جست‌وجوی استاد و پژوهشگر

Siyuan Chenمشاهده پروفایل

مدرس

• Physiological Computing
• Eye Activity Analysis
• Human-Computer Interaction
• +۳ مورد دیگر

Dr Siyuan Chen is a Lecturer at the School of Electrical Engineering and Telecommunications , UNSW Sydney. Her research focuses on physiological computing , particularly eye activity analysis for mental state recognition using wearable technology . She has contributed to signal processing and machine learning methodologies for non-invasive cognitive load and task transition detection. Ph.D. in Electrical Engineering (UNSW Sydney) M.E. in Microelectronics (RMIT University) Research Intern, NII Tokyo Research Fellow, University of Melbourne Research Visitor, INRIA France Chen's research investigates eye behavior through infrared video datasets and multimodal sensor signals. Her work addresses physiological computing for applications in human-computer interaction , wearable mental state analysis , and biomedical signal processing . Key contributions include the IREye4Task dataset and novel methods for blink-saccade synchronization and pupillary response analysis . Recent publications demonstrate trends in wearable eye tracking using acoustic sensors, low-power facial expression tracking , and event-based task transition detection . Her work spans both journal and conference venues including IEEE Transactions, ACM, and INTERSPEECH. NICTA Postgraduate Scholarship (2011-2013) Commercialization Training Scheme Scholarship (2012) Australia Endeavor Fellowship (2015) $711K US Army grant for wearable behavioral signal modeling (2019) Chen contributes to teaching in electronics , signal processing , and engineering ethics , covering courses from first-year design to postgraduate leadership modules. She serves as a topic editor for Frontiers in Computer Science special issues.

Mireille Boutinمشاهده پروفایل

استاد

• Applied Mathematics
• Signal Processing
• Machine Learning
• +۵ مورد دیگر

Mireille Boutin is a Professor at the Eindhoven University of Technology , affiliated with the Department of Mathematics and Computer Science within the Discrete Algebra and Geometry group. Her research spans applied mathematics, signal processing, and machine learning, with a focus on discrete inverse problems and the integration of geometric tools in probabilistic frameworks. Academic Background : She earned a Ph.D. in Mathematics from the University of Minnesota under Peter Olver, followed by postdoctoral positions at Brown University and the Max Planck Institute for Mathematics in the Sciences . Before joining TU/e, she served on the faculty at Purdue University . Research Trends : Recent publications demonstrate her interdisciplinary approach, including solutions to global positioning uniqueness problems via algebraic geometry, computer-aided qualitative data analysis in education, symmetry-breaking in acoustic path tracking, and novel clustering models for high-dimensional data. Her work often bridges theoretical mathematics with practical applications in engineering and education. Educational Contributions : She actively teaches Computational Algebra at TU/e and has collaborated on studies applying machine learning to qualitative education research, such as analyzing student explanations in programming and faculty teaching conceptions.

• Computational Mechanics
• Material Science
• Biomechanics
• +۵ مورد دیگر

Prof. Bernd Markert serves as Professor and Head of the Institute of General Mechanics at RWTH Aachen University's Faculty of Mechanical Engineering. He concurrently holds critical university-wide roles including Rector's Representative for Alumni and Rectorate Mandate for Mexico Cooperation, based in Aachen's Faculty of Mechanical Engineering building. His research spans computational mechanics with emphasis on phase-field modeling, molecular dynamics, and machine learning integration. Key focus areas include biodegradable magnesium alloys for biomedical implants, multiscale composite material behavior, and AI-enhanced structural failure prediction. Recent work bridges physics-based simulations with neural networks for constitutive modeling and corrosion prediction. Analysis of his 2022-2025 publications reveals accelerating convergence of mechanics and artificial intelligence, particularly in physics-informed neural networks for crystal plasticity and phase-field frameworks. His team demonstrates consistent innovation in modeling porous media, network materials, and biomechanical systems while maintaining strong industry-relevant applications in additive manufacturing and biomedical engineering. As Institute Head, Markert leads the Chair and Institute of General Mechanics (IAM), directing research on fundamental mechanics principles applied to advanced materials and structural systems through computational and experimental methodologies.

Bracha Lauferمشاهده پروفایل

مدرس

• Acoustic Source Localization
• Speech Signal Processing
• Gaussian Processes
• +۳ مورد دیگر

Dr. Bracha Laufer is a senior lecturer at the School of Electrical Engineering , part of the Iby and Aladar Fleischman Faculty of Engineering at Tel Aviv University. Her research focuses on acoustic source localization, speech signal processing, and machine learning techniques for audio engineering. Her recent work explores conformal prediction and manifold-based approaches for robust source localization, deep learning architectures for sound source separation, and simplex geometry in multichannel signal analysis. These publications highlight interdisciplinary applications of machine learning and statistical methods in acoustics. Dr. Laufer's research integrates Bayesian inference , probabilistic graphical models , and uncertainty quantification to address challenges in adverse acoustic environments. She has contributed to advancements in multi-microphone speaker localization and speech inpainting .

• Robotics
• Robot Audition
• Optimal Filtering and Estimation
• +۴ مورد دیگر

He Kong is an Associate Professor at Southern University of Science and Technology (SUSTech), affiliated with the School of Automation and Intelligent Manufacturing, where he also serves as Deputy Director of the SUSTech Institute of Robotics. Previously, he was an Assistant Professor in the Department of Mechanical and Energy Engineering at SUSTech from January to May 2022. Prior to joining SUSTech, he was a Research Fellow at the Australian Centre for Field Robotics, University of Sydney (2016-2021), and at Cranfield University's Advanced Vehicle Engineering Centre (2015-2016). He received his Ph.D. in Electrical Engineering from the University of Newcastle, Australia (2014), M.E. in Control Science and Engineering from Harbin Institute of Technology (2010), and B.E. in Electrical Engineering and Automation from China University of Mining and Technology (2004). His research focuses on robotic intelligent perception and decision making, robot audition, optimal filtering and estimation, and advanced control methods. Specifically, he works on active multi-mode perception, parameter calibration of robot audition systems, optimal filtering under unknown inputs, and fully actuated system approaches. His work has significant applications in precision agriculture, environmental monitoring, and robotic inspection of hazardous industries such as chemical and mining operations. His recent publications reveal a strong emphasis on multi-modal perception systems, particularly combining visual and auditory sensing for robotic applications. His research shows a progression from theoretical control methods toward practical implementations in field robotics, with increasing focus on real-world applications in agriculture and hazardous environments. Finalist for Youth Author Prize, IFAC Workshop on Robot Control (2019) Fifth China Robotics Academic Annual Conference Best Poster Award (2024) 14th International Conference on Indoor Positioning and Indoor Navigation Best Paper Award (2024) The Equity Scholarship, Council of International Students Australia (2011) Outstanding Postgraduate Students Award, Harbin Institute of Technology (2010) Professor Kong actively supervises numerous PhD and Master's students and has established a productive research group focused on active intelligent systems. His laboratory is equipped with advanced facilities including over 30 motion capture systems, Unitree humanoid robots, robot dogs, wheeled mobile robots, and custom-developed platforms like Cubli and acoustic perception systems. He serves on editorial boards for several prestigious journals including IEEE Robotics and Automation Letters and IEEE Sensors Letters, and has been an Associate Editor for major robotics conferences such as IEEE ICRA and IEEE/RSJ IROS.

Farhad Mohsinمشاهده پروفایل

استادیار

• Computational Social Choice
• Fairness in Machine Learning
• Preference Aggregation
• +۴ مورد دیگر

Farhad Mohsin is an Assistant Professor in the Department of Math and Computer Science at College of the Holy Cross in Worcester, MA. He earned his PhD in Computer Science from Rensselaer Polytechnic Institute (RPI) between 2018-2023, working with Professor Lirong Xia, and completed his BSc in Electrical and Electronic Engineering at Bangladesh University of Engineering and Technology (BUET) from 2010-2015. Prior to his academic career, he worked as a Telecommunications Engineer/Data Analyst at Grameenphone Ltd, Bangladesh. Dr. Mohsin's research focuses on computational social choice, particularly preference aggregation and fair decision-making. He explores ML-based techniques for designing economic mechanisms, with specific interest in fairer voting rules. His broader research interests include natural language processing, interpretable machine learning, and multi-agent reinforcement learning. His recent publications (2021-2024) examine computational complexity of voting paradoxes, election data generation using deep learning, and natural language-based preference aggregation. His work has appeared in top venues including IJCAI, AAMAS, and JAIR. Dr. Mohsin teaches courses including Data Mining, Data Structures, Analysis of Algorithms, Discrete Structures, and Advanced Algorithms. He supervises undergraduate research projects, with recent honors theses on multi-agent reinforcement learning and fairness in zoning laws.

François-Raymond Boyerمشاهده پروفایل

دانشیار

• Computer Architecture
• VLSI Systems
• Microelectronics
• +۴ مورد دیگر

François-Raymond Boyer is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a B.Sc. and Ph.D. from Université de Montréal and teaches courses in programming and digital audio. His research spans: Computer architecture and VLSI systems Network processing and traffic management Digital audio signal processing Hardware acceleration and optimization He is affiliated with ReSMiQ (Strategic Cluster for Microsystems) and OICRM (Music Research Observatory). Recent publications focus on 5G network processing, modular programming frameworks, and high-speed traffic management architectures, primarily in IEEE Access and IEEE Transactions on VLSI Systems. Professor Boyer has supervised 3 PhD and 6 Master's students, with research topics including network architecture, audio processing, and hardware design. No scientific awards are mentioned in the available records.

• Low vision rehabilitation
• Depth perception
• Binocular vision
• +۵ مورد دیگر

Dr. Vincent Nguyen serves as a Senior Lecturer in Orthoptics within the Graduate School of Health at the University of Technology Sydney. With a distinguished career spanning clinical practice, research, and academia, he brings extensive expertise in visual science and rehabilitation. His academic journey began with Honours in Orthoptics (1993) followed by a Master of Applied Science (1996), culminating in a PhD from the University of Sydney (2003) focused on binocular rivalry in visual psychophysics. Dr. Nguyen's research interests focus on low vision rehabilitation, depth perception, binocular vision, and the application of virtual reality and spatial audio technologies for assistive applications. His work bridges fundamental visual neuroscience with practical rehabilitation solutions, particularly for people with visual impairments. He has pioneered research in acoustic touch interfaces, virtual reality rehabilitation environments, and spatial audio navigation systems. His publication record demonstrates a clear trajectory from fundamental visual neuroscience to applied rehabilitation technologies. Recent work emphasizes immersive virtual reality applications for communication and physical rehabilitation, as well as innovative spatial audio systems that enhance navigation for people who are blind. His research integrates principles from neuroscience, engineering, and clinical practice to develop practical assistive solutions. Dr. Nguyen has secured significant research funding including NHMRC Ideas Grants (2023-2027) for 'Fluent Mobility for the Blind Individual Using Multimodal Auditory Sensory Augmentation' and CRC-P projects like 'ARIA - Bionic Visual-Spatial Medical Device for the Blind' (2022-2024). Current projects include 'EyeBot: AI-Powered Triage for Ophthalmology Referrals' (2025) and 'Next-Generation Extended Reality, Wearable Biosensors, and Metaverse Technologies for Medical Applications' (2024). As an educator, Dr. Nguyen teaches courses in Therapy and Rehabilitation (96037), Clinical Management of Refractive Error (96031), and Eye and Visual Systems (96027). His clinical background includes appointments as a Clinical Electrophysiologist with NSW Health (2007) and work with Vision Australia assisting people with low vision (2012). His postdoctoral work at York University's Centre for Vision Research with Professor Ian Howard focused on human depth perception, building on his foundational expertise in visual neuroscience.

• Acoustics
• Noise Measurement
• Microphone Array Technology
• +۵ مورد دیگر

Pieter Sijtsma serves as a Professor in the Department of Operations & Environment within Delft University of Technology's Faculty of Aerospace Engineering. His academic career spans over 15 years of specialized research in aeroacoustics, with significant contributions to microphone array technology and noise measurement methodologies. Current affiliations include active roles in the Berlin Beamforming Conference Committee and ongoing collaborations with major aerospace research entities. Professor Sijtsma's research focuses on advanced acoustic measurement techniques for aerospace applications. His work centers on beamforming algorithms , engine noise characterization , and wave propagation modeling in complex environments like wind tunnels and annular ducts. Key specialties include CLEAN-SC deconvolution methods for noise source mapping, directivity pattern analysis, and experimental validation of acoustic assessment techniques. His fingerprint reveals dominant expertise in acoustics (100%), noise measurement (97%), and microphone array technology (68%). Recent publication trends show concentrated activity in improving acoustic field assessment (2025), engine noise directivity determination (2024), and beamforming in swirling flows (2023). His work consistently addresses practical aerospace noise challenges through rigorous experimental validation and mathematical modeling, with strong emphasis on measurement accuracy and algorithmic innovation. Professor Sijtsma actively supervises research through collaborative projects, typically co-mentoring students with colleagues like Snellen and Avallone. His group maintains strong industry connections, evidenced by committee roles with the Ministry of Infrastructure and Environment and participation in international standard-setting conferences. Current projects involve EU-funded research on wind tunnel acoustic correction methods and engine noise source characterization. The research infrastructure leverages TU Delft's advanced wind tunnel facilities with specialized acoustic treatment and high-channel-count microphone arrays. Recent dataset releases confirm access to sophisticated wave propagation modeling tools and experimental validation platforms for closed-test-section environments.

• Wireless Networks
• Mobile Systems
• Network Protocols
• +۳ مورد دیگر

Lili Qiu is a Professor in the Department of Computer Science at the University of Texas at Austin and Vice Managing Director of Microsoft Research Asia (Shanghai). She previously worked at Microsoft Research Redmond (2001-2004). Her research spans wireless networks, mobile systems, and network protocols, with recent work in acoustic sensing and AI-driven networking solutions. Research Focus Qiu's research addresses fundamental challenges in: Wireless network performance and interference management Mobile system optimization for real-world environments Acoustic-based localization and tracking technologies Deep learning applications for network reliability Next-generation cellular architectures (5G and beyond) Publication Trends Her recent publications (2020-2023) demonstrate a shift toward multimodal sensing systems combining acoustics and computer vision, edge intelligence optimization, and robust mobility management for next-generation networks. This reflects industry-academia convergence through her dual appointments. Awards and Honors IEEE Fellow (2017) ACM Fellow (2018) National Academy of Inventors Fellow (2022) N2Women: Stars in Networking (2017) ACM Distinguished Scientist (2013) NSF CAREER Award (2006) Best Paper Awards: ACM MobiSys 2018, IEEE ICNP 2017 Leadership and Affiliations She bridges academic research and industrial innovation through her joint appointment at UT Austin and Microsoft Research Asia, where she oversees strategic research directions in computing systems.