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Emma MooreView profile

Professor

• Sociolinguistics
• Syntax
• Language Variation
• +12 more

Professor Emma Moore is a leading sociolinguist at the School of English, University of Sheffield . Specializing in the social dimensions of language, her work integrates methodologies from anthropology and sociology to investigate how linguistic variation constructs identity and social affiliations. Research focus: Sociolinguistic style, dialect contact, youth language, identity negotiation, and community-based fieldwork Key projects: Adolescence and grammar (1999-), Isles of Scilly dialect (2008-), language and inequality (2014-), language perception software (2016-) Educational background : PhD in Sociolinguistics, University of Manchester Stanford University (USA) during PhD research Research trends across her 2021-2025 publications reveal interdisciplinary exploration of: Socio-syntactic variation Clinical linguistics (2025 MDS-UPDRS studies) Digital discourse post-pandemic Indexicality and cognitive representations Dialect contact in insular communities Educational policy implications Scientific recognition : British Academy Mid-Career Fellow (2019-2020) Elected Fellow, Royal Anthropological Institute (2014) AHRC/BA funded research projects (1999-2015) Research group leadership : Mentored 9 PhD students (2004-2024) and supervised 3 undergraduate SURE projects, including analyses of: Gender in rap performance Language style and workplace inequality Oral history digitization Professional contributions : Editorial Board: Language in Society (2015-), Gender and Language (2011-2017) External Examiner: Lancaster University MA in English Language (2013-2017) Collaborative software development for dialect perception testing

Behnaam AazhangView profile

Professor

• Signal and Data Processing
• Information Theory
• Neuroengineering
• +4 more

Behnaam Aazhang is the J.S. Abercrombie Professor of Electrical and Computer Engineering at Rice University and Director of the Rice Neuroengineering Initiative (NEI). He holds a B.S., M.S., and Ph.D. from the University of Illinois at Urbana-Champaign. His roles include leading the multi-university Rice Neuroengineering Initiative and directing the Center for Neuroengineering. He has held an Academy of Finland Distinguished Visiting Professorship (FiDiPro) at the University of Oulu (2006-2014) and received an Honorary Doctorate from the University of Oulu in 2017. Education: Ph.D. in Electrical Engineering, University of Illinois at Urbana-Champaign (1986) M.S. in Electrical Engineering, University of Illinois at Urbana-Champaign (1983) B.S. in Electrical Engineering, University of Illinois at Urbana-Champaign (1981) Research Interests: Dr. Aazhang’s work focuses on signal/data processing, information theory, and neuroengineering applications. Key areas include: Neuronal circuit connectivity and learning impacts Real-time closed-loop neuromodulation for neurological disorders (epilepsy, Parkinson’s, depression) Patient-specific cardiac pacing systems Cybersecurity in cloud computing Awards & Honors: 2022 Rice Outstanding Doctoral Thesis Advisor Award 2019 SIGMOBILE Test of Time Award 2017 Honorary Doctorate (University of Oulu) 2013 IEEE Communication Society Advances in Communication Award AAAS and IEEE Fellowships (2012 and 1999) Grants & Advising: His research is supported by multi-university collaborations and grants. He has advised numerous graduate students in electrical engineering and neuroengineering, though specific names are not listed here. Labs & Teams: Leads the Aazhang Lab and the Rice Neuroengineering Initiative, focusing on translational technologies for neurological and cardiac disorders, including non-invasive neuromodulation and cloud security systems.

Zsolt KiraView profile

Assistant Professor

• Robotics
• Machine Learning
• Artificial Intelligence
• +6 more

Zsolt Kira serves as an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology's College of Computing, with additional affiliations at the Georgia Tech Research Institute and as Associate Director of ML@GT. He leads the Robotics Perception and Learning (RIPL) Lab, driving research at the intersection of machine learning and robotics. Dr. Kira earned his Ph.D. in 2010 under Professor Ron Arkin, establishing foundational expertise in robotics and AI before transitioning to his current academic role after industry experience at SRI International Sarnoff. His research pioneers beyond supervised learning through unsupervised, semi-supervised, self-supervised, and continual/lifelong learning frameworks, while advancing distributed perception via multi-modal fusion and cross-robot information integration. This dual focus addresses core challenges in robotic autonomy and sensor processing. Analysis of his 15 most recent publications reveals dominant trends in embodied AI systems, robust foundation model adaptation, and multimodal learning architectures. Key themes include neural radiance field applications, reinforcement learning for locomotion, and novel benchmarks for memory evaluation in agents. While specific advisees and grants aren't documented in the source material, his RIPL Lab leadership implies active graduate mentorship and research funding acquisition. The lab's work directly enables next-generation robotic systems through algorithmic innovation in perception and learning. The RIPL Lab operates as a hub for developing machine learning techniques that solve difficult perception problems in robotics, with particular emphasis on unsupervised learning paradigms and distributed multi-robot systems that push the boundaries of autonomous operation.

James R. FienupView profile

Professor

• Imaging Science
• Phase Retrieval
• Unconventional Imaging
• +8 more

James R. Fienup is the Robert E. Hopkins Professor of Optics at the University of Rochester's Institute of Optics, with additional appointments as Distinguished Scientist at the Laboratory for Laser Energetics, Professor at the Center for Visual Science, Professor of Electrical and Computer Engineering, and Affiliated Faculty at the Goergen Institute for Data Science and Artificial Intelligence. His office is located at Wilmot 410, 275 Hutchison Rd., Rochester, NY. Education PhD in Applied Physics from Stanford University (1975) MS in Applied Physics from Stanford University (1972) BA in Physics & Mathematics (magna cum laude) from Holy Cross College (1970) Research Focus Professor Fienup's research specializes in imaging science , with emphasis on phase retrieval algorithms, unconventional imaging techniques, and wavefront sensing. His work spans computational methods for image reconstruction, sparse-aperture systems, and synthetic-aperture imaging. Recent innovations include applying machine learning to wavefront control and developing advanced digital holography techniques for 3D imaging through atmospheric turbulence. Publication Trends His recent articles (2018-2024) demonstrate a strong focus on computational imaging techniques, particularly phase retrieval algorithms applied to optical metrology and wavefront correction. Key themes include multi-plane digital holography, coronagraphic wavefront control for astronomical applications, machine learning-enhanced sensing, and novel approaches for segmented-aperture systems. His work consistently bridges theoretical optics with practical instrumentation challenges. Awards and Honors Lifetime Achievement Award, Hajim School of Engineering (2019) Emmett N. Leith Medal, Optical Society of America (2013) National Academy of Engineering Member (2012) Distinguished Visiting Scientist, JPL (2009) Fellow of OSA and SPIE International Prize in Optics (1983) Rudolf Kingslake Medal (1979) NSF Graduate Fellow (1970-1972) Professional Activities Professor Fienup has served as Editor-in-Chief of the Journal of the Optical Society of America A (1998-2003) and held editorial roles at Applied Optics and Optics Letters . He consults for NASA (James Webb Space Telescope, Hubble), national laboratories, and aerospace companies, and holds five patents in optical systems design.

• Multimedia Signal Processing
• Computer Networks
• Communication Engineering
• +3 more

Jiro Katto is a Professor at Waseda University's School of Fundamental Science and Engineering, where he has been conducting research and teaching since 1999. He received his Ph.D. from the University of Tokyo and has established himself as a leading researcher in multimedia signal processing and computer networks. His academic journey includes positions as Associate Professor (1999-2004), Professor (2004-present), and Director at NEDO (2004-2008), along with research experience at NEC C&C Laboratories (1992-1999) and a Visiting Scholar position at Princeton University (1996-1997). Professor Katto's research interests focus on Multimedia Signal Processing and Computer Networks, with particular expertise in video compression, 5G network performance, and learned image compression techniques. His work bridges theoretical advancements with practical implementations, as evidenced by his extensive publications in top-tier conferences and journals. His research group has made significant contributions to point cloud compression, latency compensation in remote systems, and hardware-accelerated video encoding for UHD streaming. His publication record is impressive, with 276 papers cited 3,323 times in Scopus and 6,169 times in Google Scholar, reflecting his substantial impact in the field. His recent work shows a strong trend toward applying deep learning techniques to traditional signal processing problems, particularly in the areas of image and video compression, where his team has developed novel approaches to improve compression efficiency while reducing computational complexity. Electric Telecommunications Promotion Foundation Telecommunications System Technology Award (2023) Takayanagi Kenjiro Foundation Takayanagi Kenjiro Achievement Award (2020) Institute of Image Information and Television Engineers Fellow (2020) Institute of Electronics, Information and Communication Engineers Fellow (2015) IEICE Communications Society Activity Contribution Award (2006) IEICE Academic Encouragement Award (1995) SPIE VCIP 1991, Best Student Paper Award (1991) Professor Katto has served on numerous prestigious committees including IEEE ComSoC Tech News Editorial Board, IEEE Technical Program Committees for major conferences (Globecom, ICC, ICIP), and editorial boards for several academic journals. His leadership in the academic community extends to chairing conferences like IWAIT 2011 and serving as Editor-in-Chief for journals in his field. His research has practical applications in commercial 5G networks, video streaming services, and remote monitoring systems, demonstrating the real-world impact of his work.

• Robust Statistics
• Dimension Reduction
• Meta-Analysis
• +3 more

Professor Luke Prendergast is the Deputy Dean of the School of Computing, Engineering & Mathematical Sciences (SCEMS) at La Trobe University (LTU) and holds a Professorship in the Department of Mathematics and Statistics. He previously served as Head of Department (2014–2020) and led LTU's Statistics Consulting Platform. His research focuses on robust statistics, meta-analysis, dimension reduction, and applied statistics, leading the DRAMA research group. Collaborations span fields like endocrinology, disability studies, and respiratory health. He actively contributes to research grants, including projects on Prader-Willi syndrome and exercise for disability populations. Professor Prendergast's recent work emphasizes statistical software development (e.g., the rquest package) and applications in biostatistics, such as metabolomics analysis and health intervention fidelity. His articles address topics like quantile-based hypothesis testing, geospatial accessibility for disability care, and motivational interviewing efficacy. Professional roles include NHMRC grant review panels, editorial boards for Nutrients and Respirology , and leadership in the Statistical Society of Australia (SSA Vic). His teaching includes courses in meta-analysis, linear models, and data-based critical thinking. Grants funded projects on exercise programs for cerebral palsy populations and community-university partnerships for disability inclusion. Luke's work bridges statistical theory with real-world health challenges, emphasizing robust methodologies and interdisciplinary collaboration.

• Computational Fluid Dynamics
• Internal Combustion Engines
• Cavitation
• +13 more

Professor Manolis Gavaises is a leading academic in the field of mechanical engineering and computational fluid dynamics at City St George's, University of London, where he holds the position of Professor in the School of Engineering and Mathematical Sciences. He earned his PhD from Imperial College London and has been a faculty member since 2001, progressing to full Professor in 2009. His research is centered on advanced modeling of multi-phase flows, cavitation, and fuel injection systems, with extensive collaborations across Europe and industry partners such as Delphi, Caterpillar, and BP. Education: DIC, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 PhD, Mechanical Engineering, Computational Fluid Dynamics, Imperial College London, 1997 Diploma (5 years), Mechanical Engineering, National Technical University of Athens, 1992 His research interests span computational fluid dynamics, cavitation, fuel injection, atomization, high-pressure and supercritical flows, and alternative fuels . He has developed advanced numerical models and experimental techniques, including X-ray phase contrast imaging and high-pressure test rigs. His work integrates fundamental DNS and LES simulations with industrial applications in automotive, marine, aerospace, and medical devices such as heart valves. The recent publications reflect a strong trend toward real-fluid thermodynamic modeling (e.g., PC-SAFT), multi-component fuel behavior, cavitation erosion, and advanced diagnostics . His research increasingly incorporates machine learning and high-fidelity imaging to understand complex flow phenomena across energy, transportation, and biomedical domains. Scientific Awards and Recognitions: Richard Way Prize (1998) Arch T. Collwell Merit Award (1998) Best Oral Paper, SAE World Congress (2006) PE Publication Award, IMechE (2007) Best Presentation Award, Engine Combustion Processes (2009) Fellow, IMechE (2013) Fellow, IMA (2015) As a dedicated mentor, Professor Gavaises has supervised 13 PhDs to completion and currently guides 23 doctoral students. He has secured over €16 million in EU and UK funding, including multiple Horizon 2020 Marie Skłodowska-Curie ITN projects (CAFÉ, HAOS, IPPAD), which support 46 early-career researchers globally. He has created academic opportunities for post-docs and junior faculty, significantly advancing the research profile of his institution. He leads the International Institute of Cavitation Research (IICR), co-founded in 2011 with partners from Loughborough University, TU Delft, and Imperial College, supported by The Lloyd’s Register Foundation. His lab maintains strong experimental capabilities, including a 2000bar pressure flow rig with micro-transparent nozzles and collaborations with Argonne National Laboratory for X-ray imaging.

Benjamin BusamView profile

Researcher

• 3D Computer Vision
• Multi-Modal Sensor Fusion
• Collaborative Robotics
• +6 more

Dr. Benjamin Busam is a Senior Research Scientist at the Technical University of Munich , affiliated with the Chair for Computer Science Applications in Medicine under Prof. Nassir Navab. Starting September 2025, he will hold the Professorship for Photogrammetry and Remote Sensing at TUM. His career includes leadership roles at FRAMOS Imaging Systems and Huawei Research in London. Education: Mathematics (TUM), Mathematics and Physics (ParisTech, University of Melbourne), PhD in Mathematics (TUM, 2014) His research focuses on 3D computer vision , multi-modal sensor fusion , and their applications in collaborative robotics and augmented reality . He specializes in projective geometry , 6D pose estimation , and neural radiance fields , with a particular emphasis on photometrically challenging environments. Recent publications highlight advancements in 3D scene understanding , neural rendering , and medical imaging , often leveraging machine learning and vision-language models . His work has been recognized through awards like the EMVA Young Professional Award (2015) and Innovation Pioneer of the Year (2019) , along with multiple Outstanding Reviewer distinctions at leading conferences. Dr. Busam has supervised numerous PhD and MSc students on topics including 6D pose estimation , medical augmented reality , and robotic ultrasound , collaborating with institutions like MIT , École Polytechnique , and University of Padova .

• Human-Computer Interaction
• Virtual Reality
• 3D User Interfaces
• +7 more

Dr. Robert J. Teather is an Associate Professor and the Director of the School of Information Technology at Carleton University in Ottawa, Canada. He previously served as an interim Director of the School of Information Technology during the 2022-23 academic year. His academic journey includes a PhD in Computer Science from York University (2013) and a postdoctoral fellowship at McMaster University (2015). Dr. Teather's educational background includes: PhD in Computer Science from York University (2013) Master's Thesis: "Comparing 2D and 3D Direct Manipulation Interfaces" from York University (2008), which was awarded the Joseph Liu Thesis Award Dr. Teather's research broadly falls under the field of human-computer interaction, with specialization in 3D user interfaces, virtual reality, and user interfaces for computer games. His work establishes methods for direct comparison of 2D and 3D interfaces for conceptually equivalent tasks, such as selection and manipulation interfaces. He investigates factors influencing human performance in VR, including stereo 3D graphics, haptic feedback, and head-tracking. His research also evaluates novel user interfaces like tilt control or touchscreens, and examines human performance with game input devices in complex tasks involving navigation, selection, and manipulation of objects in game environments. His research has been published extensively in top venues including IEEE VR, ACM SUI, and Graphics Interface. Among his notable scientific achievements are: NSERC Postgraduate Scholarship during his PhD studies Ontario Graduate Scholarship during his PhD studies Best Paper Honourable Mention at the ACM Symposium on Applied Perception 2020 Best Demo Award for SUI 2017 Joseph Liu Thesis Award (2008) Dr. Teather actively supervises graduate students at Carleton University, currently overseeing multiple PhD and Master's students in the areas of human-computer interaction and interactive digital media. His research is supported by NSERC and the Canada Foundation for Innovation, providing funding for his students and laboratory equipment. His students have produced research spanning VR as a persuasive tool to improve vaccine confidence, selection performance using smartphones in VR, and text entry methods in virtual reality environments. Dr. Teather leads a well-equipped CFI-supported lab focused on virtual and augmented reality research. His team works collaboratively on projects related to interactive virtual reality systems, computer game user interfaces, and input devices for 3D interaction. The lab environment fosters interdisciplinary research with opportunities for students to work on cutting-edge VR/AR technologies and contribute to the growing field of spatial computing.

• Artificial Intelligence
• Natural Language Processing
• Multimodal Reasoning
• +4 more

Graham Neubig is an Associate Professor at the Language Technologies Institute (LTI) within Carnegie Mellon University (CMU). His research focuses on advancing artificial intelligence, particularly in natural language processing (NLP), multimodal reasoning, and large language models (LLMs). He explores topics such as AI safety, generative AI, and human-AI interaction, with an emphasis on practical applications like machine translation and web-agent systems. His work often involves developing frameworks for evaluating AI systems, such as OpenAgentSafety and BehaviorBox, which assess real-world agent performance and model behavior. Neubig's research also delves into improving LLM capabilities through reasoning analysis, hallucination detection (e.g., ZINA), and culturally aware systems (e.g., CAIRe). He has contributed to open-source projects like Pangea (a multilingual LLM) and frameworks such as Cmulab for model deployment. His recent work addresses challenges in agentic tasks, self-improving agents (Skillweaver), and benchmarking across domains like visual reasoning (VisualPuzzles) and software engineering. Notable achievements include advancing evaluation methodologies for LLMs, developing tools for ethical AI, and creating benchmark suites that test systems under realistic conditions. His lab collaborates on projects like the BrowserGym ecosystem and OpenHands platform, which aim to standardize web-agent research and AI-driven software development. Neubig's contributions span theoretical advancements and practical implementations, bridging the gap between cutting-edge research and real-world applications. He advises students such as Apurva Gandhi and actively publishes in top venues, addressing topics from instruction-following improvements to the societal impacts of AI. His work frequently emphasizes the importance of transparency, controllability, and cultural awareness in AI systems.

M. Tamer ÖzsuView profile

Professor

• Data Science
• Database Systems
• Distributed Data Management
• +3 more

M. Tamer Özsu is a University Professor of Computer Science at the David R. Cheriton School of Computer Science, University of Waterloo, where he holds a Cheriton Faculty Fellowship. He also serves as a Distinguished Visiting Professor at Tsinghua University and is the Founding Director of Waterloo-Huawei Joint Innovation Laboratory since 2018. His extensive contributions to computing have earned him numerous prestigious awards including the 2024 ACM Presidential Award for long-standing and significant contributions to the computing field. Professor Özsu's research focuses on data engineering aspects of data science, particularly addressing data management issues with two main foci: management of non-traditional data and large-scale distributed data management. He is renowned for his seminal book "Principles of Distributed Database Systems" (co-authored with Patrick Valduriez), now in its fourth edition, and the "Encyclopedia of Database Systems" (co-edited with Ling Liu), in its second edition. His work bridges theoretical foundations with practical system implementations, targeting grand societal challenges through computational approaches. His recent publications reveal a strong trend toward graph analytics, streaming data processing, and the integration of large language models with vector data management. The research shows increasing focus on GPU-accelerated graph processing, RDF query optimization, and multimodal data analysis, reflecting the evolution of data management challenges in the era of big data and AI. His work continues to address fundamental challenges in distributed data systems while adapting to emerging technologies and application domains. Scientific Awards and Fellowships ACM Presidential Award (2024) IEEE TCDE Education Award (2024) IEEE Innovation in Societal Infrastructure Award (2022) CS Can | Info Can Lifetime Achievement Award (2018/2019) ACM SIGMOD Test-of-Time Award (2015) ACM SIGMOD Contributions Award (2006) The Ohio State University College of Engineering Distinguished Alumnus Award (2008) Fellow of the Royal Society of Canada Fellow of the American Association for the Advancement of Science (AAAS) Life Fellow of the Association for Computing Machinery (ACM) Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) Elected member of the Science Academy, Türkiye Professor Özsu has been deeply involved in academic leadership and community building. As Founding Editor-in-Chief of ACM Books (2013-2019), he launched a series that by 2019 had published 28 major books with another 30 under contract. His service to ACM, particularly through SIGMOD, has been exemplary and widely recognized. He directs the Waterloo-Huawei Joint Innovation Laboratory, which focuses on cutting-edge research in data management and distributed systems, fostering strong industry-academia collaboration.

Ruohan GaoView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Multisensory Machine Intelligence
• +4 more

Ruohan Gao is an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park , with affiliate appointments at the University of Maryland Institute for Advanced Computer Studies (UMIACS) , Maryland Robotics Center (MRC) , and Artificial Intelligence Interdisciplinary Institute at Maryland (AIM) . His research focuses on Computer Vision and Machine Learning , emphasizing Multisensory Machine Intelligence that integrates sight, sound, and touch . He aims to enable machines to perceive, understand, and interact with the world as humans do, with applications in robotic manipulation , audio-visual localization , and differentiable rendering . Article Trends : Span 2018–2025 , centering on audio-visual perception , multisensory datasets , and robotics . Recurring themes include object-centric learning , sound synthesis , and cross-modal consistency . Scientific Awards : Michael H. Granof Award (UT Austin’s Top 1 Doctoral Dissertation, 2021) Best Paper Award Runner-Up (BMVC 2021) Best Paper Award Finalist (CVPR 2019) Highlight Paper (CVPR 2023) He leads the UMD Multisensory Machine Intelligence Lab and collaborates with institutions like Stanford and The University of Texas at Austin . Contact: rhgao@umd.edu .

• Medical Imaging
• Molecular Imaging
• Neuroscience
• +3 more

Steven Meikle is a Professor of Medical Imaging Physics and Head of the Imaging Physics Laboratory at the Brain and Mind Centre, University of Sydney. He also serves as Deputy Director (Preclinical) of Sydney Imaging and Deputy Director of the National Imaging Facility's Sydney node. His expertise spans advanced imaging technologies, with a focus on PET/SPECT instrumentation and molecular imaging. He holds a B.App.Sc.(Hons) from the University of Technology Sydney and a PhD from the University of New South Wales. Research focuses include developing novel PET systems like Open-field PET (for freely moving rodents) and Total Body PET, which enhance imaging sensitivity and enable real-time behavioral studies alongside brain function analysis. Collaborations include Tsinghua University (China) and UC Davis (USA). He leads projects on motion correction, quantitative imaging, and AI-driven analysis. Key achievements include over 180 peer-reviewed publications, editorial roles in Physics in Medicine and Biology , and leadership in professional societies. Awards include IEEE Senior Membership and Australian Institute of Physics Fellowship. Current student projects explore Total Body PET applications, motion correction, and radiopharmaceutical evaluation. Teaching roles include medical physics courses in diagnostic radiography and medical physics programs. He advises on imaging ethics, facility implementation, and translational research bridging basic science and clinical applications.

• Particle interactions
• Kinetic theory of aggregation
• Nanotechnology
• +5 more

Lande Liu is a Senior Lecturer in Chemical Engineering at the University of Huddersfield's School of Applied Sciences. Previously, he held a Lectureship at the University of Manchester (2010-2014), and earlier worked as an industrial consultant and research fellow at Leeds and Sheffield Universities. His academic journey began with a MEng in Chemical Engineering and a PhD in kinetic theory of aggregation from Sheffield (2004), preceded by a visiting PhD at Twente University (2002). Education: PhD in Chemical Engineering (University of Sheffield, 2004) Visiting PhD (Twente University, 2002) MEng in Chemical Engineering (Tsinghua University, 1999) BSc in Applied Mathematics (Tsinghua University, 1996) Liu's research focuses on multi-scale particle interactions (molecular to granular) using kinetic theory of aggregation, with applications spanning nanotechnology, pharmaceutical engineering, and sustainable chemical processes. His work aligns with UN Sustainable Development Goals for environmental protection and industrial innovation. Recent publications examine particle deposition in turbulent flows, enhanced heat exchanger designs, and nanofluid stabilization techniques. He teaches core chemical engineering topics including transport phenomena, unit operations, and process design. Active in collaborative research, Liu has partnered with institutions across Europe on projects involving spectroscopy, ultrasonics, and dynamic modeling. His technical expertise includes particle size analysis, tomography, and computational simulation of complex systems.

André FiebigView profile

Researcher

• Psychoacoustics
• Soundscape Research
• Noise Effects
• +7 more

Dr. phil. André Fiebig is a Permanent Research Associate and PostDoc at the Institute of Fluid Mechanics and Technical Acoustics (ISTA) within Faculty V - Transportation and Mechanical Systems at Technical University of Berlin. From January 2019 to December 2024, he served as a Visiting Professor responsible for the field of psychoacoustics, funded by the HEAD Genuit Foundation. Since January 2025, he has been leading the 'Psychoacoustics and Noise Effects' working group at the Department of Technical Acoustics. His research spans multiple areas within psychoacoustics and soundscape studies, including fundamentals and modeling of psychoacoustic sensation variables, binaural psychoacoustics, assessment of ambient noise and soundscapes, and psychoacoustic evaluation of sound insulation measures. His work also addresses cognitive stimulus integration of auditory sensations, auditory recreation, acoustic quality of stay, characterization of quiet areas, and measuring sound-induced emotions. Analysis of his recent publications reveals a strong focus on urban soundscapes, noise-conscious behavior in transportation, and the development of methodological frameworks for soundscape assessment. His work often integrates psychoacoustic principles with environmental considerations, particularly examining the relationship between sound environments and human health. Recent research shows increasing emphasis on cross-cultural studies of noise perception and the development of standardized assessment methodologies. Dr. Fiebig is involved in the EARS (Education and Applied Research on Soundscapes) initiative and has contributed to numerous collaborative research projects examining the intersection of urban planning, environmental acoustics, and human perception. His work frequently appears in major acoustics conferences and journals, demonstrating his active role in advancing the field of psychoacoustics and soundscape research. His laboratory work focuses on psychoacoustic testing methodologies, soundscape assessment techniques, and the development of evaluation instruments for noise protection measures. The 'Psychoacoustics and Noise Effects' working group under his leadership conducts research on both theoretical aspects of sound perception and practical applications for urban noise management.