جستجوی استاد راهنمای دانشگاهی

Josh Reissمشاهده پروفایل

استاد

• Audio Engineering
• Signal Processing
• Music Production
• +۴ مورد دیگر

Josh Reiss is a Professor of Audio Engineering at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science . He holds additional roles including President-Elect and Fellow of the Audio Engineering Society (AES), and Visiting Professor at Birmingham City University. His research focuses on audio signal processing, procedural audio, and intelligent music production. He earned degrees including BSc in Physics, BSc in Mathematics, and a PhD. Research & Awards : Reiss has published over 200 papers, authored books like Intelligent Music Production , and received awards such as the AES Board of Governors Award (2009, 2010) and Best JAES Paper 2016. His work spans sound synthesis, dynamic range compression, and live audio systems. Teaching & Industry : Teaches modules like Artificial Intelligence and Sound Design. Co-founded startups LandR (AI mixing), Tonz, and Nemisindo. Leads the Centre for Digital Music at QMUL, advancing research in audio technology. Labs & Teams : Active in the Centre for Digital Music, collaborating on projects like the Open Multitrack Testbed and semantic audio evaluation tools.

Asta Halkjær Fromمشاهده پروفایل

پژوهشگر

• Formal Logic
• Automated Reasoning
• Theorem Proving
• +۱۳ مورد دیگر

Asta Halkjær From is a postdoctoral researcher in the Department of Computer Science at the University of Copenhagen, affiliated with the Software, Data, People & Society (SDPS) section under Dmitriy Traytel. She previously completed her PhD at DTU Compute from 2020 to 2023, focusing on formalized deduction methods in computational logic. She holds a Master’s and Bachelor’s degree from DTU in Computer Science and Software Technology, respectively, with a specialization in Artificial Intelligence and Algorithms. Her research lies at the intersection of formal logic and computer science, particularly in automated reasoning, proof assistants (Isabelle/HOL and Lean), and mechanized metatheory. She has contributed extensively to synthetic completeness proofs, tableau systems, and verified theorem provers. Her work emphasizes formal verification of logical systems, including epistemic logic, hybrid logic, and first-order logic, with a focus on soundness and completeness. The recent publications highlight a consistent trend: the mechanization of logical foundations in proof assistants. Her work bridges theoretical logic with practical verification tools, enabling reliable automation in theorem proving. She has developed and verified provers, explored axiomatic systems, and advanced the methodology of synthetic completeness, often leveraging Isabelle/HOL’s framework. Distinguished Paper Award, CPP 2023 DTU Young Researcher Award DTU Travel Grant (Executive Board Recognition) Otto Mønsted Fonden Travel Grant She has supervised BSc and MSc theses, special courses, and research projects at DTU, and currently teaches Software Development for Digital Health . She has served on program committees for CPP, ITP, and Dalí workshops and has reviewed for journals including Journal of Automated Reasoning and Journal of Logic and Computation . She has also participated in international research visits, including at VU Amsterdam. She is actively involved in building tools for formal reasoning and maintains a personal website with resources, including an Isabelle snippets generator and bibliography tools. Her work continues to advance the foundations of formal logic through mechanized proofs and practical automation.

• Game Sound
• Sound Design (Procedural/Synthetic)
• Physical Computing
• +۴ مورد دیگر

Dr. Mathew Dalgleish is a Senior Lecturer in Games Audio and Technical Design at Staffordshire University since January 2023. Previously, he held roles as Senior Lecturer at the University of Wolverhampton (2010–2022), course leader for programs in Music Technology, and visiting researcher at the Open University’s Music Computing Lab (2009–2011). He earned a CETL-funded PhD (2013) exploring David Tudor-inspired digital music interface (DMI) design. His research focuses on game sound, accessible technologies, sound synthesis, and neglected histories of electronic music. Notable projects include spatial sound design for theater, accessible game controllers, and modular synthesizer innovations. Education: Began sculpture studies at Northumbria University, transferred to Coventry University for completion. Master’s in programming/physical computing under Rolf Gehlhaar, followed by a PhD in DMI design. Research interests span game audio, controller design, assistive technologies, and interdisciplinary projects blending music and technology. He has secured over £300,000 in grants as PI/CI and collaborates with industry partners. Awards include Senior Fellow of the Higher Education Academy (SFHEA). His work bridges academic, artistic, and applied contexts, emphasizing inclusive design and innovative interfaces. Recent articles highlight trends in accessibility (e.g., video game controllers), procedural audio in theater, and modular synthesizer design. He actively contributes to conferences and publications, addressing topics from multisensory cinema to haptic feedback systems for musicians.

Srinath Sridharمشاهده پروفایل

استادیار

• 3D Computer Vision
• Artificial Intelligence
• Human-Object Interaction
• +۳ مورد دیگر

Srinath Sridhar serves as the John E. Savage Assistant Professor in the Department of Computer Science at Brown University, where he directs the Interactive 3D Vision & Learning Lab (IVL). His research program centers on 3D computer vision and artificial intelligence, specifically developing foundational methods for 4D spatiotemporal visual understanding of objects, human motion, and human-object interactions in dynamic environments. His academic foundation includes a PhD from the Max-Planck Institute (2016), an MSE from the University of Michigan (2012), and a BE from Anna University (2010). Prior to his faculty position, he completed a postdoctoral fellowship at Stanford University under Leonidas Guibas and gained industry experience at Microsoft Research and Honda Research Institute. Research interests span 3D computer vision, artificial intelligence, human-object interaction, robot perception, and deep learning. The IVL lab pioneers techniques for modeling complex 4D visual phenomena, with emphasis on real-world applicability in robotics and virtual environments. Current work integrates geometric computer vision with deep learning to solve challenges in dynamic scene understanding. Analysis of recent publications (2024-2025) reveals dominant trends in 3D vision, generative modeling, and human-robot interaction. Key themes include Gaussian splatting optimization, diffusion-based 3D generation, hand-object manipulation, and multimodal perception. The work consistently bridges theoretical advances with practical robotics applications, particularly in pose estimation, tactile sensing, and dynamic scene decomposition. His scientific recognition includes: NSF CAREER award Google Research Scholar award Best Student Paper award at WACV 2025 Best Paper Honorable Mention at Eurographics 2019 Sridhar teaches core computer vision courses including CSCI 1430 (Computer Vision) and specialized graduate seminars on 3D vision and robot perception. He maintains active research partnerships through his roles as Amazon Scholar and Visiting Faculty at the Indian Institute of Science (IISc), supported by grants from NSF and industry collaborators. The Interactive 3D Vision & Learning Lab (IVL) operates as a multidisciplinary hub for advancing 3D perception, with ongoing projects in generative 3D modeling, real-time pose tracking, and embodied AI. The lab emphasizes open collaboration and maintains strong ties with robotics research groups at Brown and industry partners.

Mark Cartwrightمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Machine Learning
• Audio Processing
• +۳ مورد دیگر

Mark Cartwright is an Assistant Professor of Informatics at the New Jersey Institute of Technology (NJIT), leading the Sound Interaction and Computing (SInC) Lab. His research focuses on human-centered machine listening, audio processing, and creative sound interactions. He holds a PhD in Computer Science from Northwestern University, an MA in Music Science and Technology from Stanford University, and a BMus in Music Technology from Northwestern University. Cartwright's work bridges Human-Computer Interaction (HCI) and machine learning, addressing challenges in audio engineering, urban acoustics, and accessibility. Notable projects include the Sounds of New York City (SONYC) initiative, which uses machine learning to monitor urban noise pollution, and studies on audio captioning and deaf/hard-of-hearing creators' workflows. His lab develops tools like Scaper for soundscape synthesis and MixViz for audio mixing visualization. His research emphasizes ethical and inclusive design, particularly in enabling accessible audio creation for marginalized communities. Collaborations include NYU’s Music and Audio Research Laboratory and the Center for Urban Science and Progress. Cartwright's contributions span datasets like SONYC-UST and MONYC, advancing open-source practices in audio research.