interdisciplinary engagement across microelectronics, applied physics, and pedagogy. Daniel M. Dankovic holds no explicitly listed scientific awards in the provided text. He advises students through research collaboration, particularly evident in co-authored publications with junior researchers, though no formal list of advisees is provided. He is currently involved in 4 national and 1 international research project, indicating active grant funding and collaborative research. His leadership roles include heading key academic units and organizing major IEEE conferences in the region. He leads the Laboratory for the implementation of practical teaching in the module Electronic Components and Microsystems and the Master's program in Electronics and Microsystems, ensuring integration of research and education in advanced electronics.

Anastasija Collenمشاهده پروفایل

مدرس

• Cybersecurity
• IoT Security
• Automotive Systems Cybersecurity
• +۳ مورد دیگر

Anastasija Collen is a Lecturer at the Research Institute for Statistics and Information Science at the University of Geneva . She holds a Ph.D. from the same institution and specializes in cybersecurity, IoT security, and automotive systems. Her work focuses on developing secure architectures, cryptographic protocols, and regulatory frameworks for connected and automated vehicles. Her research spans Automotive cybersecurity standards and certifications Trust modeling in distributed networks Blockchain applications for IoT security Human-centric risk visualization Data privacy compliance (GDPR) Recent publications emphasize secure automotive systems , including trusted platform modules (TPM), lightweight cryptographic protocols (LOKI-2), and certification roadmaps. She also explores IoT security through frameworks like anomaly-based intrusion detection and blockchain-enhanced defense mechanisms. Collen’s work has been presented at conferences such as IEEE ICCP , ARES , and IEEE EuroS&PW , with over 40 peer-reviewed articles since 2018. She maintains an active presence on ResearchGate and Google Scholar .

Amy Vedderمشاهده پروفایل

مدرس

• Wildlife Conservation
• Biodiversity and Habitat Conservation
• Community Outreach
• +۵ مورد دیگر

Amy Vedder is a Lecturer at the Yale School of the Environment (YSE). She transitioned to academia in 2013 after 35 years in international wildlife and conservation practice. Her expertise spans ecological research, project management, and policy advisory roles across Africa and the U.S. She is renowned for co-launching pioneering ecotourism and community outreach programs in Rwanda and Burundi to protect montane forests and endangered fauna. Education: PhD in Zoology, University of Wisconsin-Madison MSc, University of Wisconsin-Madison B.A. in Biology, Swarthmore College Research Interests: Dr. Vedder focuses on reconciling local, national, and international interests in conservation. Her work emphasizes biodiversity preservation, governance structures, socio-economic integration, and landscape-scale approaches to mitigate threats like oil/gas development and logging. She advocates for monetized and non-monetized valuation of conservation efforts. Professional Experience: Program Director, Wildlife Conservation Society’s Africa Program (21 countries) Senior Technical Advisor, GEF/UNDP (Rwanda National Parks) Senior Vice President, The Wilderness Society (U.S. wilderness conservation) Awards & Publications: African Rain Forest Ecology and Conservation (Yale University Press) In the Kingdom of Gorillas (Simon & Schuster) Dorothy McCluskey Fellow at YSE Teaching & Outreach: Cochairs conservation seminars and leads annual study tours in Rwanda with Dr. Bill Weber. Focuses on practical conservation strategies and policy implementation.

Sam Fetherstonhaughمشاهده پروفایل

پژوهشگر

• Robotics
• Bio-inspired Design
• Computational Geology
• +۳ مورد دیگر

Sam Fetherstonhaugh is a Researcher in the Department of Computer Science at Aberystwyth University, holding a Doctor of Philosophy. His work bridges robotics, computational geology, and bio-inspired design. His research focuses on optimizing robotic systems through insights from fish kinematics and applying machine learning techniques to geological data analysis. Education: Doctor of Philosophy (PhD), Aberystwyth University Research Interests: Bio-inspired robotics, fish motion analysis for robot design, fuzzy logic applications in geology, petroleum reservoir characterization through well log analysis. He explores how biological systems' principles can enhance robotic locomotion and autonomous decision-making. Publications: Recent work includes advancing lithology classification using fuzzy inference systems and developing segmentation algorithms for fish midlines to improve robotic efficiency. His studies suggest unified control strategies for carangiform swimming could revolutionize underwater robotics. Grants & Awards: No specific grants or awards mentioned. Advising: Authored a Master's thesis titled 'Automated Optimised Segmentation of Swimming Fish Midlines' under supervision by Dr. O. Akanyeti and Dr. N. Mac Parthalain.

Jonas Blattمشاهده پروفایل

پژوهشگر

• Process Mining
• Data Analysis
• Business Informatics
• +۳ مورد دیگر

Jonas Blatt is a Researcher at the University of Koblenz-Landau, affiliated with the Process Science Research Group (FG PS) led by Prof. Dr. Patrick Delfmann. He focuses on developing methods and algorithms for uncovering collaboration patterns using event logs within the DFG-funded Social Process Mining project. He also supports teaching activities in the research group. Education: Completed Master of Science in Business Informatics at the University of Koblenz-Landau (Koblenz Campus) in August 2020. Prior Experience: Worked as a software developer in ERP systems during his studies. Research emphasizes process mining, data analysis techniques, and their applications in collaborative workflows.

Sarah Poloمشاهده پروفایل

استادیار

• Rhetoric and Composition
• Archival Research
• Rhetorical Genre Studies
• +۳ مورد دیگر

Dr. Sarah E. Polo is an Assistant Professor of English at Cottey College in Nevada, Missouri. She coordinates the college's First-Year Writing Seminar program and teaches courses in first-year writing, professional writing, multimodal composition, and writing pedagogy. Her research focuses on the histories of rhetoric and composition, archival research, rhetorical genre studies, and writing program administration. Dr. Polo earned her B.S. from Missouri Western State University, M.A. from the University of Missouri-Kansas City, and Ph.D. from the University of Kansas, joining Cottey College in 2019. Her work bridges academic writing and caregiving, exemplified by her pandemic-era video logs exploring intersections of professional and parental responsibilities. She serves as a faculty advising editor for Young Scholars in Writing , highlighting her commitment to undergraduate research mentorship. Her scholarship emphasizes historical archival analysis and multimodal pedagogical practices. Publications include studies on student writing archives (Peitho, 2022), pandemic-era caregiving narratives (Journal of Multimodal Rhetoric, 2022), and multimodal curriculum design (NCTE, 2023). Her contributions reflect a dedication to both scholarly rigor and practical pedagogical innovation in writing education.

Yulai Xieمشاهده پروفایل

دانشیار

• Data Provenance
• Intrusion Detection
• Cloud Computing Security
• +۷ مورد دیگر

Yulai Xie is an Associate Professor at Huazhong University of Science and Technology (HUST), specializing in data storage, provenance systems, and cloud security. His research focuses on intrusion detection, container monitoring, and efficient big data storage architectures, with extensive collaborations with researchers such as Dan Feng and Darrell D. E. Long. His research interests include data provenance , real-time intrusion detection , Docker container security , and hybrid modeling for resource prediction . These areas are evident in his work on systems like Pagoda and P-Gaussian , which leverage provenance graphs and statistical models for enhanced security and performance in cloud and big data environments. The trend in his recent publications shows a consistent focus on secure, scalable, and real-time data systems . He combines machine learning (e.g., Isolation Forest), time series forecasting (ARIMA), and data compression techniques to improve the efficiency and responsiveness of storage and monitoring infrastructures in modern computing environments. Provenance-based intrusion detection Container and cloud security Efficient data storage and retrieval Real-time anomaly prediction Hybrid modeling for system performance Yulai Xie has collaborated extensively with leading researchers and institutions, including the Storage Systems Research Center (SSRC) at UC Santa Cruz. His work has been supported by academic collaborations and institutional resources, though specific grants are not mentioned. He has advised or co-supervised several researchers, including Minpeng Jin, Yafeng Wu, and Zhuping Zou, as seen in co-authored publications. He has been affiliated with the Storage Systems Research Center (SSRC) at UC Santa Cruz as a visiting scholar and has contributed to the Wuhan National Laboratory for Optoelectronics as a postdoctoral researcher. These labs focus on scalable storage, archival systems, and secure data management, aligning closely with his research themes.

• Teacher Education
• Professional Identity Development
• Philosophy of Education
• +۷ مورد دیگر

Siv Yndestad Borgen is a Lecturer at Oslo Metropolitan University, affiliated with the Faculty of Teacher Education and International Studies and the Department of Kindergarten Teacher Education. Her work focuses on professional identity development, mentoring, and existential dimensions of education, particularly grief as lived experience. Position: Lecturer Institution: Oslo Metropolitan University Faculty: Faculty of Teacher Education and International Studies Department: Department of Kindergarten Teacher Education Email: siv.k.borgen@oslomet.no Her research explores critical reflection in teacher education, the role of tacit and embodied experience in crisis, and the philosophical underpinnings of grief and existence. She investigates how student teachers develop professional identity and how mentorship shapes pedagogical practice. Borgen’s publications reveal a strong focus on qualitative methodologies, including focus group interviews and research logs, often applied in cross-cultural contexts such as Norway and South Africa. Her work frequently engages with the Philosophy of Education Society of Great Britain and addresses themes of supervision, mentoring, and reflective practice in teacher training. No scientific awards are listed in the provided text. Borgen has co-authored research on unified mentor training for kindergarten and primary teachers and has conducted interviews exploring the role of teachers as educators. While no formal advising relationships are detailed, her collaborative research suggests active engagement with peers and emerging scholars in the field of teacher education. She contributes to national and international conferences and has published in pedagogical journals such as Norsk pedagogisk tidsskrift . Her work is disseminated through academic books, conference presentations, and policy-related forums, indicating a strong commitment to both research and practical application in teacher education.

Jin Wangمشاهده پروفایل

مربی

• International commercial law
• International arbitration
• Alternative dispute resolution

Jin Wang is a PhD candidate and Ordinary Tutor in Commercial Law at the University of Edinburgh's School of Law, commencing doctoral research in January 2023. She serves as Secretary of the Law Postgraduate Research Student Board (2023-2024) and Content Editor of the Edinburgh Student Law Review, while actively convening academic events including the 2024 Edinburgh Postgraduate Law Conference. Her educational background includes: LLM in Commercial Law, University of Edinburgh (2021) LLB in Law, Southwest Minzu University (2020) Wang's research centers on international commercial arbitration, third-party funding mechanisms, and access to justice frameworks within alternative dispute resolution. Her conference presentations address critical gaps in arbitration systems, including gender barriers and technological solutions for legal inequality, reflecting interdisciplinary engagement between legal theory and data science. Recent publications demonstrate cross-domain scholarship spanning peace agreement analysis, data visualization methodologies, and user interaction systems. This work reveals emerging trends in applying information science to legal processes, particularly in visualizing complex dispute resolution frameworks and user-centric legal service design. As an active academic organizer, Wang has convened major conferences while developing teaching expertise in commercial law. Her service roles within the Law School's postgraduate community highlight leadership in academic governance and scholarly publication.

Masashi Sugiyamaمشاهده پروفایل

استاد

• statistical machine learning
• weakly supervised learning
• learning from noisy supervision
• +۶ مورد دیگر

Masashi Sugiyama is a Professor at the Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, where he has been serving since 2014. He concurrently serves as the Director of the RIKEN Center for Advanced Intelligence Project (AIP) since 2016, leading research groups focused on fundamental AI technologies, AI applications, and social issues of AI. His academic journey began at Tokyo Institute of Technology, where he earned his Bachelor, Master, and Doctor of Engineering degrees in Computer Science in 1997, 1999, and 2001 respectively, before becoming an Assistant Professor and later Associate Professor at the same institution. Sugiyama's research primarily focuses on statistical machine learning, with particular expertise in weakly supervised learning, learning from noisy supervision, and learning under distribution shift. His work has established important theoretical frameworks for density ratio estimation, covariate shift adaptation, and non-stationary environments. He has developed numerous practical algorithms including KLIEP (Kullback-Leibler importance estimation procedure), uLSIF (unconstrained least-squares importance fitting), and LSDD (least-squares density difference), which have become standard tools in the machine learning community. Analysis of his recent publications reveals a strong emphasis on reliable and robust machine learning techniques that can handle imperfect supervision and data distribution changes. His work spans theoretical foundations, algorithm development, and practical applications across various domains including bioinformatics, anomaly detection, and dimensionality reduction. The recurring themes in his research include direct density ratio estimation methods, importance weighting techniques, and mutual information-based approaches for various machine learning tasks. Award for Science and Technology from the Japanese Minister of Education, Culture, Sports, Science and Technology (2022) Japan Academy Medal (2017) Japan Society for the Promotion of Science Award (2017) Faculty Award from IBM (2007) Nagao Special Researcher Award from the Information Processing Society of Japan (2011) Young Scientists' Prize for the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology Japan (2014) Sugiyama has served as program co-chair for major machine learning conferences including NeurIPS 2015, AISTATS 2019, and ACML 2010 and 2020. He has received prestigious fellowships including the Alexander von Humboldt Foundation Research Fellowship (2003-2004) and the European Commission Program Erasmus Mundus Scholarship (2006). He is the (co-)author of influential machine learning monographs including Machine Learning in Non-Stationary Environments (MIT Press, 2012), Density Ratio Estimation in Machine Learning (Cambridge University Press, 2012), Statistical Reinforcement Learning (Chapman & Hall, 2015), and Machine Learning from Weak Supervision (MIT Press, 2022). At RIKEN AIP, Sugiyama leads research initiatives focused on developing robust AI systems that can operate reliably in real-world conditions with imperfect data. His laboratory maintains an active software development effort, providing open-source implementations of many of his research contributions, which has significantly influenced both academic research and practical applications of machine learning.

Philippe Cudré-Maurouxمشاهده پروفایل

استاد

• Exascale Information Management
• Big Data
• Artificial Intelligence
• +۱۳ مورد دیگر

Philippe Cudré-Mauroux is a Full Professor at the University of Fribourg, Switzerland , where he leads the eXascale Infolab . He has held visiting researcher positions at MIT and Microsoft CISL , and serves on the Research Council of the Swiss National Science Foundation and the Scientific Advisory Board of the CHIST-ERA EU Research Programme . Research Interests: His work spans exascale information management , big data , AI , knowledge graphs , linked data , time series data repair , and emergent semantics . He focuses on building scalable, intelligent data systems that integrate storage, computation, and semantics. Publication Trends: His recent work emphasizes schema-aware knowledge graph completion , time series imputation and benchmarking , hardware-accelerated data systems , and large language models for data cleaning . His research bridges database systems, AI, and systems architecture, often targeting high-performance, real-world applications. Scientific Awards: ERC Consolidator Grant (2016) Google Faculty Research Award (2013) Verisign Internet Infrastructures Award (2012) Best Paper Awards at VLDB (2020), AAMAS (2019), and Swiss Data Science Conference (2020) EPFL Doctorate Award and Press Mention (2007) Best Mentor Award at ISWC (2010) Advising and Grants: He mentors a large group of researchers and students, many of whom are co-authors on his publications. He has secured significant funding, including a €2M ERC Grant and multiple Google and Amazon grants, supporting a vibrant research lab focused on next-generation data infrastructure. Labs and Teams: He leads the eXascale Infolab at the University of Fribourg, a dynamic research group actively publishing in top-tier venues and developing innovative tools for data management and AI integration.

• General Surgery
• Surgical Education
• Medical Simulation
• +۳ مورد دیگر

Neal Seymour is a Professor at the UMass Chan Medical School - Baystate Regional Campus , affiliated with the Department of Surgery . He holds an MD and BA in Liberal Arts from Columbia University . His research focuses on laparoscopic surgery , surgical education , and virtual reality simulation for resident training. His work spans General Surgery , Gastroenterology , and Diagnostic Imaging , with significant contributions to improving surgical resident performance through simulation technologies. Key publications examine hernia repair techniques , virtual interview ethics , and AI-driven case logging , reflecting trends in surgical training optimization. Collaborations include co-authors like Dmitry Nepomnayshy and John Romanelli , with affiliations in surgical education networks and simulation centers. His role in the SAGES Fundamentals of Laparoscopic Surgery (FLS) Committee highlights his influence on defining essential laparoscopic skills.

Thomas Bonseمشاهده پروفایل

استاد

• Media Engineering
• Video Signal Processing
• High Dynamic Range (HDR) Imaging
• +۳ مورد دیگر

Prof. Dr.-Ing. Thomas Bonse is a Professor in the field of Bildtechnik (Image Technology) at the Hochschule Düsseldorf (University of Applied Sciences Düsseldorf), Faculty of Media since 2000. His career includes roles as project leader at ITK Telekommunikation AG , group leader at the Forschungsinstitut für Telekommunikation , and R&D engineer at Grass Valley and Panasonic in the domain of advanced TV systems. Education: Diplom-Ingenieur (Dipl.-Ing.) and Doctorate (Dr.-Ing.) in Electrical Engineering from the University of Dortmund. Current Role: Teaching and research in image technology, supervising 15+ theses annually, and leading projects in HDR, broadcast workflows, and real-time video systems. His research focuses on media engineering , particularly in high dynamic range (HDR) imaging , video signal processing , and real-time broadcast systems . Key areas include: Quantisierung von Videoformaten ACES color workflow optimization Wireless video transmission AI-driven object detection IP-based broadcast infrastructures Photovoltaic soiling measurement via drones Recent research trends show emphasis on IP-based video transmission (2016-2023), HDR/SDR workflows (2021-2023), and automated studio systems (2018-2023). He has collaborated with institutions like the Institut für Rundfunktechnik (IRT) , Sportcast GmbH , and Ericsson . As a supervisor, he has guided students in: Automated camera control (Scheunert, 2020) Photovoltaic soiling detection (Mikulaschek/Scheunert, 2020) Sports broadcasting analytics (Mikulaschek, 2022) LED studio lighting systems (2023) Contact: thomas.bonse@hs-duesseldorf.de | Room 04.2.006, HSD Campus

• Agricultural and Biological Sciences
• Animal Transport
• Radio Frequency Identification (RFID)
• +۳ مورد دیگر

Pieter Hogewerf is a researcher at Wageningen University & Research, specializing in Animal Health & Welfare. His work focuses on precision livestock farming, particularly in developing RFID-based monitoring systems for animal behavior and welfare assessment. Key areas: RFID technology, animal transport conditions, slaughter process analysis Active collaborations: European Association for Precision Livestock Farming Research interests center on technological applications for animal welfare improvement, with emphasis on real-time monitoring systems and environmental data capture in transport and farming environments. Recent publications highlight RFID implementations for pig behavior tracking and thermal stress measurement during animal transport. Research trends show strong focus on precision farming technologies and welfare optimization. Projects led include: NAPRO: Temperature monitoring in animal transport GrazeGuide: Smart grazing systems Smart Dairy Farming: RFID applications

Edward Tremelمشاهده پروفایل

استادیار

• Fault-Tolerant Distributed Systems
• RDMA Networks
• Privacy and Security in Distributed Systems
• +۳ مورد دیگر

Edward Tremel is an Assistant Professor in the Department of Computer Science at Augusta University's School of Computer and Cyber Sciences. His research focuses on fault-tolerant distributed systems, RDMA network optimization, and privacy-preserving protocols for smart devices. PhD, Computer Science, Cornell University (2020) MS, Computer Science, Cornell University (2017) BS, Computer Science with Honors, Brown University (2013) Key research contributions include: Lead developer of Derecho , a C++ library for high-performance replicated services in RDMA networks Architect of Cascade , a versioned key-value storage framework for low-latency cloud applications Inventor of CascadeChain , a verifiable log storage system Designer of secure electronic pollbook systems for US elections Recent publications analyze monotonicity in distributed systems, efficient recovery mechanisms, and anonymous query protocols. His awards include NSF travel funding for SOSP 2019 and Heidelberg Laureate Forum selection in 2015.