جست‌وجوی استاد و پژوهشگر

• Economic Complexity
• Machine Learning
• Data Science
• +۳ مورد دیگر

Orazio Angelini holds a Doctor of Philosophy in Mathematics and is an active researcher with a focus on interdisciplinary research spanning economics, computer science, and healthcare. His work prominently features advanced methodologies such as Hidden Markov Models, regularization techniques, and machine learning algorithms applied to economic complexity, speech synthesis, and medical diagnostics. Education : Ph.D. in Mathematics (institution unspecified) His research interests include economic complexity metrics, data-driven forecasting, speech and singing synthesis technologies, and predictive modeling in healthcare. Notable projects involve developing cluster-driven development indicators and analyzing market structures through regularization techniques. Angelini’s contributions also extend to improving polyglot text-to-speech systems using phonetic features and exploring the interconnectedness of computational models in economic systems. His recent work (2024) highlights advancements in GDP forecasting via technological fitness and innovative speech editing techniques using parallel transformers. Earlier contributions (2017–2022) address challenges in data imputation, asymptotic product dynamics, and medical imaging applications of CNNs. No scientific awards or grants are explicitly listed in the provided texts. His academic advising and lab affiliations remain unspecified.

Iván Gonzálezمشاهده پروفایل

مدرس ارشد

• Assistive Technologies
• Quantitative Gait Analysis
• Frailty Assessment
• +۸ مورد دیگر

Dr. Iván González is a Senior Lecturer at the University of Castilla-La Mancha (UCLM), affiliated with the Faculty of Social Sciences and Information Technologies. He holds a M.Sc. and Ph.D. in Advanced Computer Technologies from UCLM. As a member of the MAmI Research Group, his work focuses on Assistive Technologies, Smart Health, and IoT-based solutions for healthcare monitoring. He has authored 16 JCR articles and supervised 2 PhD theses with 4 ongoing. Education: M.Sc. in Advanced Computer Technologies, UCLM Ph.D. in Advanced Computer Technologies, UCLM His research interests emphasize Quantitative Gait Analysis, Frailty assessment, and Mild Cognitive Impairment screening using wearable sensors and mobile technologies. Recent projects include the EU-funded TAICare initiative (2021-2023) and Just Move! (2022), focusing on movement analysis and cognitive health monitoring. Key Contributions: - Developed a 3D motion capture system for gait automation - Created emotion recognition algorithms using gait patterns - Designed energy-efficient wearable data storage systems - Pioneered conversational agents for IADL monitoring Academic Service: 2nd Academic Year Coordinator (2020, 2024–present) Computer Engineering Degree Coordinator (2020–2024) Lab Affiliation: MAmI Research Group (specializing in Ambient Intelligence and IoT solutions).

Li Xuمشاهده پروفایل

دانشیار

• Auditory Prosthetics
• Hearing Science
• Speech Perception
• +۳ مورد دیگر

Li Xu is an Associate Professor in the Department of Communication Sciences and Disorders at Ohio University's Russ College of Engineering and Technology. His research focuses on electrical hearing mechanisms and auditory prostheses, particularly cochlear implants. He holds a Ph.D. in Neuroscience from the University of Florida (1999), an M.Med. in Otolaryngology from Capital University of Medical Sciences (1988), and a B.Med. from Hengyang Medical College (1985). Research interests include speech perception in cochlear implant users, acoustic properties of speech production in hearing-impaired populations, and the role of spectral/temporal cues in tonal language processing. He has published extensively on topics such as nonlinear frequency compression effects, Mandarin tone recognition, and neural network applications for speech enhancement. Key contributions include studies on cochlear implant sound-processing strategies, auditory rehabilitation outcomes for children, and cross-linguistic speech perception. His work bridges engineering innovations with clinical applications in audiology, addressing challenges in speech understanding and sound quality perception for hearing-impaired individuals.

Chris Rogersمشاهده پروفایل

استاد

• Engineering Education
• Human-Robot Interaction
• Mechanical Engineering
• +۶ مورد دیگر

Chris Rogers is a Professor of Mechanical Engineering at Tufts University School of Engineering and a Professor of Education at Tufts University School of Arts and Sciences. He serves as the John R. Beaver Professor and a CEEO Fellow , focusing on Engineering Education , Human-Robot Interaction , and Educational Robotics . His work bridges Mechanical Engineering with Artificial Intelligence and Music Engineering . Education: PhD in Mechanical Engineering, Stanford University (1989) MS in Mechanical Engineering, Stanford University (1985) BSME, Stanford University (1984) Research Interests center on STEM Engagement , Educational Technology Development , and Teacher Professional Development . He designs tools like Smart Motors and LEGO-based platforms to enhance K-12 engineering education. His work explores Augmented Reality , Reinforcement Learning , and Accessible Makerspaces . Recent Publications demonstrate trends in Robotics Education , AI Integration , and Collaborative Learning Frameworks . Key themes include Low-Cost Hardware , K-12 AI Literacy , and Visual Instructional Design . Scientific Awards Tufts ASME 'Best Professor Award' Harry C. Bigglestone Award National Science Foundation Director’s Distinguished Teaching Scholar Award LabVIEW Programming Prize Robert Knapp Award for Best Paper (ASME) Grants and Projects include collaborations with LEGO Foundation , National Science Foundation , and Parametric Technology Corporation . His initiatives span Preparation for Indonesian STEM Education , Autism Therapy Robotics , and Novel Engineering-Literacy Integration . Labs & Outreach: As founding member of the Tufts Center for Engineering Education and Outreach (CEEO) , he develops global teacher training programs and tools like LEGOEngineering.com , impacting thousands of educators annually.

Margaret Schedelمشاهده پروفایل

استاد

• Interactive Media
• Sound Art
• Music Technology
• +۴ مورد دیگر

Margaret Schedel is a Professor in the Department of Art at Stony Brook University, with an affiliation in the Department of Music. Her work bridges classical music training, sound art, and computational science, focusing on interdisciplinary projects that integrate technology and the arts. She leads the Making Sense of Data Workgroup at the Institute of Advanced Computational Science and co-directs computer music initiatives. Her research spans interactive multimedia opera, virtual reality experiences, sound art installations, and innovative interfaces for music creation. Notable projects include The King Listens , a telematic opera, and RhumbLine , an exploration of biomimetic musical robots. She also investigates sonification techniques for healthcare applications, such as gait rehabilitation for Parkinson’s patients. Her recent articles highlight trends in inclusive design for music technology, sonification of scientific data, and reimagining traditional instruments through feminist perspectives. She advocates for accessibility in hackerspaces and gender equity in STEAM fields. Her work often merges artistic expression with cutting-edge computational methods, reflecting her dual focus on creativity and scientific inquiry. Margaret’s contributions extend to education through courses on electronic music, sound art, and interdisciplinary collaboration. She has pioneered pedagogical frameworks for notation in digital performance and contributed to the development of open-source tools like softVNS for video processing.

David Hitchcockمشاهده پروفایل

استاد

• Functional Data Analysis
• Cluster Analysis
• Environmental Data Analysis
• +۵ مورد دیگر

David Hitchcock is a Professor of Statistics at the University of South Carolina, serving as Director of the Graduate Program in the Department of Statistics within the McCausland College of Arts and Sciences. He earned his B.S. from the University of Georgia, M.S. from Clemson University, and Ph.D. from the University of Florida. His research focuses on functional data analysis, cluster analysis, and environmental applications, including spatio-temporal modeling of precipitation, medical skill assessment, and wildfire data analysis. Education: Bachelor’s Degree: University of Georgia Master’s Degree: Clemson University (Mathematical Sciences) Ph.D.: University of Florida (Statistics) Research Interests: Hitchcock’s work spans functional data analysis, cluster analysis, and environmental statistics. Recent projects include: Simultaneous registration and clustering of functional data in medical skill evaluation. Spatio-temporal models for flood dynamics and precipitation patterns. Applications in loggerhead turtle population estimation and mass spectrometry. Collaborations: He collaborates with researchers like John Grego (flooding data), Ian Dryden (proteomics), and S.Z. Samadi (environmental engineering). His team has developed influential methods in functional regression and influential curve detection. Teaching: Hitchcock teaches advanced statistics courses such as Bayesian Data Analysis, Multivariate Statistics, and Time Series Forecasting. Recent courses include STAT 542 (Computing for Data Science) and STAT 530 (Applied Multivariate Analysis). Student Advising: Guided PhD students in topics like functional clustering, stock price prediction, and music genre analysis. Notable advisees include Zizhen Wu (functional registration), Shan Zhong (deep learning ensembles), and Aimée Petitbon (multinomial time series).

Lance Putnamمشاهده پروفایل

پژوهشگر

• Generative Art
• Digital Sound Synthesis
• Media Signal Processing
• +۵ مورد دیگر

Lance Putnam is a Researcher at the Department of Computing, Goldsmiths, University of London , specializing in generative art, digital sound synthesis, and media signal processing. He holds a BSc in Electrical & Computer Engineering from the University of Wisconsin, an MA in Electronic Music & Sound Design , and a PhD in Media Arts and Technology from the University of California. His work explores the intersection of sound and graphics, symmetry in art and science, and spatiotemporal motion concepts. Collaborates with Professor William Latham and Visiting Professor Stephen Todd in Digital Creativity Labs Active in VR workshop organization (2016-2017) and international exhibitions (Paris, Venice, Kyoto, Saint Petersburg) Research focuses on procedural art generation through evolutionary algorithms, creating immersive experiences like Mutator VR and Organic Art VR that blend biological inspiration with mathematical modeling. His publications span virtual reality interfaces , flow field dynamics , and shape synthesis techniques , emphasizing human aesthetic guidance in computational creation. Article trends show 2016-2020 development of VR systems for artistic evolution , including interactive mutoid agents , vortex environments , and pedagogical adaptations . These works employ trigonometric curves , procedural landscapes , and parameter space control , with applications in art exhibitions (Centre Pompidou, HYBRIS, CYFEST) and scientific visualization .

• Machine Learning
• Data Mining
• Recommendation Systems
• +۵ مورد دیگر

Univ.-Prof. Dr. Günther Specht is a faculty member in the Department of Computer Science at Universität Innsbruck. His research focuses on machine learning, data mining, and their applications in recommendation systems, music information retrieval, and authorship attribution. He has contributed to projects such as HPT4Rec (a hyperparameter optimization framework for recommenders) and Cloudgene (a cloud computing tool for biomedical pipelines). His work spans database systems, text analysis, and social media analytics. Notable tools include HaploGrep 2 (for mitochondrial DNA analysis) and StyleExplorer (for textual style visualization). Key research areas include: (1) Developing algorithms for music popularity prediction and playlist analysis; (2) Enhancing authorship attribution techniques using grammar profiling and syntax tree analysis; (3) Designing efficient database index structures like Height Optimized Tries; and (4) Investigating ethical aspects of recommendation systems and plagiarism detection. Publications from 2020-2024 highlight advancements in cross-domain text classification, social media behavior analysis, and automated music genre recognition. His work bridges traditional statistical methods with modern machine learning, emphasizing practical applications in both academic and industry contexts.

Steven Walczakمشاهده پروفایل

استاد

• Artificial Intelligence
• Healthcare Informatics
• Cybersecurity
• +۴ مورد دیگر

Steven Walczak, Ph.D., is a tenured Professor in the School of Information at the University of South Florida's College of Arts and Sciences. He holds dual appointments with the Florida Center for Cybersecurity and has served in roles such as Editor-in-Chief of the Journal of Organizational and End-User Computing . His research focuses on applying artificial intelligence systems (e.g., neural networks, expert systems) to healthcare informatics, cybersecurity, and electronic commerce. He earned his Ph.D. in Artificial Intelligence from the University of Florida, with earlier degrees from Johns Hopkins and Penn State. Education: Ph.D., Artificial Intelligence, University of Florida (1990) M.S., Computer Science, Johns Hopkins University (1985) B.S., Mathematics, Pennsylvania State University (1981) His research spans healthcare decision support, cybersecurity threats (e.g., drone-based attacks on medical devices), and AI-driven disaster response analytics. Recent projects include using neural networks to predict surgical outcomes and identifying musical borrowing patterns via data science. He has authored over 80 peer-reviewed articles and holds an h-index of 33 (Google Scholar). Awards: Reviewer of the Year (2009), Best Paper Award (2002), Educator of the Year (1992-93), and Sigma Xi nomination (2021). Grants: Includes $41K for cybersecurity research (2020) and multiple grants for lab equipment (e.g., Palo Alto Networks firewall, mobile computing devices). Service: Chair of USF Sabbatical Committee (2018-2020), Faculty Senate Executive Committee member (2018-2022), and editorial leadership roles across 10+ journals.

• Artificial Intelligence
• Semantic Web
• Machine Learning
• +۲ مورد دیگر

Eugenio Di Sciascio is a Full Professor and Scientific Coordinator at Politecnico di Bari. His research spans artificial intelligence, semantic web technologies, machine learning, and explainable AI, with applications in recommender systems, healthcare, and cybersecurity. As evidenced by 413+ publications, his work frequently bridges theoretical computer science with practical implementations. Recent research trends focus on trustworthy AI systems, particularly in healthcare diagnostics and recommendation security. His 2024-2025 publications demonstrate strong emphasis on explainable AI methodologies in medical applications (e.g., BRAINEX for brain age prediction, MORIX for mortality inference) and adversarial robustness in recommender systems. Additional work explores neurotechnology interfaces and semantic web foundations.

Toby Heysمشاهده پروفایل

استاد پژوهشی

• Virtual Reality
• Machine Learning
• Media Theory
• +۵ مورد دیگر

Professor Toby Heys is a Research Professor at Manchester School of Art, Manchester Metropolitan University. He leads research in digital art, sound studies, and media theory, focusing on virtual reality, acoustic surveillance, and sonic warfare. His work spans installations, publications, and collaborations with institutions like AUDINT and Hexagram. Key projects include AUDIENCE WITH A HERO (Innovate UK), LIKELY STORIES (AHRC), and UNHEALTHY BIAS (Wellcome Trust). He holds a PhD from Liverpool John Moores University and has been a Visiting Scholar at NYU. Research Interests: Toby’s work explores the intersections of technology and culture, particularly through sound and virtual reality. His projects investigate how sonic frequencies and digital tools influence perception, memory, and society. Recent themes include the ethics of AI in health communication, the legacy of acoustic surveillance in espionage, and the cultural implications of virtual necromancy. Grants & Projects: AUDIENCE WITH A HERO (£1m): VR-based Holocaust witness experiences. LIKELY STORIES (£60k): Machine learning in social media narratives. UNHEALTHY BIAS (£1.2k): NHS video efficacy for South Asian audiences. MOOD/MUSIC (£83k): Co-creating emotion-sensing music tools for young carers. Publications: Toby’s outputs include books like Sound Pressure (2019) and Unsound:Undead (2019), as well as exhibitions such as The Phantom Economy of Torments (2025) and Ghostcode (2023). His research group AUDINT examines sonic frequencies in military and civil contexts.

• Digital Arts
• Game Engines
• Machine Learning
• +۲ مورد دیگر

Owen Brierley is a Senior Lecturer in the Department of Creative Industries at Kingston University. He holds a Ph.D. in Computational Media Design from the University of Calgary and researches digital arts, game engines, and human-computer interaction. His work merges technological innovation with artistic principles across various creative domains. Dr. Brierley's interdisciplinary research spans machine learning applications, bioinformatics visualization, and interactive media design. As former Executive Director of the Edmonton Digital Arts College (2008-2019), he expanded the institution by over 1,400% and developed research-led curricula. His artistic collaborations encompass theater, dance, music, and visual arts, with works featured at venues including the Banff Centre for the Arts.

• Music Technology
• Interactive Music Systems
• Musical Expression and Gesture Analysis
• +۴ مورد دیگر

Teresa Nakra is a Professor and Director of Music & Technology at Stevens Institute of Technology’s School of Humanities, Arts and Social Sciences. Previously, she held roles as Professor of Music and Design at The College of New Jersey (TCNJ) and Adjunct Assistant Professor at Worcester Polytechnic Institute. Her research focuses on musical expression, gesture analysis, and interactive systems, with notable contributions like the Conductor’s Jacket and the Digital Baton. She has collaborated with institutions like the Boston Symphony Orchestra and Robert Wood Johnson University Hospital on music & health initiatives. Education: PhD (2000) and MS (1996) in Media Arts & Sciences from MIT, BA (1992) in Music (magna cum laude) from Harvard University. Her 2024 book Constructing Music: Musical Explorations in Creative Coding (Oxford University Press) is a seminal work in the field. Research Interests: Quantifying conducting gestures for interactive systems, music technology education, health applications of music, and interdisciplinary collaboration between arts and sciences. Her work bridges music performance, computer science, and robotics, as seen in projects like conducting robots and museum installations. Articles highlight her focus on synchronous audience-conductor dynamics, immersive pedagogy, and robotics in music education. Awards include the Excellence in Technology Education Award (2008) and induction into Phi Kappa Phi (2018). Grants and Projects: Over $400K in funding for initiatives like TCNJ’s Center for Creative Technology, health communication projects with Colgate-Palmolive, and NSF grants for conducting robotics research. She advises on curriculum design at K-12 and university levels, including a 6th-grade music program in NJ. Labs/Teams: Founder of Immersion Music, Inc. (1999–2021), a nonprofit developing music technologies for artists and institutions. Current collaborations include a music & health design project with Robert Wood Johnson University Hospital.

• Neuroscience
• Mathematical Biology
• Computational Mathematics
• +۶ مورد دیگر

Amitabha Bose is a Professor in the Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT). His research focuses on mathematical neuroscience, particularly modeling neural networks and circadian rhythms. He has actively contributed to understanding synaptic plasticity, rhythmic timing mechanisms, and oscillatory systems through interdisciplinary approaches combining mathematics and biology. His work spans circadian entrainment dynamics, phase resetting in neural networks, and applications of mathematical models to music perception and sleep disorders. Bose has secured multiple NSF grants, including projects on undergraduate biology-mathematics training programs and the role of synaptic plasticity in neuronal networks. His research outputs include over 50 peer-reviewed articles in journals such as Mathematical Biosciences , Scientific Reports , and Journal of Theoretical Biology . Key Projects : Conference on Frontiers in Applied and Computational Mathematics (2022) UBM Training Program in Biology and Mathematics (2004–2010) Role of short-term synaptic plasticity in feedback neuronal networks (2006–2010) Bose’s grants and collaborations reflect his expertise in bridging mathematical analysis with biological systems, particularly in rhythm generation and neural network behavior. His recent work includes studies on circadian misalignment in shift work and jet lag, as well as biophysical models for rhythmic timing in recurrent neural networks.

Suresh Peddojuمشاهده پروفایل

استادیار

• Cybersecurity
• Healthcare Technology
• Machine Learning
• +۳ مورد دیگر

Suresh Peddoju is an Instructional Assistant Professor in the Department of Information Science Technology at the University of Houston's College of Technology. His expertise lies in cybersecurity, healthcare technology, and machine learning applications. He teaches courses including CIS 2332 (Information Technology Hardware), CIS 2337 (Information Security Fundamentals), and CIS 3347 (Information Systems Infrastructure). Research Interests: Peddoju focuses on securing smart medical devices (Medical 4.0), developing machine learning frameworks for early disease diagnosis (e.g., diabetes, Alzheimer's), and enhancing IoT-based healthcare systems. His work also addresses cybersecurity challenges such as DDoS defense mechanisms and malware detection through system call analysis. Publications Trends: His recent work (2020-2025) highlights advancements in AI-driven diagnostics, IoT security, and grid computing trust models. Notable contributions include using NLP for anomaly detection and evaluating cloud-based healthcare infrastructure. Labs/Teams: No specific lab affiliations mentioned, but collaborates on interdisciplinary projects combining cybersecurity and healthcare innovation.