جستجوی استاد راهنمای دانشگاهی

Dr. Tiago Mendes Ferreira is a Research Fellow at the Institute of Physics within the Faculty of Natural Sciences II at Martin Luther University Halle-Wittenberg. His research focuses on biophysics, molecular dynamics, lipid membranes, and solid-state NMR. He utilizes computational and experimental methods to study complex biological systems, contributing to advancements in medical imaging and material science. Research interests include: Molecular dynamics simulations of lipid membranes Solid-state NMR techniques for biomolecular analysis Computational modeling of membrane proteins Biophysical properties of cellular structures Advanced imaging for medical diagnostics His recent publications emphasize deep learning applications in ophthalmology and biomechanics, reflecting interdisciplinary collaborations. Article trends show strong focus on medical AI, universal design in web interfaces, and sports analytics.

• Biophysics
• Molecular Dynamics
• Lipid Membranes
• +۲ مورد دیگر

Louis Busby is Senior Lecturer and Course Leader for the MSc Data Science and AI at UAL's Creative Computing Institute. His research explores machine learning applications in audio generation and musical robotics. He developed the MIMIC creative ML platform used by 70k+ students and secured multiple Google grants for AI projects. His curriculum development focuses on NLP, machine learning, and creative computing applications. Previously at Goldsmiths, he researched motion sensor feature engineering for interactive ML systems. Commercial experience includes senior developer roles at AI firms. His robotic drummer Mortimer appeared on BBC's Christmas Lectures. Grants include Alan Turing Institute funding for open-source AI music tools. He continues performing music using neural networks and maintains several open-source libraries.

• Machine Learning for Audio Generation
• Social Robotics
• Musical Robotics
• +۲ مورد دیگر

Xiaowan Yi is an Associate Lecturer at the Creative Computing Institute , University of the Arts London (UAL), and a UKRI-funded PhD researcher in Artificial Intelligence and Music at Queen Mary University of London. She holds an MSc in Data Science and Machine Learning from University College London (2018–2019). Her research focuses on neural audio synthesis, music informatics, and generative models, blending computational methods with artistic practice. Education: MSc Data Science and Machine Learning, University College London (2018–2019) Languages: Fluent in English and Mandarin (reading, writing, speaking, and peer review). Previously, she worked as a Research Engineer at Vision RT Ltd (2019–2021). Her interdisciplinary background spans music performance, digital arts, and AI, with professional affiliations including Camberwell, Chelsea, and Wimbledon Colleges of Arts. She maintains active creative and research profiles via her website ( xiaowan-yi.com ) and Vimeo channel.

• Artificial Intelligence
• Music Technology
• Neural Audio Synthesis
• +۳ مورد دیگر

David B Allan serves as Professor of Marketing and Dirk Warren ’50 Sesquicentennial Chair in Business at Saint Joseph's University, where he also co-directs the Music Industry Minor program through the College of Arts and Sciences Interdisciplinary Program. With over two decades of industry experience in radio broadcasting leadership roles at Clear Channel and AM/FM Inc., he bridges academic research with real-world marketing practice. His educational credentials include a BA in Communications from American University (1981), MBA in Marketing from Saint Joseph's University (1999), MLS in Entertainment Law from USC (2022), and PhD in Mass Media & Communication from Temple University (2003). His dissertation examined personal significance of popular music in advertising effects. Dr. Allan's research focuses on music-marketing intersections , with primary streams analyzing advertising cue effects (music placement, commercial lengths, disclaimer speeds) and secondary interests in ethics education and virtual learning . His work demonstrates how personally significant music enhances brand attention, memory, and purchase intent while exploring optimal ad durations and ethical disclaimer presentation. Recent publications reveal evolving trends from Super Bowl music analysis (2016) to AI's disruptive role in audio branding (2023), maintaining consistent focus on empirical measurement of music's advertising impact across diverse media contexts. His scholarship spans consumer psychology, retail atmospherics, and emerging technology applications. He has received Beta Gamma Sigma honors (2009) and multiple university awards including Teaching (2008), Research (2005), and Advisor (2007) distinctions, plus the American Marketing Association Faculty Advisor of the Year (2006). Community service recognition includes Philadelphia Liberty Bell and City/State Citations (2002). As faculty advisor for the AMA chapter and 1851 Records, he mentors students in experiential learning while securing grants like the Morris Grant for 'Super Sonic Logos' (2020) and Arrupe Center funding for 'Joe Camel Meet Juul' (2019). His industry commentary reaches major media including NBC, Washington Post, and Billboard. He actively shapes curriculum through the Music Industry Minor program and student initiatives like Radio 1851, connecting classroom theory to music business practice while researching audio branding's commercial applications.

• Music Marketing
• Advertising Effects
• Commercial Lengths
• +۳ مورد دیگر

Dr. Sheela Ramanna is a Professor and Chair of the Applied Computer Science Graduate Program at the University of Winnipeg , with an adjunct appointment in the Department of Computer Science at the University of Manitoba. She holds a Ph.D. in Computer Science from Kansas State University (2003), an M.S. in Computer Science (1998), and a B.S. in Electrical Engineering (1996) from Osmania University , India. Adjunct Professor, University of Manitoba Professor & Chair, University of Winnipeg Graduate Program Her research focuses on Artificial Intelligence , Machine Learning , and Soft Computing (Rough Sets, Fuzzy-Rough Sets, Tolerance-based Methods) with applications in Multimodal Information Processing , Natural Language Processing , and Topological Data Analysis . She has developed novel tolerance near-set algorithms for sentiment classification, named entity recognition, and community detection in social networks. Recent publications include 2025 work on speech emotion recognition, 2024 studies on diabetic retinopathy detection and plant species recognition, and 2023 research on text summarization and NLP applications. Her work spans 15+ peer-reviewed articles in journals like Scientific Reports , Information Fusion , and Frontiers in Artificial Intelligence . Scientific Awards include the UW Merit Award for Exceptional Performance (multiple years), MITACS Globalink Research Intern (2024), and 3MT People's Choice Award (2018). She has served as Editor for EAAI Journal , Associate Editor for KES Journal , and Organizing Co-Chair for ISCMI 2025 . She supervises 22+ graduate students and postdocs, including Vrushang Patel (President's Scholarship), Habib Ben Abdallah (MITACS Fellow), and Anil Rahate (collaborative PhD with SIT Pune). Her NSERC-funded projects include precipitation forecasting with WeatherLogics Inc., road condition classification, and LULC mapping using satellite imagery.

• Artificial Intelligence
• Machine Learning
• Soft Computing
• +۷ مورد دیگر

David De Roure is a Professor of e-Research at the University of Oxford, affiliated with the Oxford e-Research Centre within the Department of Engineering Science. He holds additional roles as Academic Director of the Digital Scholarship @ Oxford initiative, Academic Director of the Laboratory for AI Security Research, and Honorary Research Professor at the Royal Northern College of Music. His work bridges computer science, cybersecurity, digital humanities, and music technology. De Roure's research focuses on digital scholarship, cybersecurity of IoT systems, and computational methods in musicology. He has led interdisciplinary initiatives such as the PETRAS National Centre of Excellence for IoT Systems Cybersecurity and the Software Sustainability Institute. Previously, he directed the Oxford e-Research Centre (2012–2017) and held roles at the Alan Turing Institute as a Turing Fellow. His academic contributions span over 289 publications, with recent work emphasizing AI-driven cybersecurity, IoT risk management, and music technology. Notable projects include PRiSM SampleRNN (a music generation framework) and foundational work on Research Objects for open science. He is a Fellow of Wolfson College and multiple professional societies, including the British Computer Society and the Institute of Mathematics and its Applications. De Roure's career includes prior professorships at the University of Southampton (2000–2010) and early contributions to the UK e-Science Programme. His educational background includes a PhD in computer science from the University of Southampton (1990). Current research interests include AI in music composition, computational archival science, and ethical implications of emerging technologies.

• e-Research
• Cybersecurity
• Artificial Intelligence
• +۴ مورد دیگر

Professor Val Gillet is a renowned academic in Chemoinformatics, currently serving as Professor of Chemoinformatics and former Head of the School of Information, Journalism and Communication at the University of Sheffield (2012–2016 and 2019–2023). She holds degrees from the University of Cambridge (MA) and the University of Sheffield (MSc, PhD). Her research focuses on computational methods in drug discovery, including de novo design, QSAR modeling, and AI-driven toxicity prediction. She has led interdisciplinary projects funded by EPSRC, BBSRC, and industry partnerships like AstraZeneca and GlaxoSmithKline. Professor Gillet coordinates programs such as the MSc(Res) in Chemoinformatics and teaches courses on data science and computational drug design. Roles: Head of School, REF Coordinator, Deputy Director of Research Education: MA (Cambridge), MSc/PhD (Sheffield) Research: Chemoinformatics, molecular design, QSAR, AI in drug discovery Her work bridges academia and industry, with grants totaling over £2M and over 200 publications. She advises PhD students in areas like de novo design and AI applications. Her lab contributes to projects like Alzheimer’s drug discovery and sustainable chemical formulations.

• Chemoinformatics
• Drug Discovery
• Computational Chemistry
• +۴ مورد دیگر

Affiliations Senior Lecturer in People-Centred AI at the Surrey Institute for People-Centred Artificial Intelligence (PAI) and School of Computer Science and Electronic Engineering, University of Surrey. Visiting Faculty at IIIT Lucknow. Former Postdoctoral Research Fellow at the Centre for Translation Studies (CTS), University of Surrey. Education PhD, IIT Bombay & Monash University (2021) - Dissertation on distributional similarity for cognate detection and computational phylogenetics. BTech in CSE, Uttar Pradesh Technical University (2013). Research Interests Focused on NLP and ML, particularly in low-resource languages, machine translation quality estimation, cognitive NLP, and multimodal information processing. Leads research in Human-Machine Interaction at PAI and the NLP subgroup in the Nature Inspired Computing and Engineering (NICE) group. Publications & Awards Over 30 publications in top conferences (ACL, EMNLP, EACL) including Best Paper Honourable Mention at EACL 2021. Awards include CISCO Fellowship (2016-2020) and Teaching Assistant of the Semester (2017, 2019). Teaching Leads NLP module for undergrad and postgrad students at Surrey. Co-teaches NLP at IIIT Lucknow. Integrates cutting-edge topics like multimodal processing into coursework.

• Natural Language Processing
• Machine Learning
• Low-resource Languages
• +۴ مورد دیگر

Dr Muhammad Awais is a Senior Lecturer in Trustworthy and Responsible AI at the University of Surrey. He leads research on foundation models and self-supervised learning, with affiliations to the Surrey Institute for People-Centred Artificial Intelligence (PAI) and the Centre for Vision, Speech and Signal Processing (CVSSP). His expertise spans AI ethics, audio processing, medical AI, and biometric systems. Education: PhD in AI, MSc in AI, BSc Computer Engineering, BSc Mathematics and Physics. His research focuses on advancing AI through self-supervised learning techniques, with applications in healthcare (e.g., Parkinson’s Disease rehabilitation), transportation, and security systems. He has published extensively on topics like masked autoencoders, audio event classification, and age-invariant face recognition. Key contributions include DailyMAE (fast autoencoder pretraining), ASiT (audio-spectrogram transformers), and AiCareGaitRehabilitation (AI-driven gait rehabilitation). His work emphasizes ethical AI deployment and cross-modal learning.

• Artificial Intelligence
• Trustworthy AI
• Self-Supervised Learning
• +۵ مورد دیگر

Dr. Sara Atito Ali Ahmed is a Surrey Future Fellow at the University of Surrey's Faculty of Engineering and Physical Sciences , specifically within the Centre for Vision, Speech and Signal Processing (CVSSP) . She holds a PhD in Computer Science and specializes in advanced machine learning techniques, with a focus on computer vision, medical imaging, and audio signal processing. Her research emphasizes self-supervised learning, multimodal data fusion, and deep learning ensembles for robust decision-making. Her academic journey includes contributions to healthcare AI through projects like SS-CXR for medical image pretraining and DeepChest for multi-task learning in chest X-ray diagnostics. She has also developed innovative models such as the ASiT audio-spectrogram transformer and DailyMAE for efficient masked autoencoder training. Her work spans diverse domains including robotics perception, SAR target recognition, and plant species identification via ensemble methods. Awards and recognitions are not explicitly mentioned in the provided texts, but her prolific publication record highlights her impact in top-tier venues. She has collaborated on interdisciplinary projects ranging from biomedical applications to environmental sensing, demonstrating a commitment to bridging theoretical research with real-world applications.

• Computer Vision
• Machine Learning
• Medical Imaging
• +۵ مورد دیگر

Dr. Vijaya Kolachalama is an Associate Professor at Boston University, affiliated with both the School of Medicine and the Faculty of Computing and Data Sciences, within the Department of Computer Science. Their research focuses on developing AI-driven solutions for clinical challenges, particularly in neurodegenerative diseases, digital pathology, and domain generalization in medical imaging. Key interests include dementia screening frameworks, clinical-grade software tools for pathology, and neural network advancements for data generalization. Education: B.S. from Indian Institute of Technology, Kharagpur, India; Ph.D. from University of Southampton, UK. Their lab (VKola Lab) emphasizes translational AI for healthcare, with projects addressing Alzheimer’s diagnostics, voice-based cognitive assessment, and gait analysis in osteoarthritis. Collaborations span biomedical engineering, neurology, and nephrology. Research trends in their articles highlight AI applications in healthcare, including privacy-preserving voice analysis, multimodal data fusion for diagnostics, and computational models of amyloid-tau interactions in Alzheimer’s. They also explore digital platforms for brain health monitoring and machine learning in clinical trial design. No scientific awards listed. Advising and grants details are not provided in the text. The VKola Lab website (https://vkola-lab.github.io) serves as a hub for their work, including open-source tools and datasets.

• Artificial Intelligence in Healthcare
• Medical Imaging Analysis
• Neurodegenerative Disease Modeling
• +۵ مورد دیگر

Renan Guarese is a Postdoctoral Researcher in Human-Computer Interaction at KTH Royal Institute of Technology, Sweden. His work focuses on AR/VR applications, particularly assistive technologies for visually impaired individuals and data visualization in pharmaceutical manufacturing through the SMART Industry project. He holds a PhD from RMIT (Australia) and MSc from UFRGS (Brazil), with extensive experience in teaching HCI, AI, and game development at KTH, RMIT, and UFRGS. Education: PhD in Computer Science (2020-2024), RMIT University, Melbourne MSc in Computer Science (2019-2020), UFRGS, Brazil BSc in Computer Science (2013-2018), UFRGS, Brazil Technician Diploma in IT (2013-2014), IFRS, Brazil Research Interests: Assistive AR/VR technologies for accessibility Sonification and spatial audio interfaces Situated visualization for decision-making Empathy embodiment through immersive systems AR applications in education and industrial contexts Article Trends: Recent work emphasizes AR-driven solutions for industrial scenarios (pharmaceutical manufacturing, predictive maintenance) and accessibility-focused interfaces. Key areas include sonification-based navigation systems, cognitive load measurement in games, and embodied empathy experiences. Awards: Best Doctoral Thesis (SVR 2024) ATN PhD Scholarship (2020-2024) 3DUI Contest Winner (IEEE VR 2020) Supervision & Grants: Supervised 4 MSc/Honours students. Active in Digital Futures (AstraZeneca partnership) and SMART Industry projects. Holds grants from ATN, Linnaeus-Palme, and CAPES programs. Labs/Teams: Collaborates with KTH's Division of Computational Science and Technology, RMIT's Centre of Digital Ecosystems, and AstraZeneca's industrial teams. Involved in IEEE, ACM, and SBC conference committees.

• Human-Computer Interaction
• Augmented Reality (AR)/Virtual Reality (VR)
• Data Visualization
• +۶ مورد دیگر

Simon Colton is a Professor of Computational Creativity, Games, and Artificial Intelligence at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science. His research focuses on AI-driven creativity in domains like music, game design, and visual arts, emphasizing generative techniques and philosophical aspects of creative systems. He leads projects in automated composition, procedural content generation, and interdisciplinary AI applications. Education: Extensive background in AI and computational creativity, with a focus on generative systems. Research Interests: Computational Creativity, Generative AI, Music Generation, Game Design Automation, and Neuro-Symbolic Systems. His work explores how AI can autonomously create artistic content, including music, games, and visual art, with notable contributions to frameworks like ANGELINA for game design and The Painting Fool for automated art. Recent projects include AI-driven music composition and tools for creative support (e.g., Gamika, Danesh). Key grants include the £3M EPSRC-funded IGGI2 Centre for Doctoral Training, focusing on Intelligent Games and Game Intelligence. His lab, the Centre for Multimodal AI, advances research in cross-modal AI creativity.

• Computational Creativity
• Artificial Intelligence
• Game Design
• +۴ مورد دیگر

Professor Peter Cowling is a faculty member at Queen Mary University of London, holding the position of Professor of Artificial Intelligence within the School of Electronic Engineering and Computer Science. He is affiliated with the Centre for Multimodal AI, focusing on research areas including AI in games, esports analytics, Monte Carlo Tree Search (MCTS), and applications in real-world problems like maintenance scheduling and business model analysis. His work spans theoretical advancements in AI algorithms and practical implementations in gaming, healthcare, and education. Notable grants include leadership in the IGGI CDT Phase 2 (£3M EPSRC grant), the Digital Creativity Hub, and contributions to game intelligence research. His research emphasizes human-AI interaction, ethical AI narratives, and AI-driven solutions for complex systems. Professor Cowling’s publications highlight contributions to MCTS optimization, esports prediction models, and AI applications in procedural content generation. His interdisciplinary approach bridges computer science, psychology, and economics, addressing societal challenges through technological innovation.

• Artificial Intelligence
• Games
• Future of AI and Humanity
• +۵ مورد دیگر

Jian He is a Teaching Professor at the School of Mathematics , Monash University, Australia. His research focuses on advancing cross-spectral biometric systems, medical image processing, generative adversarial networks (GANs), and robust machine learning. He has contributed significantly to improving face recognition technologies under challenging conditions such as thermal-to-visible spectrum translation and adversarial attacks. His work includes developing frameworks for medical imaging segmentation, enhancing security in biometric systems, and exploring novel applications in audio-visual synchronization and video generation. Key research themes include: Cross-spectral face recognition and thermal imaging analysis Medical image segmentation and 3D reconstruction Generative models for text-to-image synthesis and video generation Adversarial attacks and defense mechanisms in AI systems His publications demonstrate expertise in integrating deep learning with biometric security, healthcare AI, and computer vision applications. Notable contributions include surveys on cross-spectral recognition and innovations in latent diffusion models for high-quality video synthesis. No scientific awards or grants are explicitly listed in the provided texts. He currently has no recorded advisees, though his research areas suggest potential collaborations in interdisciplinary teams focused on AI and medical imaging.

• Biometrics
• Computer Vision
• Medical Imaging
• +۳ مورد دیگر