Find Academic Supervisors

Robert BaudoView profile

Lecturer

• Learning and Memory
• Sensation and Perception
• Psychoacoustics
• +2 more

Robert Baudo is a Lecturer in the Department of Psychology at Lake Forest College. His research focuses on auditory perception, cognitive learning mechanisms, and memory consolidation processes. PhD, MA in Communication Sciences and Disorders, Northwestern University BS in Psychology and Biology, Middle Tennessee State University Dr. Baudo's work investigates: How auditory cues (like interaural level differences) contribute to sound localization The role of pinna anatomy in shaping spectral cues for vertical localization Memory reactivation constraints and anterograde interference effects Time-sensitive dynamics of perceptual learning consolidation His recent publications demonstrate expertise in psychoacoustics and cognitive neuroscience, particularly examining auditory discrimination tasks and stimulus-specific memory mechanisms. Key trends include studying binaural hearing, memory plasticity, and temporal processing limitations. Dr. Baudo contributes to undergraduate education through teaching in psychology and mentoring student research projects, while maintaining active collaborations with researchers at institutions like Middle Tennessee State University and Northwestern University.

• Differential Geometry
• Geometric Flows
• Ricci Flow
• +4 more

Prof. Miles Simon is a University Professor at the Institute for Analysis and Numerical Analysis (IAN) at Otto von Guericke University Magdeburg. His research focuses on geometric flows, particularly Ricci flow and mean curvature flow, with emphasis on singular metric spaces, curvature estimates, and geometric evolution equations. He has held academic positions since 1998, including postdoctoral roles at Max Planck Institute, Humboldt University Berlin, and Albert Ludwigs University Freiburg before becoming a full professor in 2011. Education: Completed his PhD at Melbourne University (1997) with a thesis on Ricci flow pinching phenomena. He obtained his Habilitation at Freiburg (2007) and has extensive postdoctoral training across leading institutions. Teaching: Regularly instructs advanced courses in differential geometry, geometric evolution equations, and analysis. Recent courses include Analysis III, Funktionentheorie, Differentialgeometrie II, and seminars on geometric analysis topics. Research Contributions: Over 20 peer-reviewed articles since 2000, focusing on Ricci flow regularity, curvature estimates, soliton dynamics, and geometric limit spaces. Notable work includes extending Ricci flows in 4D with bounded curvature and analyzing singularities in 3D geometries. Leadership: Project leader in DFG's SPP 2026 'Geometry at Infinity' and organizer of international workshops on nonlinear geometric diffusion equations. Active in academic administration and mentoring PhD students. Lab/Team: Supervises graduate researchers including Dr. Florian Litzinger and M.Sc. Priyamvada Vishwamitra, focusing on geometric flow applications and singularity analysis.

• Signal Processing
• Communication Systems
• Wireless Communications
• +5 more

Assoc. Professor Jun Tong is affiliated with the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong. He holds a PhD from City University of Hong Kong and specializes in signal processing for communication systems and instrumentation, focusing on robust, low-complexity algorithms for high-dimensional signals and imperfect models. His research enhances spectrum/energy efficiency in challenging environments. Research Interests: Signal processing applications in communication systems, MIMO and 5G/6G technologies, optical systems, machine learning for signal processing, and sensor networks. He has published extensively in top-tier journals like IEEE Transactions and conferences such as ICC and MWP. Teaching & Supervision: Teaches Digital Signal Processing, Engineering Electromagnetics, and Digital Hardware. Supervises PhD/Master’s projects on topics like 6G wireless communication, MIMO systems, and light-field imaging. Current students are researching areas such as ODDM modulation and sub-THz communications. Funding & Grants: Secured grants including the Advancement and Equity Grants Scheme for Research (AEGiS) for multi-modal defect detection in manufacturing. Previously led projects on UOW-UESTC collaborations. Service & Leadership: Member of the IEEE. Actively involved in academic leadership and curriculum development within his school.

Sébastien GaltierView profile

Professor

• Plasma Physics
• Astrophysics
• Turbulence
• +4 more

Sébastien Galtier is a Professor of Astrophysics at Université Paris-Saclay and a member of the Plasma Physics Laboratory (LPP) at the Polytechnic School (École Polytechnique), located in Palaiseau, France. He holds an honorary fellowship from the Institut Universitaire de France. His primary affiliation is with the Space Plasmas team within the LPP, focusing on fundamental plasma physics and astrophysical applications. His research spans turbulence in astrophysical and cosmological contexts, including solar wind dynamics, magnetohydrodynamics (MHD), gravitational waves, and interstellar medium processes. He employs advanced mathematical frameworks and numerical simulations to explore these phenomena. Key research areas include weak MHD turbulence theory, solar coronal heating mechanisms, planetary dynamo processes, and the study of compressible and incompressible plasma turbulence. His work bridges theoretical models with observational data from space missions and laboratory experiments. Notable contributions include groundbreaking studies on gravitational wave turbulence, solar wind plasma dynamics, and the development of exact scaling laws for compressible and Hall MHD turbulence. He has authored influential books such as Physics of Wave Turbulence (2023) and Introduction to Modern Magnetohydrodynamics (2016). Awards include the Honorary Fellowship of the University Institute of France, recognizing his contributions to plasma physics and astrophysics. His research has been published in leading journals like Physical Review Letters , Astrophysical Journal , and Journal of Plasma Physics .

Mitchell GuttmanView profile

Professor

• Non-coding RNA
• Gene Expression Regulation
• 3D Nuclear Organization
• +3 more

Mitchell Guttman is a Professor of Biology at the California Institute of Technology (Caltech), where he leads the Guttman Lab. His research focuses on understanding how long non-coding RNAs (lncRNAs) regulate gene expression and nuclear organization. He holds a B.S. and M.S. from the University of Pennsylvania (2006) and a Ph.D. from MIT (2012). Before becoming a full Professor in 2019, he served as an Assistant Professor at Caltech and a Visiting Associate. His work has pioneered methods like SPRITE and ChIP-DIP to map 3D genome organization and RNA-protein interactions. Education: B.S., University of Pennsylvania, 2006 M.S., University of Pennsylvania, 2006 Ph.D., Massachusetts Institute of Technology, 2012 His research investigates how lncRNAs coordinate proteins, localize to genomic targets, and shape nuclear architecture to control gene expression. Recent breakthroughs include discoveries about nuclear speckles' role in mRNA splicing efficiency and the development of technologies for multiplexed protein-DNA/RNA interaction mapping. His lab integrates experimental and computational approaches, emphasizing collaboration across disciplines. Key Projects: SPRITe: Maps multi-way DNA-RNA-protein interactions in 3D ChIP-DIP: Identifies hundreds of proteins binding DNA simultaneously SPIDR: Maps RNA-protein interactions under cellular stress Labs & Teams: The Guttman Lab fosters an inclusive environment for students and postdocs, emphasizing innovation and cross-disciplinary collaboration. Recent lab members include Paulomi Bhattacharya, Andrew Perez, and Jimmy Guo, who have contributed to high-impact studies on nuclear organization and RNA biology.

• Structural Biology
• Ion Channels
• Cryo-Electron Microscopy (Cryo-EM)
• +3 more

Frederick Sigworth is a Professor of Cellular and Molecular Physiology, Biomedical Engineering, and Molecular Biophysics and Biochemistry at Yale University. He holds primary faculty appointments in Cellular & Molecular Physiology and secondary appointments in Molecular Biophysics and Biochemistry. His research focuses on the structural and functional analysis of ion-channel proteins using cryo-electron microscopy (Cryo-EM) and electrophysiological techniques. Sigworth’s work has significantly advanced understanding of ion channel gating mechanisms, voltage sensor function, and membrane protein structure. Education: PhD in Physiology from Yale University (1979). Postdoctoral training at the Max Planck Institute for Biophysical Chemistry (Göttingen, Germany) under Erwin Neher, co-developer of the patch-clamp technique. Key contributions include pioneering cryo-EM methods for membrane protein analysis and structural studies of potassium channels. Research interests span structural biology, ion channel biophysics, and cryo-EM methodology. Notable projects include determining the structure of the BK potassium channel and developing computational tools for single-particle image analysis. Collaborations include work with Henry J. Binder and Joseph Santos-Sacchi on ion channel physiology and engineering. Awards include AAAS Fellowship (2023), National Academy of Sciences membership (2016), and the K. C. Cole Award (1997). His lab, the Sigworth Lab, integrates experimental and computational approaches to study ion channel mechanisms. Phased retirement status indicates reduced but ongoing academic engagement.

Amalia de GötzenView profile

Associate Professor

• Service Design
• Systemic Design
• Open Data
• +7 more

Amalia de Götzen is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology, part of The Technical Faculty of IT and Design. Her work focuses on Systemic Design, Service Design, and Open Data initiatives, with a particular emphasis on participatory approaches and sustainability. She leads projects like CREATIVE DRIVERS FOR SUSTAINABLE LIVING HERITAGE LANDSCAPES and BC4ECO (Blockchain for Environmental Education), exploring interdisciplinary solutions for societal challenges. Her research interests include systemic design principles, cross-cultural collaboration through digital platforms, and ethical frameworks for data-driven design. Notable contributions include the DiversityOne multi-country smartphone sensor dataset and work on Theory of Change methodologies in urban regeneration projects. She has been awarded for innovative contributions to mobile sensing and 3D user interface design. Prof. de Götzen actively engages in public sector design, developing tools like the Stakeholder Map to enhance citizen-centric service design. Her projects often bridge academia and industry through collaborative ecosystems, emphasizing open licensing and IP awareness (e.g., ZOOOM project). Key Projects: Co-Design 4 Transitions (CD4T) - Climate Transition Strategies (2024-2027) Blockchain for Environmental Education (BC4ECO) - Disruptive Technology Pedagogy (2022-2025) CREATIVE DRIVERS - Heritage Landscapes and Sustainable Living (2023-2026) Awards: 2023: Mood Inference Model Prize for cross-cultural data analysis 2015: 3D User Interface Design Excellence Award Her work frequently addresses global challenges through design thinking, such as circular economy practices and digital citizenship frameworks. Current research explores temporal dimensions in urban planning and ethical AI integration in diversity-aware platforms.

• Augmented Reality
• Virtual Reality
• Computer Graphics
• +6 more

Dieter Schmalstieg is the Alexander von Humboldt Professor of Visual Computing at the University of Stuttgart and an adjunct professor at Graz University of Technology. He leads research in augmented reality (AR), virtual reality (VR), and visualization, with contributions to tracking, rendering, and medical applications. His work spans academia and industry, with over 400 publications and numerous awards, including the IEEE ISMAR Career Impact Award and Fellow of the IEEE. Education: PhD (1997), Habilitation (2001) from Vienna University of Technology. Research: Focuses on AR/VR systems, medical visualization, and real-time graphics. Key projects include the Christian Doppler Laboratory for Handheld AR and collaborations with Qualcomm and VRVis. Awards: START Prize (2002), IEEE Technical Achievement Award (2012), Humboldt Professorship (2023). His teaching includes courses on computer graphics, VR, and real-time rendering. He has advised over 30 PhD students, many of whom hold academic or industry leadership roles. Current research explores situated analytics, mixed reality telepresence (MRUnion), and AR applications in mining and medicine (MiReBooks).

Yan YanView profile

Assistant Professor

• Bioinformatics
• Machine Learning
• Big Data Analysis
• +7 more

Yan Yan is an Assistant Professor at the School of Computer Science, University of Guelph. His research focuses on bioinformatics, multi-omics analysis, and AI-driven computational models for understanding biological processes. His lab develops algorithms for genome-wide association studies, single-cell RNA-seq analysis, and de novo peptide sequencing, with applications in plant genomics and digital agriculture. Education : Not explicitly stated, but his publications suggest advanced training in bioinformatics and computational biology. Research Interests : Bioinformatics, Machine Learning, Big Data Analysis, Statistical Association, and AI applications in agriculture. His work integrates artificial intelligence with omics data to uncover disease mechanisms and improve agricultural practices. Recent trends in his publications emphasize robotics, structural health monitoring, and environmental sensing using hybrid neural networks and deep learning techniques. Grants & Awards : No awards explicitly listed, but his prolific publication record indicates sustained research activity. Advising & Labs : Advises students like B S Puliparambil and J Tomal. His lab actively collaborates on projects involving AI in agriculture, robotics, and structural engineering. Current initiatives include digital twins for human-robot collaboration and precision livestock monitoring systems. Labs/Teams : Leads a computational biology and AI lab focusing on multi-omics integration and smart agriculture solutions.

Daniel Pizarro PérezView profile

Professor

• Computer Vision
• Medical Imaging
• Smart Grids
• +3 more

Dr. Daniel Pizarro Pérez is a Professor in the Department of Electronics at the University of Alcalá, Spain. He is a member of the GEINTRA research group, which focuses on Electronic Engineering applied to Intelligent Spaces and Transport. He holds a doctoral degree from the University of Alcalá, completing his thesis on 'Localización de robots móviles en espacios inteligentes utilizando cámaras externas y marcas naturales' (2008), supervised by Dr. Manuel Ramón Mazo Quintas and Dr. Enrique Santiso Gómez. His research interests span computer vision, medical imaging, smart grid technologies, acoustic signal processing, and control systems. Notable projects include augmented reality applications in laparoscopic surgery, non-intrusive load monitoring using smart meters, and advanced control methodologies for power electronics. His work bridges theoretical advancements with practical applications in healthcare, energy systems, and robotics. Recent publications highlight contributions to neural radiance fields for minimally-invasive surgery, distributed acoustic sensing in submarine environments, and deep learning-based activity recognition via energy consumption. His research frequently integrates interdisciplinary approaches, such as combining computer vision with medical robotics and leveraging machine learning for real-time control systems. Dr. Pizarro’s work has been supported by grants and collaborations within the GEINTRA group, with applications in intelligent spaces, robotic navigation, and sensor fusion. He has also contributed to educational initiatives like the GEMS Erasmus+ project, emphasizing sensory module development for robotics education.

Spilianakis CharalamposView profile

Associate Professor

• 3D Epigenetics
• Genome Architecture
• Chromosomal Interactions
• +5 more

Charalampos Spilianakis is an Associate Professor at the University of Crete with a research affiliation at the Institute of Molecular Biology and Biotechnology (IMBB) of the Foundation for Research and Technology - Hellas (FORTH). His work focuses on the three-dimensional organization of the genome and its critical role in gene regulation within immune cells, particularly T cells. Dr. Spilianakis earned his PhD in 2003 from the University of Crete in Biochemistry, Molecular Biology, Cellular and Developmental Biology. His academic career has been dedicated to understanding how nuclear architecture influences cellular function and gene expression patterns. His research program investigates both cis and trans regulatory mechanisms of gene expression, with particular emphasis on how protein complexes generate and maintain long-range chromosomal interactions in immune cell populations. His laboratory employs an integrated approach combining biocomputing, molecular techniques, biochemical assays, advanced imaging, and genetic analyses to explore the field of 3D epigenetics. This work has significant implications for understanding immune cell differentiation and function. Analysis of Dr. Spilianakis' publication record reveals a consistent research trajectory focused on chromatin architecture and transcriptional regulation in immune cells. His contributions include developing protocols for chromosome conformation capture in primary T cells, elucidating SATB1's role in shaping the 3D enhancer network during T cell development, and investigating the nuclear periphery's role in microRNA gene localization. His work bridges molecular biology, immunology, and genomics to advance spatial genomics understanding. Based at IMBB-FORTH (Office A251, Lab A204), Dr. Spilianakis leads a research group that serves as an important hub for investigating the relationship between nuclear architecture and gene expression in the immune system. His laboratory combines cutting-edge molecular and imaging technologies to address fundamental questions about genome organization and its functional consequences in health and disease.

Tesh DagneView profile

Associate Professor

• Artificial Intelligence Governance
• Intellectual Property Law
• Data Rights Allocation
• +2 more

Tesh Dagne is an Associate Professor in the School of Public Policy and Administration at York University's Faculty of Liberal Arts & Professional Studies. He holds the Ontario Research Chair in Governing Artificial Intelligence and serves as a member of the graduate faculty in Law, Public Policy, and Science & Technology Studies. His research examines governance frameworks for emerging technologies with particular focus on AI applications in health, agriculture, and environmental sectors. His principal research domains include: Legal and ethical frameworks for AI governance Intellectual property rights in data pipelines Privacy norms in digital innovation Geographical indications for traditional knowledge 3D printing regulations Analysis of his scholarly output reveals sustained investigation into the intersections of intellectual property law with emerging technologies, including significant contributions to understanding data governance in agriculture, health technology regulation, and copyright implications in additive manufacturing. His work consistently addresses equity concerns in technological development. Dr. Dagne supervises graduate students through interdisciplinary programs and leads research projects funded by Connected Minds, focusing on governance challenges in AI-assisted health devices and sustainable digital agriculture.

Tuomas VirtanenView profile

Professor

• Audio signal processing
• Machine listening
• Sound source separation
• +5 more

Tuomas Virtanen is a Professor at Tampere University's Signal Processing Research Centre within the Faculty of Information Technology and Communication Sciences. His primary affiliation is the Computing Sciences department, where he leads the Audio Research Group . His work focuses on computational analysis of audio signals, machine listening, and acoustic scene understanding. Research Interests: Audio signal processing, content analysis of audio, sound source separation, acoustic scene classification, speech processing (including noise-robust ASR and speaker recognition), and machine learning techniques such as deep neural networks and statistical modeling. His group develops methods for sound event detection, localization, and tracking in complex acoustic environments. Key Contributions: Leading the DCASE (Detection and Classification of Acoustic Scenes and Events) challenges, developing open-source datasets like TUT Acoustic Scenes and STARSS, and advancing techniques in audio captioning, privacy-preserving audio processing, and multimodal learning. Notable Projects: Creation of the Audio Research Group , development of the Clotho audio captioning dataset, and pioneering work in zero-shot audio classification using semantic embeddings. His research bridges signal processing fundamentals with modern machine learning paradigms.

• Optical Communications
• High-speed Optical Transmission
• Optical Access Networks
• +3 more

Professor Jianming Tang is a leading academic at Bangor University's School of Computer Science and Engineering, holding the position of Professor in Optical Communications since 2011. He received his PhD in Optoelectronics from Bangor University in 1999 and has since developed an internationally recognized research program in optical networking technologies. His research focuses on: High-speed optical transmission systems Optical access networks and fiber-wireless convergence Digital signal processing for telecommunications Ultrafast dynamics of optical devices Secure communication systems Analysis of his recent publications (2024-2025) reveals strong emphasis on next-generation access networks, including fiber-wireless convergence, physical layer security using chaotic encryption, flexible transceivers for PON systems, neural network applications in optical communications, and advanced modulation techniques. His work consistently bridges theoretical innovation with experimental validation. Scientific Awards: The Royal Society Brian Mercer Feasibility Award (2008) Fellow of The ERA Foundation (2008) Visiting Professor, University of Electronic Science and Technology of China (2006) Professor Tang leads a highly productive research team that has secured £3.8M in research funding across 13 grants. His group focuses on optical transmission, dynamic networking, and ultrafast optical switching for future networks. He maintains active industry collaborations through projects like the EPSRC TRANSNET Programme and industrial partnerships with companies including Huawei and Oclaro.

• Signal Processing
• Antenna Engineering
• Radar Imaging
• +5 more

Amir Masoud Molaei is a Research Fellow at the School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast. His research focuses on advanced radar imaging techniques, antenna engineering, and signal processing, with particular emphasis on near-field localization, MIMO systems, and computational imaging using metasurface antennas. He has collaborated extensively on projects involving millimeter-wave systems, sparse array configurations, and security applications. His work integrates theoretical models like Kirchhoff migration with experimental validation, emphasizing hardware-efficient designs and algorithmic improvements. Key themes include overcoming challenges in mutual coupling effects, optimizing dynamic antenna configurations, and enhancing 3D imaging resolution. He has explored applications ranging from medical imaging to security systems, with a strong focus on real-time processing and experimental validation. Notable contributions include pioneering studies on reconfigurable metasurface antennas for radar and computational imaging, as well as algorithmic advancements in direction-of-arrival estimation and mixed-field source localization. His research bridges electromagnetic theory, signal processing, and practical hardware implementations, often addressing trade-offs between computational efficiency and accuracy. Molaei has published over 40 papers since 2021, with a focus on IEEE journals and conferences. His work frequently addresses challenges in signal reconstruction, sparse sampling techniques, and the integration of machine learning with traditional signal processing methodologies.