Find Academic Supervisors

Kin K. LeungView profile

Professor

• Wireless Communications
• Communication Networks
• Machine Learning
• +4 more

Kin K. Leung is the Tanaka Chair Professor in the Electrical and Electronic Engineering and Computing Departments at Imperial College London. He serves as the Head of the Communications & Signal Processing Group (2009-2024) and Deputy Director of the University Defence Research Centre in Signal Processing. Previously, he held senior technical roles at AT&T Bell Labs and Lucent Technologies. Education: B.S. from Chinese University of Hong Kong (1980), M.S. and Ph.D. from University of California, Los Angeles (1982, 1985). Research Interests: Focuses on wireless technologies, communication networks, stochastic modeling, machine learning, optimization, and emerging quantum computing applications. His work integrates theoretical frameworks with practical implementations in multi-antenna systems, cross-layer network designs, and distributed quantum architectures. Publication Trends: Recent works (2021-2025) demonstrate a strong focus on quantum computing integration with networking systems, federated learning optimizations for edge devices, and reinforcement learning solutions for resource allocation in wireless environments. Awards and Honors: Fellow of Royal Academy of Engineering (2022) IEEE Fellow (2001) IET Fellow (2021) Royal Society Wolfson Research Merit Award (2004-2009) IEEE Communications Society Leonard G. Abraham Prize (2021) IEEE Best Survey Paper Award (2022) Grants and Leadership: Principal Investigator for EPSRC TITAN/HASC Com Hubs, DCIT Centre, and DQC & App (distributed quantum computing). Leads the Communications & Signal Processing Group and co-directs the School of Convergence Science in Space, Security and Telecoms.

Veljko MilutinovicView profile

Professor

• Microprocessor architecture
• VLSI design
• Data mining
• +9 more

Veljko Milutinovic is a Full Professor at the School of Electrical Engineering, University of Belgrade since 1990. He has also held academic positions at Purdue University (1982-1989) and consulted globally for institutions like IEEE and ACM. Current role: Computer Area Director, teaching VLSI, Data Mining, and E-Business Previous roles: Tenure Track Assistant Professor at Purdue University International collaborations: EU FP7 projects, Raiffeisen Bank, Wall Street Journal His research spans microprocessor architecture , VLSI design , data mining , and semantic web , focusing on energy-efficient architectures and e-business infrastructure. He pioneered DARPA's 200MHz GaAs RISC microprocessor and 4096-node systolic arrays. Recent work trends include: Technical and semantic interoperability in e-government Customer satisfaction accelerators in e-commerce 3D semantic web visualization Data mining for inverse engineering Academic-industry co-design methods Global university collaboration frameworks Scientific awards include: IEEE Life Fellow (2003) Foreign Member, Montenegrin Academy (2018) IPSI Awards (2007-2010) for eGov projects Best Method papers ranked #1 in Google search Supervised PhD students at Purdue, Belgrade, and Valencia Universities, with significant contributions to cache coherence, GaAs processors, and mobile network security. His publications (over 100 SCI papers) have been cited over 4000 times on Google Scholar.

Hans Zanna Munthe-KaasView profile

Professor

• Differential Geometry
• Lie Group Techniques in Geometric Integration
• Computational Mathematics
• +3 more

Hans Zanna Munthe-Kaas is a Professor at the Department of Mathematics, University of Bergen since 2005 and an Adjunct Professor (Prof. II) at UiT - The Arctic University of Norway since 2022. He has held previous academic roles at NTNU and the University of Bergen. Education Dr.Ing. (PhD), Department of Mathematical Sciences, NTNU (1989) Siv.Ing. (MSc), Department of Mathematical Sciences, NTNU (1986) Research Interests focus on Differential Geometry , Lie Group Techniques in Geometric Integration , and Computational Mathematics , with applications to numerical methods and parallel computing. His work explores algebraic structures like Post-Lie and pre-Lie-Rinehart algebras, and their role in geometric integration and manifold integration. Scientific Awards and Memberships 1995 Carl-Erik Fröberg Prize in Numerical Analysis 1990 Exxon Mobile Research Award for Best PhD, NTNU 1986–1989 Jubilee Scholar Scholarship, NTNU 2016 Elected Member, The Norwegian Academy of Science and Letters 2012 Elected Member, The Royal Norwegian Society of Sciences and Letters (DKNVS) 2007 Elected Member, The Norwegian Academy of Technological Sciences (NTVA) Advising and Leadership includes supervising 9 PhD students, organizing 25 international scientific meetings, and serving as Editor-in-Chief of Foundations of Computational Mathematics , President of the Norwegian Mathematical Society, and Director of the Lie–Størmer Center .

Onur MutluView profile

Professor

• Computer architecture
• Bioinformatics
• Computer memory systems
• +7 more

Onur Mutlu is a Full Professor of Computer Science at ETH Zurich (since 2015), with adjunct professor positions at Carnegie Mellon University (since 2016) and Bilkent University (since 2015). His academic career spans prestigious institutions including Carnegie Mellon University where he served as Assistant Professor (2009-2013) and Strecker Early Career Endowed Professor (2013-2016). His research focuses on computer architecture, particularly memory systems, with expertise in: Computer memory systems and DRAM architecture Multi-core processor design Fault tolerance and reliability Hardware/software interactions Systems security related to hardware Emerging memory technologies Dr. Mutlu's work has significantly impacted both academic research and industry practices. His discovery of the RowHammer problem created a new field at the intersection of hardware reliability and systems security. His research on memory controllers, flash memory reliability, and emerging memory technologies has been adopted by major technology companies including Samsung, Intel, IBM, and Microsoft. His numerous scientific awards include the IEEE Computer Society Harry H. Goode Memorial Award (2025), IFIP Jean-Claude Laprie Award (2024), Huawei OlympusMons Award (2023), IEEE Computer Society Edward J. McCluskey Technical Achievement Award (2020), and ACM SIGARCH Maurice Wilkes Award (2019). He is an IEEE Fellow (2018), ACM Fellow (2017), and member of Academia Europaea (2018). Dr. Mutlu has received significant industry recognition with Faculty Awards from Google, Facebook, HP, Huawei, IBM, Intel, Microsoft, NSF, and VMware. His work has earned over 20 Best Paper awards and 12 papers selected for IEEE Micro's Top Picks as some of the most influential papers in computer architecture. He maintains strong industry connections, having worked at Microsoft Research (2006-2009), Intel (multiple summers), AMD (multiple summers), VMware (2016), and Google (2016), enabling direct technology transfer of his research ideas into commercial products.

Camille SchreckView profile

Researcher

• Computer Graphics
• Physics-based Simulation
• Geometric Modeling
• +2 more

Camille Schreck is a researcher in Computer Graphics currently holding an Inria Starting Faculty Position (ISFP) at Inria Nancy within the MFX Team. She has been actively contributing to the field of computer graphics with a focus on physics-based simulation and geometric modeling since completing her PhD in 2016. Her educational background includes an engineering degree from ENSIMAG (Grenoble INP) in 2013, followed by a PhD at the University of Grenoble-Alpes supervised by Stefanie Hahmann and Damien Rohmer. Between 2016 and 2020, she conducted postdoctoral research at IST Austria in Chris Wojtan's group. Dr. Schreck's research spans physics-based simulation of natural phenomena, geometric modeling, and computational fabrication techniques. Her work demonstrates particular expertise in simulating deformable materials like paper, water dynamics, and developing novel methods for 3D printing and shape manipulation. She has successfully bridged theoretical computer graphics with practical applications in digital fabrication. Her publication record shows consistent high-impact contributions to top computer graphics venues including SIGGRAPH, Eurographics, and Computer Graphics Forum, with recent work focusing on star-shaped particle simulation, self-shaping 3D printed structures, and efficient mesh processing techniques. The progression of her research demonstrates a clear trajectory from fundamental paper simulation to increasingly complex physical phenomena and fabrication methods. Young Research Fellow of Eurographics France (YFR EGFR) - 2024 Dr. Schreck serves on numerous program committees including SIGGRAPH, Eurographics, and Shape Modeling International. She teaches courses in computer graphics and parallelism at ENSG-GeoRessources and Telecom Nancy, both part of Université de Lorraine. Her teaching spans from 2020 to the current 2024-2025 academic year. As a member of the MFX research team at LORIA (Inria Nancy), she collaborates on advancing the state of the art in physics-based animation and geometric modeling, with her StarDEM project representing a significant contribution to particle simulation methods.

Michael QuellView profile

Researcher

• Semiconductor Technology
• Computational Engineering
• Numerical Methods
• +3 more

Michael Quell is a Researcher at the Microelectronics Research Department (E360-01) at TU Wien. His work focuses on numerical methods for semiconductor process simulation, including level-set techniques, hierarchical mesh processing, and high-performance computing. He holds a Dipl.-Ing. (Master's equivalent) and a Dr.techn. (PhD) in technical sciences. His research emphasizes parallel algorithms for material flow simulation, adaptive mesh refinement, and TCAD applications. Education: Dipl.-Ing. and Dr.techn. in Technical Sciences Research interests span computational engineering, numerical analysis, and semiconductor fabrication modeling. Key contributions include shared-memory parallel implementations of the Fast Marching Method, hierarchical re-distancing algorithms, and feature detection for topography simulations. His work often addresses challenges in nanoscale fabrication processes and multi-material wet etching. Collaborations involve projects on parallel mesh adaptation frameworks and quantum transport simulations. He has contributed to advancing computational tools for semiconductor process design and manufacturing optimization.

Stefan HaeusslerView profile

Associate Professor

• Production Planning
• Logistics Management
• Workload Control
• +7 more

Stefan Haeussler is an Associate Professor at the Department of Information Systems, Production and Logistics Management within the University of Innsbruck , Austria. His academic career spans since 2009, starting as a University assistant while completing his PhD in Management. He holds dual diplomas in Business Administration (2009) and Political Science (2010) from the same university. Specializing in production and logistics management, Häussler combines optimization techniques with machine learning approaches to address complex manufacturing challenges. His research focuses on Workload control systems Order release mechanisms Lead time management Reinforcement learning applications Semiconductor manufacturing optimization Behavioral operations in supply chains Recent publications highlight his work on integrated production planning , explainable AI for powertrain control , and dynamic workload allocation . He actively presents at major conferences like Winter Simulation Conference, EURO, and International Working Seminar on Production Economics. Häussler also teaches master's level courses and supervises thesis work in production economics, while serving as a guest lecturer on topics at the intersection of AI and manufacturing.

• Audio Processing
• Machine Learning
• Sound Event Detection
• +3 more

Paul Primus is a researcher at the Institute of Computational Perception, Johannes Kepler University Linz, specializing in audio processing and machine learning. His work focuses on sound event detection, acoustic scene classification, and language-based audio retrieval, with significant contributions to the DCASE (Detection and Classification of Acoustic Scenes and Events) challenges. Education: Dr. (PhD) MSc BSc Research Interests: Primus's research bridges audio signal processing and deep learning, addressing real-world challenges in machine listening. His work emphasizes device invariance, data efficiency, and transformer architectures for audio analysis. Key contributions include knowledge distillation for audio retrieval, multi-stage transformer training, and novel approaches to language-audio interaction. He actively explores low-complexity solutions suitable for embedded systems and edge deployment. Publication Trends: Primus's recent work (2023-2025) shows a clear trajectory toward multimodal audio-language systems, leveraging transformers and pretraining techniques. His publications increasingly focus on data efficiency, device generalization, and practical deployment constraints, as evidenced by his DCASE challenge submissions. The integration of metadata and cross-modal alignment represents a growing research emphasis. Activities: Adversarial Robustness in Data Augmentation (2020) Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification (2019) Labs and Teams: Primus is a core member of the Institute of Computational Perception at JKU, which leads research in computational audio analysis. The institute maintains strong participation in international challenges like DCASE and collaborates extensively on audio transformer development and language-audio interaction systems.

Martin FedaView profile

Researcher

• Radiosity
• Photorealistic Image Synthesis
• Parallel Graphics Algorithms
• +1 more

Martin Feda is an Associated Researcher at the Institute of Computer Graphics, Vienna University of Technology, where he previously served as Assistant Professor. His research focuses on advancing radiosity methods for photorealistic image synthesis, with significant contributions to algorithmic efficiency and visual quality in global illumination rendering. Feda's primary research interests include radiosity, photorealistic image synthesis, and parallel graphics algorithms. He has pioneered techniques for stochastic radiosity, progressive refinement, and parallel implementations to accelerate computation. Key innovations involve hierarchical subdivision algorithms, methods for reducing shadow leaks without explicit meshing, improvements to intermediate radiosity images through directional light, and overshooting techniques to speed up progressive radiosity. His work consistently bridges theoretical advancements with practical applications for handling highly complex scenes. Analysis of his 1991-1997 publication record reveals a clear evolution in radiosity research: early work established parallel implementations on transputers and foundational radiosity algorithms, while later contributions developed sophisticated stochastic and hierarchical methods. The trajectory shows increasing emphasis on Monte Carlo techniques and computational optimizations to achieve greater efficiency and visual fidelity in global illumination, with consistent publication in top-tier graphics venues like Eurographics and Computer Graphics Forum.

Lukas RadlView profile

Researcher

• Computer Graphics
• Computer Vision
• Machine Learning
• +4 more

Lukas Radl is a University Assistant and PhD Student at the Institute of Visual Computing, Graz University of Technology, where he works on 3D Scene Representations for View Synthesis under the supervision of Markus Steinberger. His research focuses on advancing real-time rendering techniques, particularly in Neural Radiance Fields (NeRF) and Gaussian Splatting, to bridge digital and physical world representation. Education: Master of Science in Computer Science (with distinction), Graz University of Technology, 2018-2023 Bachelor of Science in Software Engineering, Graz University of Technology, 2018-2023 Research Focus: Radl's work intersects Computer Graphics, Computer Vision, Machine Learning, and Parallel Processing. He pioneers practical implementations of Radiance Field Representations, addressing critical challenges in view consistency, anti-aliasing, and real-time performance for interactive applications. His innovations enable robust rendering in virtual reality and complex lighting scenarios through novel geometric and neural approaches. Publication Impact: Recent publications (2024-2025) demonstrate a cohesive trajectory toward production-ready radiance field systems. Key advances include sorting algorithms for view consistency (StopThePop), anti-aliasing frameworks for Gaussian Splatting (AAA-Gaussians), and VR-optimized pipelines (VRSplat). These contributions establish new standards for real-time performance while maintaining visual fidelity across diverse hardware platforms. Scientific Recognition: Dean's List (top 5% of students) at Graz University of Technology (2019, 2020) Mentorship & Service: Radl actively shapes academic discourse as a reviewer for premier venues (CGF, ICCV, TVCG) and mentors students through open projects in real-time rendering. His teaching portfolio spans exercise coordination for core visual computing courses since 2020, with current leadership in Real-Time Graphics and Computer Graphics instruction. He fosters talent through student projects advancing Gaussian Splatting implementations. Research Ecosystem: Embedded in Graz University of Technology's Institute of Visual Computing, Radl collaborates within a specialized team focused on radiance field optimization. The group maintains active pipelines for NeRF and Gaussian Splatting research, with strong industry connections evidenced by his upcoming Meta Reality Labs internship. Current projects target foveated rendering, geometric consistency, and editing capabilities for next-generation AR/VR systems.

Günther RaidlView profile

Associate Professor

• Combinatorial Optimization
• Heuristic Optimization
• Metaheuristics
• +7 more

Günther Raidl is an Associate Professor and Head of the Algorithms and Data Structures Group at the Institute of Computer Graphics and Algorithms, Faculty of Informatics, TU Wien. He holds a Dipl.-Ing. (1992), Ph.D. (1994), and Habilitation (2003) from TU Wien. His research focuses on combinatorial optimization, heuristic methods, and hybrid optimization techniques, addressing large-scale problems in transportation, network design, and cutting/packing. He leads a group of 1 PostDoc, 8 PhD candidates, and collaborates with institutions like the Vienna Graduate School on Computational Optimization (VGSCO). Education: Dipl.-Ing. in Computer Science (1992), TU Wien Ph.D. in Computer Science (1994), TU Wien Habilitation (2003), TU Wien Research Interests: Raidl’s work combines exact and heuristic optimization techniques, including mixed-integer programming, metaheuristics, and matheuristics. Applications span transportation systems (e.g., electric vehicle routing, bike-sharing systems), network design, and bioinformatics. His group leverages high-performance computing resources, such as the Vienna Scientific Cluster (VSC). Publications & Awards: Over 115 reviewed articles in journals/conferences like INFORMS Journal on Computing and Evolutionary Computation. Notable recognition includes the EvoStar 'Old Croc' Award (2012) for contributions to evolutionary computation. Advising & Grants: Supervises 8 funded PhD students and contributes to the Vienna Graduate School’s DK funding (€20,000/year for personnel and travel). Labs/Teams: Algorithms and Data Structures Group at TU Wien, collaborating with researchers like Monika Henzinger and Nysret Musliu.

Florian MüllerView profile

Associate Professor

• History of Archaeology
• Collection History
• Historical Museology
• +6 more

Florian Müller is an Associate Professor and Director of the Institute of Archaeology at the University of Innsbruck. With a habilitation thesis on the 1912–1913 excavations in Aguntum, his career spans roles as a researcher, educator, and museum curator since 2009. He leads the Archaeological University Museum Innsbruck (since 2012) and specializes in the history of archaeology, museum studies, and Roman culture in Tyrol. Born 1977 in Innsbruck Diploma in Classical Archaeology and Ancient History (2003) Habilitation on Aguntum excavations (2017) His research focuses on the history of archaeological science , collection provenance , and reception of antiquity , particularly examining Romans in Tyrol and Southern Italian cultures. Articles reveal expertise in museum ethics, fieldwork from Mesolithic to modern eras, and interdisciplinary collaborations. Notable scientific awards include the 2019 Innsbruck City Research Prize and multiple university grants. He organizes academic events like the AKMe doctoral program colloquia and serves on committees for the Austrian Academy of Sciences.

Monika LanzenbergerView profile

Assistant Professor

• Semantic Web
• Ontology Alignment
• Information Visualization
• +4 more

Monika Lanzenberger is an Assistant Professor at the Institute of Software Technology and Interactive Systems, Faculty of Informatics, Vienna University of Technology. Her research focuses on the intersection of Semantic Web technologies, ontology alignment, and information visualization. She has established herself as a notable researcher in visual ontology alignment through her development of the AlViz tool and related publications. Dr. Lanzenberger received her PhD from the Vienna University of Technology, Faculty of Informatics in 2003 and her MSc in Computer Science from the same institution in 2001. She completed a Post-Doc Fellowship (ERCIM) with the NTNU, Department of Computer and Information Science, Trondheim, Norway (February - October 2005) and with the Centre for IT Innovation (CITI) at the CRP Henri Tudor, Luxembourg (November 2005 - July 2006). Her primary research interests center around Semantic Web and Ontology-based Data, with specific focus on ontology alignment and visualization techniques. She has made significant contributions to the field through her work on visual ontology alignment tools, particularly the AlViz system. Her research also extends to Human Computer Interaction, Information Visualization techniques, feminist perspectives on computer science, and online learning and didactics. She has published extensively in top conferences and journals in these areas, with a particular emphasis on making ontology alignment more accessible through visualization. Dr. Lanzenberger has received recognition for her work, including an Outstanding Paper Award in 2002 for her research on the evaluation of navigation in hypertext learning systems. She is an active member of the scientific community, serving as a reviewer for international conferences and co-organizer of workshops in her field. As an educator, Dr. Lanzenberger has taught numerous courses including Information Visualization, Women in Science and Technology, Fundamentals of Methodical Working, and Semi-Automatic Information and Knowledge Systems. She has supervised multiple student projects, Bachelor's theses, and Master's theses, particularly in areas related to information visualization and semantic technologies. She is a member of several professional organizations including IEEE, ÖGAI, OCG, and GI, demonstrating her active engagement with the broader computer science community.

• Algorithms
• Graph Theory
• Dynamic Algorithms
• +4 more

Kathrin Hanauer is an Assistant Professor at the University of Vienna, where she is affiliated with the Research Group Theory and Applications of Algorithms and the Research Network Data Science. She conducts research in the design, analysis, and experimental evaluation of fast algorithms, with a focus on Algorithm Engineering connecting theoretical foundations with practical implementations. Her research interests include: Algorithm Engineering for practical algorithm implementation Dynamic algorithms for efficiently handling changing data Graph algorithms and network analysis Reachability problems on directed graphs Ranking problems, particularly the NP-hard Feedback Arc Set problem Network analysis, motif search, and subgraph counting Dr. Hanauer's recent publications demonstrate a strong focus on dynamic graph algorithms, with significant contributions to reachability queries, subgraph counting, and datacenter network optimization. Her work spans both theoretical algorithm design and practical implementation, often with C++ software projects. Notable contributions include the O'Reach algorithm for faster reachability queries in large graphs and several dynamic algorithms for subgraph counting and network analysis. Her scientific contributions: O'Reach: A novel approach to reachability queries in large graphs that outperforms previous methods Dynamic algorithms for four-vertex subgraph counting with efficient update operations Work on demand-aware link scheduling for reconfigurable datacenters Interdisciplinary research on normative reasoning with Aristotelian diagrams Dr. Hanauer actively supervises student research, with numerous completed theses focusing on dynamic graph algorithms, geometric algorithms, and reachability problems. Her lab maintains several software projects related to graph algorithms, including a modular algorithms library for dynamic graphs written in C++ and specialized implementations for reachability queries and subgraph counting.

• Reconfigurable Computing
• Parallel Computing
• FPGA Accelerators
• +4 more

Prasanna Viktor is a Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California (USC), holding the Charles Lee Powell Chair in Engineering. He also serves as Director of the Center for Energy Informatics and has held leadership roles in interdisciplinary research centers such as the USC Infosys Center for Advanced Software Technologies. With a BE from Bangalore University, ME from Indian Institute of Science, and PhD from Pennsylvania State University, he is a globally recognized expert in reconfigurable computing, FPGA accelerators, and parallel computing. His research focuses on high-performance architectures for applications in networking, security, HPC, and machine learning. Over 25 years, he has secured research grants totaling over $50M, including $12.9M from 2016–2021. He has advised over 70 doctoral students and published over 600 papers, earning 22 best paper awards. His work has led to IP cores with improved throughput, latency, and energy efficiency. Prasanna is a Fellow of the IEEE, ACM, and AAAS, and an elected member of Academia Europaea. He has received prestigious awards such as the W. Wallace McDowell Award (2015) and the Distinguished Alumnus Award from IISc (2019). He currently serves as Editor-in-Chief of the Journal of Parallel and Distributed Computing. He leads interdisciplinary efforts in energy informatics and smart oilfield technologies, bridging computer science, engineering, and energy sectors. His contributions include foundational work in reconfigurable computing and FPGA-based accelerators for diverse applications.