جست‌وجوی استاد و پژوهشگر

Kauther Badrمشاهده پروفایل

استاد

• Business Law
• Employment Law
• International Business Law
• +۱۲ مورد دیگر

Kauther Badr serves as Professor and Accreditation Coordinator in the Department of Management and International Business at Southern Connecticut State University's School of Business. A licensed attorney admitted to Connecticut State courts and the U.S. District Court for Connecticut, she combines academic work with active legal practice through her own law firm, specializing in employment, personal injury, and international law while providing pro bono services to underserved clients. Integral to School of Business achieving AACSB accreditation (Spring 2023) CSCU Transfer Council member University Standards and Assessment Review (StAR) committee co-chair (2020-2023) and current member Her research examines business law, employment law, and international business law through intersecting lenses of gender, ethics, and globalization. She investigates data privacy rights, human rights frameworks, legal technology applications, and organizational structures affecting women in business. Current work addresses AI regulation, healthcare law intersections, and educational policy impacts on legal curriculum development. Recent publications demonstrate evolving focus from foundational business law education to cutting-edge regulatory challenges. Her 2022 textbook establishes core principles while 2023 conference proceedings explore AI ethics and business continuity. Case studies analyze entrepreneurial decision-making in immigrant-owned businesses, and data privacy research spans international compliance frameworks and FOIA exemptions. Professor Badr has secured multiple grants including the $3,000 Accelerated MBA Faculty Incentive Fund grant (2022-2023) for case book development and $6,000 School of Business awards for employment law research (2020-2022). These projects directly inform her teaching of Real Estate Law, Employment Law, and Advanced Employment Law courses while advancing practical business law applications.

Alexey Solodovnikovمشاهده پروفایل

دانشیار

• Systematic Entomology
• Rove Beetles Taxonomy
• Phylogenetics
• +۵ مورد دیگر

Alexey Solodovnikov is an Associate Professor and Curator at the Natural History Museum Denmark, University of Copenhagen. Since 2022, he has led the museum's Zoology research section. His academic work focuses on systematic entomology with special emphasis on rove beetles (Insecta: Coleoptera: Staphylinidae), the largest family of living organisms. Dr. Solodovnikov's educational background includes graduating from university in Krasnodar in 1993, followed by obtaining his PhD from St. Petersburg State University in 1997. He conducted post-doctoral work at the Field Museum of Natural History in Chicago under renowned experts Alfred Newton and Margaret Thayer. His primary research interests encompass systematic entomology, phylogenetics, taxonomy, and biodiversity patterns of rove beetles. As a systematic entomologist, he discovers new species, develops phylogeny-based classifications, and studies evolutionary, biogeographic and macroecological patterns of biodiversity. His work involves extensive study of institutional entomological collections and leading insect collecting expeditions globally. Dr. Solodovnikov has published 137 research outputs, including 129 journal articles. His recent publications demonstrate strong trends in phylogenomics, integrative taxonomy combining morphological and molecular data, citizen science applications in entomology, and studies of specialized ecological relationships like beetle-mammal mutualisms. His work appears in prestigious journals including Systematic Entomology, Systematic Biology, and Journal of Natural History. His scientific contributions are significant in advancing our understanding of insect biodiversity, particularly through methodological innovations that bridge traditional taxonomy with modern computational approaches. Dr. Solodovnikov is actively involved in academic instruction and mentorship. At UCPH, he teaches Entomology and Terrestrial Zoology courses, previously taught in the Basal Arctic Biology course, and currently instructs the Communicating Science module in the UCPH-SCIENCE "Fundamentals" PhD course. He trains the next generation of zoological taxonomists through Master's, PhD, and post-doctoral level mentorship, focusing on developing sustainable expertise to identify, study and protect insect species, many of which remain undiscovered. His research laboratory operates within the Natural History Museum Denmark, with international collaborations spanning multiple continents. The team combines traditional taxonomic approaches with cutting-edge techniques including phylogenomics, deep learning for morphological analysis, and citizen science initiatives to advance systematic entomology and biodiversity research.

Chenchen Kangمشاهده پروفایل

استادیار

• Precision Agriculture
• Autonomous Agricultural Machinery
• Computer Vision
• +۴ مورد دیگر

Chenchen Kang serves as Assistant Professor of Precision Agriculture in Tennessee State University's College of Agriculture, Department of Agricultural Science and Engineering, based at the Otis L. Floyd Nursery Research Center in McMinnville, TN. His work integrates cutting-edge technology with agricultural engineering to solve field-level production challenges. Education: Postdoctoral Scholar, The Pennsylvania State University (2023-2025) Ph.D., Biological and Agricultural Engineering, Washington State University (2018-2023) M.S., Agricultural Mechanization Engineering, China Agricultural University (2016-2018) B.S., Agricultural Engineering (Outstanding Graduate), China Agricultural University (2012-2016) Dr. Kang's research pioneers autonomous agricultural machinery and AI-driven field solutions , with core expertise in computer vision for crop monitoring, precision irrigation systems, and robotic harvesting. His work bridges electrohydraulic control systems and data science to optimize resource use in specialty crops, particularly viticulture and vegetable production. Key innovations include hyperspectral imaging for water stress detection and low-cost sensor networks for orchard management. Analysis of his 9 publications (2022-2025) reveals dominant trends in sensor fusion (hyperspectral/thermal/3D imaging) for real-time vineyard monitoring, robotic thinning/spraying systems, and IoT-based decision support. The research consistently targets practical implementation in controlled environments and open-field agriculture, with strong emphasis on cost-effective solutions for small-scale growers. Dr. Kang actively secures external funding as Co-PI on State Horticultural Association of Pennsylvania projects ($20,964 total) for orchard sensor systems. He has contributed to USDA proposals including AgShred robotic harvesting ($601,250) and precision crop load management. His research infrastructure leverages the Otis L. Floyd Nursery Research Center for field validation of agricultural robotics and sensor technologies.

Matthias Hagenمشاهده پروفایل

استاد

• Information Retrieval
• Natural Language Processing
• Web Data Mining
• +۳ مورد دیگر

Matthias Hagen is Professor of Databases and Information Systems at Friedrich-Schiller-Universität Jena. His research focuses on information retrieval (query understanding, conversational search, comparative questions, known-item search, user simulation), natural language processing (clickbait, argumentation), and web data mining. He earned his Ph.D. from Friedrich-Schiller-Universität Jena with a thesis on algorithmic complexity, and previously led research groups at Bauhaus-Universität Weimar and Martin-Luther-Universität Halle-Wittenberg. His current work develops novel methods for retrieval-augmented generation evaluation, neural information retrieval efficiency, and user-centered search systems. Recent publications examine crowdsourcing for RAG evaluation, LLM-based relevance assessment, corpus subsampling techniques, and child-friendly web search evaluation frameworks. He contributes to open web search initiatives and develops tools like the TIREx Tracker for experimental reproducibility in IR research. Dr. Hagen serves on program committees for major conferences including SIGIR, ECIR, and ACL. His research group participates in competitive evaluations such as TREC, CLEF, and Touché. Recent projects explore axiomatic approaches to retrieval, argumentation systems, and the impact of search result quality on decision-making.

• Intellectual Property
• Copyright Law
• Patent Law
• +۳ مورد دیگر

Aleksei Kelli is a Professor of Intellectual Property Law at the University of Tartu's Faculty of Social Sciences, School of Law, where he also serves as Deputy Director for Research. His academic career spans over two decades at the University of Tartu, progressing from research assistant to full professor. Dr. Kelli holds a Doctor's Degree (2009) and a Research Master's Degree (2005), both from the University of Tartu Faculty of Law. His doctoral dissertation focused on the development of Estonia's intellectual property system to meet knowledge-based economy challenges. His research primarily centers on intellectual property law with specializations in copyright law, patent law, data protection, and the legal implications of artificial intelligence. Kelli's work bridges theoretical legal scholarship with practical applications, particularly in digital environments. His recent publications reveal a growing focus on AI-generated content, copyright exceptions for education, and the impact of EU digital regulations on research access. As an active contributor to intellectual property policy development, Kelli has served as the Estonian national correspondent for intellectual property cases and led significant projects including the 'Raising awareness of IP and copyright in Estonia' initiative funded by EUIPO. His scholarly contributions extend to reviewing for prominent journals including TRAMES, Review of Central and East European Law, and Juridica International. Professionally, Kelli serves on multiple committees including the Copyright Committee at the Estonian Patent Office, the University of Tartu committee resolving intellectual property disputes, and the CLARIN ERIC Legal and Ethical Issues Committee. His work demonstrates a consistent commitment to advancing intellectual property law both in Estonia and within the broader European context.

Farshid Naseriمشاهده پروفایل

دانشیار

• Electric Vehicles
• Battery Management Systems
• Power Electronics
• +۵ مورد دیگر

Farshid Naseri serves as an Associate Professor at AAU Energy within The Faculty of Engineering and Science at Aalborg University, Denmark. His research centers on advancing electric vehicle technologies through innovations in energy storage, power electronics, and control systems, with significant contributions to battery and supercapacitor management. Education: Ph.D. in Electrical Engineering specializing in State Estimation in Advanced Electric Vehicles Research Focus: Dr. Naseri's work spans Electric Vehicles , Battery Management Systems , and Energy Storage , with emphasis on state estimation, predictive control, and system stabilization. His fingerprint analysis reveals core expertise in Supercapacitor engineering (100%), Kalman Filtering (100%), and State of Charge determination (100%), reflecting deep specialization in electrochemical energy systems for sustainable transportation. Publication Trends: Recent publications (2020-2025) demonstrate a strategic evolution from foundational supercapacitor modeling toward AI-integrated battery management and cybersecurity for connected vehicle systems, with increasing focus on real-world vehicular applications and next-generation lithium iron phosphate cells. Scientific Recognition: Awarded Europe's most prestigious research grant in 2025 for groundbreaking work in electric vehicle technology Research Leadership: Principal Investigator for the DeepBMS project (2023-2025), developing deep reinforcement learning-based battery management systems. His work directly contributes to UN Sustainable Development Goal 7 (Affordable and Clean Energy) through advancements in electric mobility infrastructure. Research Environment: Active member of the E-Mobility and Drives research group at AAU Energy, collaborating with international partners on cutting-edge projects at the intersection of power electronics, artificial intelligence, and sustainable transportation systems.

Pascal Bizarroمشاهده پروفایل

دانشیار

• Accounting Information Systems
• IT Auditing
• Information System Assurance & Control
• +۷ مورد دیگر

Pascal Bizarro, Ph.D., is an Associate Professor in the Department of Accounting and Information Systems at Bowling Green State University (BGSU), part of the Schmidthorst College of Business. He holds a Ph.D. and M.Acc. from the University of Alabama and a B.B.A. in Commercial Engineering from HEC, Liège, Belgium. A Certified Information Systems Auditor (CISA), he specializes in IT Auditing, Accounting Information Systems, and emerging technologies like blockchain. He advises BGSU's Information System Audit and Control (ISAC) programs and serves as president of the Northwest Ohio ISACA Chapter and academic board member of the Northwest Ohio IIA Chapter. Dr. Bizarro's research focuses on cybersecurity, audit technology, data privacy, and blockchain applications in accounting. His work has been published in leading journals such as ISACA Journal , Internal Auditing , and The CPA Journal . Notable contributions include studies on phishing attacks, IoT security, AI in auditing, and XBRL implementation. He has received awards including the Schmidthorst Leadership Council Faculty Excellence Award (2015) and the Primrose Family Professorship (2013–present). His professional certifications and academic leadership roles reflect his expertise in bridging accounting practices with information systems innovation.

• Blockchain Technology
• Internet of Things
• Cybersecurity
• +۴ مورد دیگر

Syed Muhammad Danish is a researcher specializing in Blockchain Technology and its applications in Internet of Things (IoT) , Cybersecurity , and Smart Grids . His work focuses on integrating blockchain for security, data privacy, and efficient resource allocation in large-scale systems. Research Interests : Blockchain, IoT, Federated Learning, Electric Vehicles, Cybersecurity, Data Privacy Key Collaborations : Kaiwen Zhang, Hans-Arno Jacobsen, Aroosa Hameed, Ali Ranjha Publication Trends : Recent articles (2025) address privacy-preserving techniques in renewable energy forecasting and electric vehicle charging load optimization using blockchain and federated learning. 2024 studies explore blockchain-as-a-service architectures and energy credit management via distributed ledgers. 2023-2018 works focus on IoT security, blockchain middleware, and defense mechanisms against jamming attacks in LoRaWAN systems.

• Machine Learning
• Computer-Aided Medical Diagnosis Systems
• Medical Signal/Image Processing
• +۵ مورد دیگر

Dr. Jiang Li is a Professor in the Batten College of Engineering & Technology at Old Dominion University (ODU). He holds a Ph.D. in Electrical Engineering from the University of Texas at Arlington (2004), an M.S. in Automation from Tsinghua University (2000), and a B.S. in Electrical Engineering from Shanghai Jiao Tong University (1992). Before joining ODU in 2007, he was a postdoctoral fellow at the NIH's Department of Radiology (2004–2006). Dr. Li's research focuses on machine learning, medical imaging, and signal processing. His work spans computer-aided diagnosis systems for medical applications, neural networks, and modeling/simulation. He has led or co-led numerous grants, including funded projects on biomarker identification, robotic dental implantation, and hazard detection. His research trends emphasize interdisciplinary applications of AI, such as medical imaging analysis, remote sensing, and cybersecurity in engineering systems. Recent publications highlight advancements in deep learning for radiation estimation, seagrass mapping, and adversarial attack detection. Awards : NIH Fellows Award for Research Excellence (2006) UTA TxTEC Award (2003) Image Processing Scholarship (2002) Herman Fellowship (2000) Dr. Li's advising and grants reflect collaborations across disciplines, with notable contributions to biomedical engineering and computational methods. He has contributed to labs and teams in medical imaging, robotics, and environmental remote sensing.

• Cybersecurity
• Data Privacy
• Internet of Things
• +۳ مورد دیگر

Seamus Dowling is a Lecturer in Cybersecurity at the Department of Computer Science & Applied Physics, and serves as Principal Investigator at the Centre for Research and Community Engagement (EPIC). His research focuses on cybersecurity frameworks, data privacy regulations (especially GDPR), and adaptive honeypot technologies. Dowling has contributed to understanding Ireland's cybersecurity landscape and has developed novel approaches for securing IoT environments through machine learning. His recent work includes analyzing GDPR compliance in healthcare sectors, designing adaptive honeypot systems, and evaluating cybersecurity postures in Irish industries. With an h-index of 12 and over 100 citations, his research bridges theoretical cybersecurity principles with real-world regulatory challenges. Dowling collaborates internationally on projects addressing malware detection, privacy-preserving data processing, and dynamic network defense mechanisms. No scientific awards or grants are explicitly listed in the provided information.

• Explainable AI
• Blockchain Technology
• Cryptographic Security
• +۳ مورد دیگر

Dr. Swati Sachan is a Lecturer in Artificial Intelligence in Finance at the University of Liverpool's Management School, specializing in explainable AI and blockchain integration for financial, legal, and insurance sectors. She holds an MSc in Financial Operational Research from the University of Edinburgh and a PhD in Operational Research and Applied Statistics from the University of Glasgow. Her research focuses on developing secure, transparent AI systems using blockchain for auditing, cryptographic security, and decision-making improvements in underserved communities. Key areas include XAI for loan underwriting automation, human-AI collaboration in financial decision noise reduction, and blockchain frameworks for legal compliance. Swati has contributed to industry projects like the UKRI-funded AI Smart Claim insurance toolkit with Kennedys Law and AXA Insurance. Her work emphasizes ethical AI deployment, federated learning for agricultural risk analysis, and optimal strategies for banking API innovations. Teaching modules: Introduction to Programming (Python), LawTech, Regulation and Ethics Professional roles: Advisor at OpenTrellis and Kennedys Law, conference reviewer for GECCO and AI conferences

Vijay Soodمشاهده پروفایل

استاد

• Power Systems
• Smart Grid Technology
• High Voltage DC Transmission
• +۴ مورد دیگر

Dr. Vijay Sood is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University's Faculty of Engineering and Applied Science. He is an industry pioneer with expertise in smart grid energy storage, power systems simulation, protection, and renewable energy integration. His research focuses on advancing HVDC transmission systems and grid resilience. Education: PhD in Power Electronics from Bradford University (1977), MASc in Electrical Machines from Strathclyde University (1969), and BSc in Electrical Engineering from Nairobi University (1967). Research Interests: Smart grid technology, high-voltage DC (HVDC) systems, power electronics, flexible AC transmission systems (FACTS), and energy storage solutions for grid stability. Notable Achievements: Fellow of the Canadian Academy of Engineers (2010), IEEE Fellow (2006), and Engineering Institute of Canada Fellow (1999). Recognized for contributions to HVDC and power system protection through awards like the IEEE Third Millennium Medal (2000). Affiliations: Professional Engineers Ontario, IEEE, and Canadian Academy of Engineers. Teaches courses including Power System Protection Relaying and Capstone Systems Design for Engineering. Publications and Talks: Over 20 technical papers since 2013, addressing HVDC modeling, grid stability, and smart metering. Presented at conferences such as IEEE PowerCon and International Conference on Power Systems Transients.

• Electronic Design Automation
• Energy Efficient Electronic Systems
• Low Power Design
• +۱۲ مورد دیگر

Andrea Calimera is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is actively involved in teaching and research, contributing to doctoral programs and undergraduate and graduate courses in computer engineering and data science. Full Professor (L.240), Polytechnic University of Turin Department of Control and Computer Science (DAUIN) Member, SmartData@PoliTO - Big Data and Data Science Laboratory Member, College of Computer, Film and Mechatronics Engineering His research interests center on electronic design automation, energy-efficient electronic systems, and low-power design, with strong connections to artificial intelligence, embedded systems, and IoT. His work bridges hardware and software optimization for intelligent edge devices. The recent publications (2023–2025) reflect a focused trend on federated learning, secure and efficient AI deployment on edge devices, and low-power embedded systems. Topics include robust evaluation in federated learning, resource management under label skew, homomorphic encryption for private tensor operations, pipeline optimization for keyword spotting, and side-channel attacks via DVFS for neural network fingerprinting—highlighting expertise in both performance and security of AI systems on constrained hardware. Andrea Calimera supervises PhD and master's students and leads research projects funded by competitive and commercial grants. He has contributed to national and international patents on low-power depth estimation and single-image signal processing. Scientific Director, SENSEI Project (2017–2019): Energy-efficient machine learning on chip for IoT Scientific Director, Commercial Project (2020–2022): Design tools for AI on energy-efficient embedded mobile devices Supervision of PhD student Erich Malan (ongoing, since 2022) on distributed and federated learning over IoT networks Supervision of Bachelor's student Chen Xie (2020–2024) on synthesis of smart sensors He teaches courses such as High-Level Synthesis (PhD), Synthesis and Optimization of Digital Systems, Machine Learning for IoT, and Efficient Computing for Artificial Intelligence across Computer Engineering and Data Science programs. His research group is EDA - Electronic Design Automation (DAUIN), which focuses on hardware-software co-design for intelligent systems.

• Digital Forensics
• Cybersecurity
• IoT Authentication
• +۹ مورد دیگر

Dr. Abdulghani A. Ahmed is a Senior Lecturer in Digital Forensics and Course Leader for MSc Cybersecurity at the School of Computer Science and Informatics, De Montfort University (DMU), UK. He is affiliated with the Cyber Technology Institute (CTI) and has a long-standing academic career since 2004, previously serving as a Senior Lecturer at University Malaysia Pahang. University: De Montfort University School: School of Computer Science and Informatics Role: Senior Lecturer, Course Leader (MSc Cybersecurity) Email: aa.ahmed@dmu.ac.uk ORCID: 0000-0001-9748-6067 Education: PhD in Network Security & Intrusion Detection Systems, Universiti Sains Malaysia (2014) MSc in Network Forensics & Identity Spoofing Investigation, Al-Neelain University (2006) BSc (Hons) in Computer Science, Sudan University of Science and Technology (2002) Dr. Ahmed’s research focuses on critical areas in cybersecurity, including digital forensics, IoT authentication, big data privacy, cloud and network security, malware analysis, incident response, and cybercrime investigation. His work integrates machine learning, bio-inspired algorithms, and proactive forensic models to enhance cyber resilience. He has led numerous research projects and published extensively in top-tier journals such as IEEE Access, Sensors, and Springer. The recent publications reflect a strong trend toward digital forensics in cloud and mobile environments, bio-inspired security frameworks, and machine learning applications in cybercrime detection. His work bridges theoretical innovation and practical deployment, particularly in real-time intrusion detection and evidence collection. Scientific Awards and Honors: Multiple Gold, Silver, and Bronze medals from international innovation exhibitions (MTE2018, Citrex, iCAN, ICE-CINNO) CENDEKIA BITARA AWARD 2016 for high-impact journal publication Nominated for Best PhD Thesis Award at USM (2015) Three-time High Impact Publication Award (2011–2013) at USM Dr. Ahmed actively supervises PhD students and has secured significant research funding as Principal Investigator from Innovate UK, COMSTECH-TWAS, and Malaysian government grants. His consultancy work includes cybercrime investigation and incident response for SysArmy Sdn Bhd and Golden Carousel Sdn. Bhd. He is a Senior Member of IEEE and IAENG, and holds professional certifications including SFHEA (UK), Cellebrite CCO, and digital forensics credentials from AccessData and Condition Zebra. He leads the Cyber Technology Institute research group at DMU, focusing on next-generation cybersecurity solutions. His projects include proactive forensic models, IoT security frameworks, and AI-driven botnet detection systems, positioning him at the forefront of applied cybersecurity research.

Aleksandra Knapińskaمشاهده پروفایل

پژوهشگر

• Network Optimization
• Machine Learning
• Traffic Prediction
• +۷ مورد دیگر

Aleksandra Knapińska is a doctoral researcher at the Wrocław University of Science and Technology, Faculty of Electronics, Photonics and Microsystems, Department of Computer Networks and Systems. She is an active member of multiple research teams including the Computer Networks Team, Machine Learning Team, and Advanced Data Analysis Methods Team. Her work is primarily associated with the MAAN project focused on optimizing multilayer application-aware networks. Her research interests center on network optimization , machine learning for traffic prediction , and multi-criteria optimization in optical and multilayer networks . She applies advanced data analysis and machine learning techniques to model and predict time-varying network traffic, particularly in backbone and optical networks. Her work bridges theoretical modeling with practical network performance evaluation. The most recent articles highlight a strong trend in using machine learning—especially ensemble and neural network models—for short-term and long-term network traffic forecasting. These publications emphasize challenges such as feature selection, bandwidth blocking, node failure resilience, and traffic fragmentation in spectrally-spatially flexible optical networks. The research is deeply applied, targeting real-world network performance improvements. Scientific profiles: Google Scholar ResearchGate ORCID: 0000-0003-2654-4893 She is involved in supervising diploma theses and has participated in international research collaborations, including an internship at Politecnico di Torino, Italy, under the InterDocSchool program. She has presented her work at major conferences such as GLOBECOM, ONDM, RNDM, and CNSM. Her PhD thesis, titled "Optimization of multilayer networks with time-varying traffic aided by traffic prediction", is supervised by Prof. Krzysztof Walkowiak, with Dr. Piotr Lechowicz as co-supervisor. She is part of ongoing research projects including: Dark-Box Optimization – Developing highly effective general-purpose optimizers Evolutionary methods for multi-criteria optimization with many criteria Advanced optimization of multi-layer application-aware networks (MAAN) Using multi-criteria optimization in classifier training for decision-making tasks