جست‌وجوی استاد و پژوهشگر

• New Product Development
• Knowledge Management
• Collaborative Work Environments
• +۵ مورد دیگر

Angelo Corallo is an Associate Professor at the Department of Experimental Medicine, University of Salento, specializing in technologies and methodologies for collaborative processes in industrial systems. His research spans Digital Business Ecosystems , Cybersecurity , and Collaborative Product Design , focusing on the interplay between technology and organizational dynamics. He leads interdisciplinary research divisions in Open Networked Business Management , Learning and Innovation , and Collaborative Product Design . Research Interests : Corallo's work integrates Information and Communication Technologies (ICT) with Business Management, particularly in Digital Twins for healthcare and manufacturing Knowledge Modeling and Ontology Engineering Industry 4.0 and Smart Manufacturing Agri-Food Sustainability through digitalization Scientific Contributions : His recent articles explore trends in Cybersecurity for Industrial IoT Metaverse Applications in business models Traceability Systems in food supply chains Collagen-Based Biomaterials from aquaponics

Mahsa Salehiمشاهده پروفایل

مدرس ارشد

• Data Mining
• Machine Learning
• Time Series Analysis
• +۵ مورد دیگر

Mahsa Salehi is a Senior Lecturer in the Department of Data Science & AI at Monash University’s Faculty of Information Technology. She holds a PhD in Computer Science from the University of Melbourne and previously served as a postdoctoral researcher at IBM Research Australia. Her research focuses on data mining, machine learning, and time series analysis, with applications in healthcare, cybersecurity, and smart grids. Education: PhD in Computer Science, University of Melbourne (2016) MSc in Software Engineering, Amirkabir University of Technology (2009) BSc in Information Technology & Computer Engineering, Amirkabir University of Technology (2008/2006) Her key research interests include multi-dimensional time series analysis, anomaly detection, brain-inspired machine learning, and non-stationary data learning. She has led or contributed to over 40 research outputs, including high-impact papers on anomaly detection frameworks (e.g., CARLA) and EEG representation learning (EEG2Rep). Her work bridges theoretical advancements with practical applications, such as detecting urinary anomalies in seniors and securing smart grid systems against cyberattacks. Dr. Salehi has secured significant grants, including AU$246K from ARENA (2019–2021) and AU$30K from Emotiv Research (2022–2024). She is an Associate Editor of the ACM Transactions on Knowledge Discovery from Data and has been recognized with awards like the ICDM 2022 Best Paper Runner-Up and IBM’s Manager’s Choice Award (2016). Grants & Projects: Privacy-Preserving Machine Learning (CSIRO Next Gen, 2023–2027) AI for Clean Energy & Sustainability (Monash, 2023–2027) Deep Learning for Brain EEG Analysis (PhD Top-Up, 2022–2025) Her contributions extend to editorial and patent activities, including roles at IBM Research and collaborative projects with industry partners like Emotiv.

Bernadette Hyland-Woodمشاهده پروفایل

مدرس

• Public Data Policy
• Digital Communications
• Data Ethics
• +۸ مورد دیگر

Dr. Bernadette Hyland-Wood is a Lecturer in the School of Communication at Queensland University of Technology (QUT) and a Research Fellow at QUT's Centre for Data Science. She serves as an Affiliated Investigator in the Computational Communication and Culture Program within QUT's Digital Media Research Centre and is a chief investigator in the QUT Digital Media Research Centre. Her academic journey began with a Bachelor of Arts (Honours equivalent) in Computational Linguistics from UCLA, followed by a PhD in Policy and Governance from the University of Queensland in 2021. Dr. Hyland-Wood's research focuses on: Public data policy and digital communications during crisis situations Data ethics, AI governance, and organizational behavior in data-driven environments Responsible data science and deployment of generative AI technologies Indigenous Data Sovereignty and ethical considerations in AI development Science and technology policy with applications in health data infrastructure Her scholarly work demonstrates a consistent trajectory examining the intersection of data, policy, and public communication, particularly during periods of societal disruption. Recent publications reveal an increasing focus on AI governance frameworks, Indigenous perspectives on technology, and regulatory compliance in emerging technological landscapes. Her research has evolved from foundational work on open government data to more complex analyses of AI ecosystems and their societal implications. Dr. Hyland-Wood has received recognition through media features in the Australian Broadcasting Corporation (ABC) and Radio New Zealand. Her expertise has been sought for high-level policy contributions, including chairing the W3C Government Linked Data Working Group and authoring influential publications on crisis communications during the COVID-19 pandemic. Professional highlights include: Founding four tech startups in Australia and the U.S., two of which were acquired by major companies Serving as professional CEO of a semantic technology spin-out from MIT Co-founding Women in Technology (WiT) Australia in 1997, now Australia's largest professional networking organization supporting women in digital technologies Two decades of involvement in Open Source Software projects and W3C data standards development Leadership in international initiatives on data exchange standards to support digital research and evidence-based policymaking Dr. Hyland-Wood's career bridges academia, industry, and policy, emphasizing applied research and knowledge translation to ensure responsible AI and data-driven decision-making. Her work contributes to multiple United Nations Sustainable Development Goals, particularly those related to quality education, industry innovation, and reduced inequalities.

Nitesh V. Chawlaمشاهده پروفایل

استاد

• Artificial Intelligence
• Data Science
• Network Science
• +۴ مورد دیگر

Nitesh V. Chawla is the Frank M. Freimann Professor of Computer Science and Engineering at the University of Notre Dame, serving as founding director of the Lucy Family Institute for Data and Society. He also holds concurrent faculty appointments in the Department of Applied and Computational Mathematics and Statistics (College of Science) and the Department of Information, Technology, Analytics and Operations (College of Business). Ph.D., Computer Science and Engineering, University of South Florida, 2002 M.S., Computer Science, University of South Florida, 2000 B.E., Computer Science and Engineering, University of Poona, 1997 Chawla's research focuses on advancing artificial intelligence, data science, and network science to address societal challenges through interdisciplinary collaboration. He applies machine learning and big data analytics to domains such as public health, peace processes, and community development, with an emphasis on ethical and translational impact. Scientific recognition includes: Fellowships: AAAS, AAAI, ACM, IEEE Awards: IEEE CIS Outstanding Early Career, IBM Watson Faculty, IBM Big Data and Analytics, 1st Source Bank Technology Commercialization Honors: Rodney F. Ganey Award, Michiana 40 under 40 He founded the Inference Analytics and Learning (DIAL) Lab and co-founded Aunalytics, a data science software company. Affiliations span Notre Dame's Kellogg Institute, Kroc Institute, Liu Institute, Pulte Institute, Reilly Center, and Technology Ethics Center.

• Eye Tracking Methodology
• Human-Computer Interaction
• Computer Graphics
• +۵ مورد دیگر

Andrew T. Duchowski is a Professor at Clemson University, specializing in Eye Tracking Methodology, Human-Computer Interaction, and Computer Graphics. His work spans over two decades with significant contributions to gaze-based interaction systems, foveated rendering, and cognitive load measurement. He authored three editions of the influential textbook Eye Tracking Methodology (Springer, 2003/2007/2017). Duchowski's research integrates eye movement analysis with applications in virtual reality, medical imaging (e.g., colonography viewers), and aviation safety. He actively collaborates with institutions globally and serves on editorial boards for journals like Proceedings of the ACM on Human-Computer Interaction . His recent projects include developing real-time gaze analytics pipelines and exploring entropy-based metrics for visual attention analysis. Publications (selected 15 recent): Focus on advancing gaze interaction in immersive environments, optimizing 3D visualization, and measuring cognitive load through pupillary activity and microsaccades. Key co-authors include Krzysztof Krejtz, Matias Volonte, and Donald House.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۵ مورد دیگر

Christian Eichhorn is an Assistant Professor in the Department of Computer Science at Technical University of Munich, specializing in Human-Computer Interaction, Virtual Reality, and Augmented Reality applications. His research primarily focuses on developing serious games and immersive technologies for healthcare, education, and older adults. He has established a strong collaborative network, particularly with David A. Plecher and Gudrun Klinker, resulting in numerous publications in top HCI and VR venues. Dr. Eichhorn's research interests center around creating accessible and engaging technology applications. His work demonstrates particular expertise in developing serious games for various educational purposes (language learning, history education), healthcare applications (rehabilitation, dementia care), and technologies specifically designed for older adults. His research combines technical innovation in AR/VR systems with practical applications addressing real-world challenges in healthcare and education. Analysis of his recent publications (2022-2025) reveals a consistent focus on practical applications of immersive technologies. His work spans educational tools for programming and language learning, healthcare applications for rehabilitation and clinical training, and specialized technologies for older adults. The research demonstrates a strong interdisciplinary approach, bridging computer science with healthcare, education, and gerontology. His technical contributions include innovations in AR/VR system design, collaborative environments, and novel interaction techniques. Dr. Eichhorn has been actively involved in organizing workshops and contributing to major conferences in the VR/AR field, including IEEE VR and ISMAR. His collaborative approach is evident in his extensive co-authorship network spanning multiple institutions. His laboratory work focuses on developing practical AR/VR applications, with particular emphasis on creating systems that bridge virtual and physical experiences. Current projects include serious games for health behavior change, rehabilitation assessment tools using wearable sensors, and social VR environments for older adults.

Malcolm Macdonaldمشاهده پروفایل

استاد

• Space Technology
• Astrodynamics
• Networked Systems
• +۳ مورد دیگر

Eur Ing Malcolm Macdonald is a Professor of Electronic and Electrical Engineering at the University of Strathclyde. He serves as Director of the Applied Space Technology Laboratory (ApSTL) and the Centre for Signal and Image Processing (CeSIP). Additionally, he holds Visiting Professor roles at University College Dublin's Centre for Space Research and is Vice-Chair of the UK Space Agency's Space Technology Advisory Committee. His expertise spans space mission design, networked systems, and sustainable space technologies, with a focus on democratizing space data accessibility. He contributed to Scotland's first CubeSat and led initiatives like the Scottish Centre of Excellence in Satellite Applications (SoXSA). Research interests include astrodynamics, swarm engineering, and Earth observation, leveraging systems engineering to address global challenges. Notable awards include the 2020 Copernicus Masters Transport Challenge and the 2024 CompleNet Best Poster Award. He advises on over 80 research projects, focusing on satellite constellations, offshore energy monitoring, and space debris mitigation. His work integrates multidisciplinary approaches, emphasizing resilience and innovation in space systems. Labs and teams include ApSTL and CeSIP, where he leads a team of researchers and postgraduate students. Equipment resources include specialized drones and control systems for experimental validation. Collaborations span academia, industry, and government, driving advancements in space technology and policy.

Hakan Demirtasمشاهده پروفایل

دانشیار

• Statistical Methods
• Missing Data Analysis
• Multiple Imputation
• +۳ مورد دیگر

Hakan Demirtas is an Associate Professor in the Department of Epidemiology and Biostatistics at the University of Illinois at Chicago (UIC) School of Public Health. His research focuses on statistical methods for handling missing data, multiple imputation, and simulation techniques in public health contexts. He leads the Center for Health Statistics and has developed several R packages for data generation and analysis. His work emphasizes improving statistical methodologies for correlated data, particularly in discretization and correlation modeling. Notable contributions include frameworks for generating multivariate data with mixed variable types and modeling correlational transformations in non-normal contexts. His research also applies statistical models to epidemiological studies, such as estimating pandemic dynamics and assessing environmental health risks. Dr. Demirtas has published extensively on topics like Poisson data generation, fractional Brownian motion discretization, and software tools for statistical analysis. He actively contributes to the R community through packages like MultiOrd and PoisNor. Despite no explicit awards listed, his impactful methodological work underscores his expertise in biostatistics.

Zhao Zhaoمشاهده پروفایل

استادیار

• Wearable Systems
• Human-Computer Interaction (HCI)
• Human-Robot Interaction (HRI)
• +۴ مورد دیگر

Zhao Zhao is an Assistant Professor at the School of Computer Science, University of Guelph. Her work focuses on wearable systems, human-robot interaction, and gamification for health and education. She holds a PhD from Carleton University (2019) and completed a postdoctoral fellowship at the University of Toronto (2019–2023) before roles at McMaster University and her current position. Education includes a BSc in Computer Science from University of Electronic Science and Technology of China (2011), MSc from Carleton University (2014), and PhD in Electrical and Computer Engineering (2019). Research interests span physiological computing, AI-assisted creativity tools, and adaptive systems leveraging wearable sensors. Key research areas include: 1) Wearable-based gamification for health and education, 2) Emotion sensing via physiological signals, and 3) Human-robot interaction enhanced by wearable data. Her lab uses Empatica EmbracePlus wristbands and Emotiv EEG headsets to analyze real-time physiological responses in diverse interaction scenarios. Recent publications (2020–2025) emphasize personalized exergame systems, child-robot interaction studies, and AI linguistic competency analysis. She actively seeks graduate students and industry partnerships in wearable technology, education tech, and HRI.

• Psychometrics
• Personality Psychology
• Statistical Methods in Psychology
• +۳ مورد دیگر

Michele Vecchione is a Full Professor (Professore Ordinario) of Psychology at Sapienza University of Rome. He holds the academic rank of Professor and specializes in psychometrics, personality psychology, and statistical methods for psychological assessment. He is affiliated with the Department of Psychology of Development and Socialization within the School of Medicine and Psychology. His research focuses on personality assessment, value theory, and statistical methodologies, with particular attention to political behavior, developmental psychology, and the application of advanced statistical models like structural equation modeling. Education: Vecchione earned a Laurea in Psychology (2001) and a PhD in Social and Personality Psychology (2006) from the University of Padua. He has held various academic positions, including Researcher (2008), Associate Professor (2015), and Full Professor (2023) at Sapienza University. He has also held visiting researcher positions at institutions like the Humboldt University of Berlin (2014) and the University of Helsinki (2011). Research Interests: His work emphasizes the measurement of personality traits, values, and their role in predicting behavior, political choices, and academic performance. He has led projects on value stability across life stages, the protective role of resilience in health conditions, and the application of implicit association tests in organizational settings. His research has been supported by grants from Sapienza University and international collaborations. Teaching: Vecchione teaches courses in psychometrics, statistical analysis, and research methods at both undergraduate and graduate levels. He has coordinated courses such as Psicometria and served as a faculty member in doctoral programs in Psychology and Neuroscience. Awards and Editorial Roles: He has held editorial positions in journals like BMC Psychology and the European Journal of Psychological Assessment. His academic qualifications include national scientific habilitations for both second (2012–2020) and first-level university professorships (2017–2023).

• Voice Acoustics
• Choir Acoustics
• Voice Analysis
• +۵ مورد دیگر

Sten Ternström is a Professor at KTH Royal Institute of Technology's Division of Speech, Music and Hearing. He holds a MScEE (1982), PhD (1989), and has been a Professor since 2003. His research focuses on voice acoustics, particularly singing voice analysis and synthesis, with emphasis on clinical applications. Current interests include addressing voice variability, electroglottography, and audio technologies for music and voice clinics. He has led projects like FP7 EUNISON and SkAT-VG, and is a Fellow of the Acoustical Society of America. Education: All degrees at KTH—MScEE (1982), PhD (1989). Research Interests: Voice acoustics, choir acoustics, voice synthesis, biomedical signal processing. His work combines technical innovation with clinical relevance, e.g., developing FonaDyn software for real-time voice analysis. He explores how vocal fold dynamics influence voice quality and investigates non-invasive methods for voice assessment. Publications: Over 100 peer-reviewed articles, including recent work on WaveNet-based EGG prediction (2025), voice mapping post-thyroidectomy (2024), and pediatric voice analysis (2021). His research spans voice disorders, Parkinson’s disease voice therapy, and choral singing acoustics. Awards: Fellow of the Acoustical Society of America, Guest Editorships, and editorial roles in Acta Acustica. His contributions bridge engineering and clinical practice in voice science. Teaching: Leads courses in music acoustics, sound engineering, and supervises MSc projects on voice clinic software and singing synthesis. Active in outreach for choir acoustics and pedagogy. Labs/Teams: Involved in FonaDyn software development for voice analysis. Collaborates internationally on voice biomechanics and clinical voice measurement.

Ingvild Berganمشاهده پروفایل

استادیار

• Educational Technology
• Guidance Pedagogy
• Professional Development for Educators
• +۳ مورد دیگر

Ingvild Bergan is an Assistant Professor at the Department of Education , University of Agder, specializing in guidance pedagogy and digital competence development . She holds a general teacher qualification from UiA/UiO, a master's in religion, ethics and society (UiA), interdisciplinary guidance studies (UiT), and project management (BI). Teaches guidance pedagogy for school and kindergarten teachers Leads R&D work in initial teacher education and mentor education Co-leader of Practice, Teaching, Policy in Teacher Education (PUPIL) research group Her research focuses on technology integration and learning design to enhance mentor professional development , with specific emphasis on 360° video and virtual reality (VR) applications. She investigates how digital tools can improve observational learning and competence assessment in educational settings. Recent publications highlight trends in educational technology for mentorship, game-based learning for cultural inclusivity, and digital competence frameworks in teacher education. Her work spans empirical studies, theoretical analyses, and practice-oriented interventions documented in journals like Nordic Journal of Digital Literacy and NORDVEI: Nordic journal in guidance pedagogy . While no explicit scientific awards were mentioned, her extensive collaborative R&D projects (e.g., ProDiG) demonstrate institutional impact. She has no formal student advisement records listed but contributes to professional development through school partnerships.

• Numerical Analysis
• Computational Mathematics
• High-dimensional Integration and Expectations
• +۸ مورد دیگر

Dirk Nuyens is a Senior Lecturer in the Department of Computer Science at the Faculty of Engineering Sciences, KU Leuven, Belgium. He is affiliated with the Numerical Analysis and Applied Mathematics (NUMA) research unit and is a member of the iSi Health Institute for Physics-based Modeling for In Silico Health. He also serves on the Faculty Council of Engineering Sciences and the Programme Committees for Engineering Sciences and Computer Science. Education: While specific degrees are not listed, his expertise and research output indicate advanced training in numerical analysis, computational mathematics, and applied mathematics. Research Interests: His primary research focuses on numerical analysis, computational mathematics, and quasi-Monte Carlo (QMC) methods. Specific areas include high-dimensional integration and approximation, lattice rules, low-discrepancy sequences, uncertainty propagation, and financial engineering. He develops algorithms for efficient sampling, integration, and approximation in high-dimensional spaces, with applications in uncertainty quantification, Bayesian inversion, and PDEs with random coefficients. Research Trends: His recent publications emphasize the construction and analysis of embedded lattice-based algorithms for multivariate function approximation and integration. There is a strong focus on achieving higher-order convergence rates, particularly in Korobov and Sobolev spaces, and on developing randomized lattice rules for improved error bounds. His work bridges theoretical developments in numerical analysis with practical implementations in scientific computing and engineering. Scientific Contributions: He has authored or co-authored numerous influential papers in top-tier journals such as Mathematics of Computation , Journal of Complexity , SIAM Journal on Numerical Analysis , and Journal of Computational Physics . His work on lattice rules, QMC methods, and high-dimensional integration has been widely cited and used in fields ranging from computational finance to theoretical physics. Projects and Funding: He leads or co-leads several ongoing and completed research projects funded by national and international agencies. These include projects on turbulence reconstruction from partial observations, uncertainty quantification for climate control in buildings, computational methods for infinite-dimensional Bayesian inversion, circularity improvements in scrap analysis, and ML-based sensitivity analysis. Software Development: He maintains and contributes to open-source software repositories for QMC point generation, including the Magic Point Shop and QMC4PDE projects. These provide efficient implementations of lattice and digital sequence generators in MATLAB, C++, and Python. Institutional Service: Beyond research, he contributes to academic governance through his roles in faculty and departmental councils, influencing curriculum development and strategic planning in engineering and computer science education at KU Leuven.

• Artificial Intelligence in Medicine
• Rhinology
• Ear Surgery
• +۵ مورد دیگر

Rhea Darbari Kaul serves as an Ears, Nose and Throat Registrar at Macquarie University Clinical Associates (MUCA) while pursuing her Doctor of Philosophy through the Faculty of Medicine, Health and Human Sciences at Macquarie University. With an h-index of 19, she demonstrates significant research impact in her field. Dr. Darbari Kaul's research focuses at the intersection of artificial intelligence and otolaryngology, with particular emphasis on rhinology and ear surgery applications. Her work bridges clinical practice with technological innovation, developing practical AI solutions for medical imaging analysis, surgical procedures, and prosthetic development. She has established herself as a specialist in applying computational methods to paranasal sinus radiology and endoscopic ear surgery video analysis. Her publication record reveals a clear trajectory toward integrating artificial intelligence with traditional ENT practices. The pattern shows increasing sophistication in AI applications, moving from systematic reviews of existing literature to developing novel algorithms and practical clinical tools. Her research demonstrates strong collaboration with multidisciplinary teams including clinicians, computer scientists, and engineers. As an active researcher with multiple publications in 2023 and 2025, Dr. Darbari Kaul contributes significantly to advancing the application of artificial intelligence in otolaryngology. Her work on open-source algorithms and cost-effective digital solutions suggests a commitment to making advanced medical technologies more accessible across different healthcare settings.

Anantaa Kotalمشاهده پروفایل

استادیار

• Generative AI
• Privacy-Preserving Data Sharing
• Cybersecurity
• +۲ مورد دیگر

Anantaa Kotal is an Assistant Professor of Computer Science at The University of Texas at El Paso (UTEP), commencing her position in Fall 2024. Previously, she completed her PhD at the University of Maryland, Baltimore County (UMBC) and gained industry experience at Amazon and IBM. Her academic credentials include: PhD in Computer Science, University of Maryland Baltimore County (UMBC), 2024 B.E. in Computer Science and Engineering, Jadavpur University, 2017 Dr. Kotal's research centers on Generative AI applications for privacy and security, with emphasis on privacy-preserving data sharing, synthetic data generation, and policy compliance verification. She integrates knowledge graphs, reinforcement learning, and neurosymbolic approaches to develop frameworks for secure data synthesis in healthcare, agriculture, and cybersecurity domains. Her work addresses critical challenges like policy ambiguity resolution and trustworthy AI code generation. Analysis of her 15 most recent publications (2021-2025) reveals a strong trajectory toward knowledge-infused generative models for privacy preservation, with increasing focus on large language models (LLMs) and real-world applications in distributed systems. Key thematic clusters include policy-aware data synthesis (12 publications), healthcare data security (7 publications), and knowledge-graph-enhanced cybersecurity (5 publications). Dr. Kotal is actively recruiting graduate students for her research lab at UTEP and currently teaches Data Mining (CS 5362/6362) in Fall 2024. She maintains active research collaborations with her doctoral advisor Dr. Anupam Joshi at UMBC and industry partners including IBM. She leads a research laboratory at UTEP focused on developing next-generation privacy-preserving AI systems, with current projects spanning healthcare data anonymization, agricultural data sharing frameworks, and policy-compliant synthetic data generation for cybersecurity applications.