جست‌وجوی استاد و پژوهشگر

Scott Richard Floydمشاهده پروفایل

دانشیار

• Radiation Oncology
• Brain Tumor Research
• DNA Damage Response
• +۷ مورد دیگر

Scott Richard Floyd is the Gary Hock and Lyn Proctor Associate Professor of Radiation Oncology at Duke University School of Medicine, with secondary appointments as Associate Professor of Radiation Oncology and Assistant Research Professor in Pharmacology and Cancer Biology. He is also a Member of the Duke Cancer Institute and serves as Associate Radiation Director of the Duke Center for Brain and Spine Metastasis and Associate Program Director of the Duke Radiation Oncology Residency Program. Dr. Floyd received his M.D. and Ph.D. from Yale University in 2002. His professional training includes: Internship in Internal Medicine at Hospital of Saint Raphael (2002-2003) Residency in Radiation Oncology at Harvard Medical School, Harvard Radiation Oncology Program (2003-2007) Clinical Investigator position at MIT Koch Institute for Integrative Cancer Research (2012-) Dr. Floyd's research focuses on DNA damage signaling and repair in brain tumor cells, particularly investigating how chromatin changes mediated by epigenetic modifiers affect the DNA damage response (DDR). His lab develops small animal irradiation techniques and mouse models of glioblastoma to test the effects of epigenetic writers and readers on DDR in clinically relevant model systems. He aims to identify strategies to enhance tumor cell killing while protecting normal brain tissues from radiation damage. His work on brain slice models provides a platform for studying stroke, Alzheimer's disease, Huntington's disease, and brain tumors while reducing animal use. Analysis of Dr. Floyd's recent publications reveals a strong focus on brain metastases, radiation necrosis, and the application of artificial intelligence in radiation oncology. His work increasingly integrates radiogenomics, machine learning, and novel radiation techniques to improve outcomes for patients with brain tumors. There's a clear trend toward interdisciplinary collaboration, particularly in combining radiation therapy with immunotherapy and targeted agents, as evidenced by his leadership in the Consortium for Intracranial Metastasis Academic Research (CIMARa). Dr. Floyd has secured significant research funding, including: NEUROD1 function in SCLC fate and plasticity (NIH, 2024-2029) Synthetic lethality with BET bromodomain inhibition (American Cancer Society, 2025-2026) ASPET SURF Institutional Award (2018-2028) Multiple NIH R01 grants supporting his research on DNA damage response and brain tumor biology Dr. Floyd leads the Floyd Lab, which focuses on studying mechanisms of DNA damage signaling and repair in brain tumor and other mammalian cells. His lab utilizes advanced techniques including small animal irradiation, mouse models of glioblastoma, and organotypic brain slice culture platforms. He is also involved in Project Brainslice, which develops experimental model systems using brain slices to research new treatments for brain diseases. His clinical expertise centers on the treatment of benign, primary, and metastatic tumors of the brain and spine, making him a key figure in Duke's brain and spine metastasis program.

• Traditional Chinese Medicine (TCM)
• Data Mining
• Medical Informatics
• +۴ مورد دیگر

Associate Professor Josiah Poon is affiliated with the School of Computer Science at the University of Sydney. His research focuses on applying data mining and IT techniques to Traditional Chinese Medicine (TCM), particularly analyzing herbal combinations for effective treatments. He collaborates with institutions in China to improve TCM evidence and has contributed to clinical data analysis, medical informatics, and multimodal AI systems. Teaching includes courses such as INFO1003 (Foundations of IT) and INFO9003 (IT for Health Professionals). Current research students are Rina CABRAL (Multimodality Representation), Yan LI (Long Document Comprehension), and Xiaobin LU (Financial Decisions). Research highlights include developing algorithms to quantify TCM efficacy, analyzing complementarity in herbal combinations, and applying machine learning to healthcare data. Notable projects include a randomized controlled trial on pneumococcal vaccination (2021) and a Google-funded multimodal health detection system (2020). Key areas of expertise span TCM informatics, medical data analytics, and AI-driven healthcare solutions. His work bridges Eastern/Western medicine through computational methods, emphasizing evidence-based practices in TCM.

• Music Perception
• Intercultural Music Dialogue
• Musicology
• +۳ مورد دیگر

Dr Alex Chilvers is a Lecturer in Aural Skills at the Sydney Conservatorium of Music, The University of Sydney, and an Honorary Postdoctoral Fellow in Macquarie University's Department of Psychological Sciences. He holds a PhD in Composition (2019), a BMus(Hons), BIT(Hons), and is a Fellow of the Higher Education Academy (FHEA). His research focuses on music perception, intercultural musical dialogue, and the aesthetic role of folklore in Polish music. Chilvers composes for orchestras and ensembles like the Tasmanian Symphony Orchestra, and co-founded the Bark Tin Band to explore cross-cultural musical collaborations. He coordinates aural perception units at the Conservatorium and supervises postgraduate research in music performance, composition, and musicology. Current projects include 'New Music Through Dialogic Intercultural Collaboration' with Dr Lulu Liu. Chilvers' work bridges musicology, psychology, and performance, with affiliations to the Music, Sound and Performance Lab and the Australian Music Centre. His compositions and research publications address themes of cultural identity, intercultural exchange, and the psychological impact of music. Publications include analyses of Szymanowski and Górecki's use of folklore, and empirical studies on cultural sensitivity in music appreciation. His teaching emphasizes aural skills development and interdisciplinary approaches to music education.

Anika Großمشاهده پروفایل

استاد

• Database Systems
• Knowledge Graphs
• Ontologies
• +۷ مورد دیگر

Prof. Anika Groß is a Professor for Database Systems and Programming at the Department of Computer Science and Languages at Anhalt University of Applied Sciences in Köthen, Germany. She holds a PhD from the University of Leipzig (2014) and has held roles as a PostDoc in strategic research at Daimler AG and as a research assistant at the Interdisciplinary Centre for Bioinformatics (IZBI). She is actively involved in academic governance, serving on the faculty council, board of examiners, and various sustainability and research data management committees. Her research focuses on database systems, knowledge graphs, and ontology engineering, with applications in environmental science, medicine, and material sciences. Education - PhD (Dr. rer. nat.) in Computer Science, University of Leipzig (2014) - Diploma in Bioinformatics, MLU Halle-Wittenberg (2007) - Postdoctoral research at University of Leipzig's Database Group (2008–2013) Research Interests Her work emphasizes temporal graphs, ontology evolution, and semantic data integration. She develops tools like Region Evolution eXplorer (REX) and contributes to projects such as AgriRestore (ecosystem restoration) and MeineWaldKI (AI-based forest monitoring). Her recent focus includes wearable device applications in healthcare and digital twins for lithium value chains. Recent Research Trends Recent publications highlight interdisciplinary applications of knowledge graphs in agriculture and environmental science, leveraging temporal analysis and machine learning for tasks like chemical transformation prediction and bladder monitoring. She also explores cross-lingual semantic annotations in medical forms and holistic clustering of linked data. Professional Roles - Executive Committee Member, GI Database Systems Group - Fellow, Institute for Technologies and Economics of Lithium (ITEL) - Co-Chair of multiple workshops including FGDB-Workshop @ LWDA 2018 and BigDS@BTW 2017 Labs & Collaborations She leads research teams in projects funded by DFG, European Union (EFRE), and ITEL, collaborating with organizations like Daimler AG and ANU. Her lab focuses on advancing database systems and interdisciplinary data science applications.

• Music Cognition
• Auditory Perception
• Medical Alarm Design
• +۴ مورد دیگر

Dr. Michael Schutz is a Professor of Music Cognition/Percussion at McMaster University's School of the Arts, serving as University Scholar and founding director of the MAPLE Lab. His research bridges music performance/perception, focusing on auditory perception, medical alarm design, and cross-modal sensory integration. Supported by grants from CFI, NSERC, SSHRC, NIH, and others, his work appears in journals like Psychology of Music and British Journal of Anaesthesia . He actively contributes to the Percussive Arts Society and Society for Music Perception and Cognition, co-authoring influential textbooks and leading national percussion networks. Recent studies explore alarm redesign using musical principles and historic shifts in emotional expression across musical eras. His research has been featured on CBC's Quirks & Quarks , On The Nature of Things , and in textbooks including Cognitive Psychology and The Psychology of Music in Multimedia . He directs the McMaster Institute for Music and the Mind, emphasizing interdisciplinary connections between music, mind, and technology. Grants: CFI, NSERC, SSHRC, NIH, Early Researcher Award (Ontario) Key Roles: MAPLE Lab Director, SMPC Board Member (2014–2017) Public Engagement: Over 60 media features, 30+ invited performances, and collaborative research with Vanderbilt University Teaching includes courses on music cognition, percussion ensembles, and laboratory methods. His work has influenced anti-racist practices in music cognition research and ergonomic design of medical interfaces.

• Human-Computer Interaction (HCI)
• Virtual/Augmented Reality (VR/AR)
• User Experience (UX)
• +۶ مورد دیگر

Vassilis Charisis is a Professor of Creative Technologies and Associate Dean of Research and Innovation at the School of Arts and Creative Industries, Edinburgh Napier University . He holds a PhD and MPhil in Human-Computer Interaction (HCI) and VR/AR from the University of Glasgow and serves as a Visiting Professor at the University of Nicosia (Cyprus) and University of West Attica (Greece). Former roles include Professor of HCI and VR/AR at Glasgow Caledonian University Founder and Director of VRS Lab and VRDS Lab Director of Visual, Affective and Pervasive Systems (VAPS) research group His research spans Human-Computer Interaction , Virtual/Augmented Reality , User Experience (UX) , Artificial Intelligence , and Medical Simulation . With over £12.5M in research funding and 100+ publications, he focuses on: Automotive Engineering : AR/VR interfaces, collision avoidance systems Healthcare Applications : Dialysis training, telemedicine Consumer Electronics : UX optimization, gesture recognition Recent publications highlight trends in XR for geriatric rehabilitation , AI-driven AR HUD systems , and IoT security frameworks . His work integrates AI, immersive environments , and user-centered design across domains. Scientific Awards International awards for automotive design (FIAT, Opel) Professional memberships: MIET, FBCS, FRSA, FDSRI, SFHEA He advises on PhD supervision (e.g., Kweku Bram Larbi) and contributes to advisory committees like the Scottish Arts and Humanities Alliance . His projects include: VR Dialysis Training Systems (Kidney Research UK, NHS) noPILLLS in the Water (EU FP7, £7.5M) Collision Avoidance AR Interfaces for emergency vehicles

• Machine Learning
• Toxicology
• Computational Biology
• +۴ مورد دیگر

Keerthana Jaganathan is a researcher at Northumbria University, specializing in the application of machine learning to toxicology and health risk assessment. Her work bridges computational biology, artificial intelligence, and chemical safety analysis. Her research focuses on developing explainable AI models for toxicity prediction, including applications in respiratory, liver, and mitochondrial toxicity. She has published extensively on multimodal fusion approaches, feature selection techniques, and hybrid molecular representations in predictive toxicology. Recent publications highlight her expertise in deep learning for dermal toxicity assessment, fuzzy mutual information for multi-label classification, and comparative studies of tree-based ensemble models in pulmonary toxicity prediction. While specific departmental affiliations are not detailed in the provided texts, her work aligns with interdisciplinary research initiatives at Northumbria.

Prasad Tadepalliمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +۵ مورد دیگر

Prasad Tadepalli is a Professor in the School of Electrical Engineering and Computer Science at Oregon State University, serving as the AI Graduate Program Director. He is affiliated with the Collaborative Robotics and Intelligent Systems Institute. His expertise spans artificial intelligence, machine learning, reinforcement learning, and automated planning, with impactful contributions to explainable AI and natural language processing. Tadepalli holds a Ph.D. from Rutgers University and M.Tech/B.Tech degrees from Indian institutions. He has authored over 100 papers, organized international conferences, and received awards such as the AAAI Outstanding Paper Award (2013) and ICAPS Best Student Paper (2009). Education: Ph.D. (Rutgers University, 1990), M.Tech (IIT Madras, 1981), B.Tech (Regional Engineering College, 1979) His research focuses on advancing AI through techniques like relational planning, reinforcement learning, and interpretable models. Recent work includes integrating planning and RL for multiagent systems and developing explainable models via tree ensemble compression. His articles highlight contributions to time-series imputation, adversarial attacks on bandits, and chess rating estimation using CNN-LSTM networks. Awards: AAAI Outstanding Paper Award (2013), ICAPS Best Student Paper (2009) Tadepalli emphasizes independent thinking in students and has advised numerous researchers. His work bridges theoretical AI with practical applications, such as robotics and data-driven decision-making.

• Random Matrices
• Limit Theorems
• Mathematical Diffraction Theory
• +۱ مورد دیگر

Prof. Dr. Holger Kösters is affiliated with the Institute of Mathematics at the University of Rostock , where he focuses on probability theory and its intersections with mathematical physics and data science. His research spans random matrix theory, spectral distributions, and diffraction phenomena in stochastic systems. University: University of Rostock School: Faculty of Mathematics and Natural Sciences Department: Institute of Mathematics Email: holger.koesters@uni-rostock.de Research Interests: Random matrices and their applications, limit theorems in high-dimensional statistics, mathematical diffraction theory, and probabilistic methods in data science. His work explores universal patterns in eigenvalue distributions, connections to number theory, and statistical mechanics. Publication Trends: Recent articles emphasize random matrix products, spectral asymptotics, and applications to diffraction theory. Areas include polynomial ensembles, free probability, and probabilistic models for point processes. Academic Role: As a professor, he contributes to research and teaching in probability and mathematical statistics, with co-authorships in journals like Annals of Probability and Communications in Mathematical Physics .

Vassilis P. Plagianakosمشاهده پروفایل

دانشیار

• Machine Learning
• Neural Networks
• Bioinformatics
• +۵ مورد دیگر

Vassilis P. Plagianakos is an Associate Professor at the Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece. He has held visiting academic roles at the University of the Aegean, University of Patras, and University of Central Greece. He currently serves as the Department Head and Director of the postgraduate program Informatics and Computational Biomedicine in the School of Sciences. His research focuses on machine learning, neural networks, bioinformatics, and parallel computing with applications in healthcare and education. Education : Bachelor’s in Mathematics (1996), University of Patras Ph.D. in Mathematics (2003), University of Patras Research Interests : Plagianakos explores neural networks, evolutionary algorithms, and machine learning applications in bioinformatics, medical diagnosis, and educational technology. His work bridges computational methods with real-world challenges in healthcare (e.g., precision medicine) and STEM education (e.g., flipped classrooms, AI integration). Recent Trends in Publications : Recent work emphasizes predictive precision medicine using big data, blockchain scalability solutions, and AI ethics in automated content detection. He has pioneered methods like the HCER hierarchical clustering-ensemble regressor and developed tools for analyzing single-cell RNA sequencing data. Professional Activities : Member of IEEE Neural Networks Society, IEEE BBTC, and former Board Member of the Hellenic AI Society. Active in collaborative projects like CrowdHEALTH for policy-driven health data analytics.

Rim Harissمشاهده پروفایل

استادیار

• Operations Management
• Big Data & Machine Learning
• Data Analytics
• +۴ مورد دیگر

Rim Hariss is an Assistant Professor of Operations Management at the Desautels Faculty of Management, McGill University . She holds a PhD in Operations Research from MIT (2019), and degrees from École Polytechnique (MS in Applied Mathematics, 2014; BS in Mathematics & Engineering, 2013). Her research focuses on Big Data Analytics, Dynamic Pricing, Behavioral Operations, and Retail Optimization . Education : PhD in Operations Research, MIT, 2019 MS in Applied Mathematics, École Polytechnique, 2014 BS in Mathematics & Engineering, École Polytechnique, 2013 Research Themes : Combines machine learning with operational decision-making in retail and service systems. Key areas include data-driven pricing strategies, consumer behavior modeling, and optimization under uncertainty. Recent work addresses ticket reselling analytics and markdown pricing mechanisms. Grants & Roles : Principal Investigator: $5,000 SSHRC Grant (2021-2023) for promotional budget optimization in retail McGill Startup Grant ($45k) supporting foundational research Awards : 2022: INFORMS Data Mining Best Theoretical Paper 2019: MSOM Practice-Based Research Finalist Multiple fellowships from French government and MIT Labs/Teams : Actively involved in Data Science for Business Decisions initiatives within Desautels.

Max Stallerمشاهده پروفایل

استادیار

• Transcriptional Regulation
• Gene Expression
• Intrinsically Disordered Proteins
• +۳ مورد دیگر

Max Staller is an Assistant Professor in the Department of Molecular and Cell Biology at the University of California, Berkeley, affiliated with the College of Letters & Science and the Center for Computational Biology. His lab focuses on understanding how transcriptional activation domains regulate gene expression through interdisciplinary approaches combining experimental, computational, and theoretical methods. Research Interests: Transcriptional regulation mechanisms in development and stress responses Functional analysis of intrinsically disordered protein domains Machine learning applications in protein sequence-function prediction Evolutionary dynamics of transcription factors Grants & Collaborations: Lead investigator on the NSF-funded PlantSynBio project (2021) for identifying transcriptional activation domains across plant species. Collaborates with the Cohen Lab (Washington University) on mutational scanning studies. Labs & Affiliations: Director of the Staller Lab, which integrates high-throughput experiments with computational modeling. Active in the Berkeley Bioscience community and the Center for Computational Biology.

Saleh Ashkboosمشاهده پروفایل

پژوهشگر

• Deep Learning
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Saleh Ashkboos is a Ph.D. student in the Computer Science Department at ETH Zurich, advised by Professors Torsten Hoefler and Dan Alistarh. He is also a Research Assistant at the Scalable Parallel Computing Lab and an affiliated doctoral student of the ETH AI Center. His research focuses on accelerating deep neural network training and developing systems for large-scale graph processing. Prior to ETH Zurich, he earned his Master's degree in Computer Science from Sharif University of Technology, advised by Professor Amir Daneshgar. His work has led to notable contributions, including the best paper award at SC22 for 'ProbGraph.' Recent research emphasizes efficient LLM training and quantization techniques, with publications on topics like 4-bit inference, quantization-aware training frameworks, and scalable meteorological modeling. He has interned at Apple and Microsoft, and his work is accessible via Google Scholar and GitHub. Key projects include GPTQ (post-training quantization for transformers), SliceGPT (LLM compression), and ProbGraph (high-performance graph mining). His technical contributions span distributed systems, neural network optimization, and climate-related machine learning.

• Electric Vehicles
• Fuzzy Logic
• Blockchain
• +۵ مورد دیگر

Shahid Hussain is an Associate Professor at King Abdullah University of Science and Technology (KAUST) in the Computer, Electrical and Mathematical Sciences and Engineering Division. His research spans multiple domains including electric vehicle infrastructure, blockchain technology, and intelligent systems for IoT applications, with a focus on practical implementations of computational intelligence techniques. Dr. Hussain's research interests include: Electric Vehicles and Smart Grid Integration Fuzzy Logic and Intelligent Decision Systems Blockchain Applications for Security and Privacy Machine Learning for IoT and Healthcare Applications Energy Management Systems Smart City Infrastructure Development His recent publications demonstrate a strong focus on applying hybrid computational approaches to solve complex engineering problems, particularly in transportation systems and healthcare applications. Dr. Hussain has published extensively in IEEE journals, with particular emphasis on innovative approaches to electric vehicle charging infrastructure, secure IoT systems, and blockchain-enabled solutions for real-world challenges. Dr. Hussain maintains active collaborations with researchers globally, particularly with Reyazur Rashid Irshad, Young-Chon Kim, and Subhasis Thakur. His work bridges theoretical advancements with practical implementations, as evidenced by his research on fuzzy integer linear programming for EV charging stations and blockchain-enabled security frameworks for medical IoT systems.

Erkki Huovinenمشاهده پروفایل

استاد

• Music Education
• Psychology of Music
• Philosophy of Music
• +۷ مورد دیگر

Erkki Huovinen is a Professor of Music Education at the Royal College of Music in Stockholm, Sweden, since 2016. Previously, he held professorships in Musicology at multiple Finnish universities and was a Visiting Professor at the University of Minnesota School of Music. He earned his PhD in Musicology at the University of Turku in 2002, focusing on tonality perception in melodies. His research spans the psychology of music , philosophy of music , and music education , with a focus on creativity, improvisation pedagogy, and mixed-methods approaches. Key Research Areas: Music and imagination, empirical studies on musical creativity, eye-tracking in music reading, theoretical understanding of musical aesthetics. Major Projects: Led the Academy of Finland’s Reading Music: Eye-Movements and the Development of Expertise (2014–2018), exploring visual processes in music reading. Publications: Over 50 peer-reviewed articles and book contributions, including works on music perception, improvisation psychology, and interdisciplinary methodologies. His research integrates qualitative and quantitative methods, such as microphenomenological interviews and eye-tracking studies. He has also contributed to textbooks like Musiikkipsykologia and edited volumes on musical improvisation. His work frequently bridges empirical research with philosophical inquiry, emphasizing the interplay between theory and practice. Grant History: Academy of Finland consortium leader (2014–2018). Teaching: Focuses on music education innovation and interdisciplinary pedagogy. Labs/Teams: Collaborates with interdisciplinary groups in cognitive science and music technology.