جست‌وجوی استاد و پژوهشگر

Ingrid Verduycktمشاهده پروفایل

دانشیار

• Speech-Language Pathology
• Voice Disorders
• Perceptual Analysis
• +۳ مورد دیگر

Ingrid Verduyckt is an Associate Professor at the School of Speech-Language Pathology and Audiology, part of the Faculty of Medicine at the Université de Montréal. She holds affiliations with the CRIR (Interdisciplinary Rehabilitation Research Center of Metropolitan Montreal), REPAR (Quebec Provincial Adaptation-Rehabilitation Research Network), and BRAMS (International Laboratory for Brain, Music, and Sound Research). Her research focuses on vocal motor control, perceptual aspects of dysphonia, and the impact of soundscapes on communication and well-being. She has led interdisciplinary projects such as the GRAPPE initiative addressing educational sound management and the MyOrtho vocal coaching application. Dr. Verduyckt earned a Master’s from Lund University (Sweden) and a PhD in Psychological Sciences from the Catholic University of Louvain (Belgium). She has supervised Master’s theses on topics like Parkinson’s therapy co-development and theater’s role in aphasia recovery. Notable awards include the 2019 Fortissimo Young Researcher Award recognizing her innovative intersectoral collaborations. She teaches courses including voice disorder assessment (ORT-6141) and professional advocacy (ORT-6602). Her work spans over 30 peer-reviewed publications and numerous grants, including CIHR-funded studies on virtual care equity and FQRSC-supported projects on voice handicap indices. She actively promotes inclusive theater environments and has developed validated assessment tools like the CAPE-Vf voice evaluation protocol.

• Wireless Digital Communications
• Indoor Localization
• Error Control Coding
• +۱۲ مورد دیگر

Dr. Ian D. Marsland is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University, Faculty of Engineering and Design. He holds a Ph.D. in Electrical Engineering from the University of British Columbia and has been a faculty member since 1999. His research is centered on wireless digital communications, with a focus on error control coding, noncoherent detection, iterative decoding, and indoor localization. B.Sc.Eng. (Honours) in Mathematics and Engineering, Queen's University, 1987 M.Sc. in Electrical Engineering, University of British Columbia, 1994 Ph.D. in Electrical Engineering, University of British Columbia, 1999 His research interests span wireless digital communications , including indoor localization using wireless networks , error control coding (LDPC, turbo, polar codes) , noncoherent receiver design , and applications of iterative decoding . His work bridges theoretical communication systems with practical implementation in modern wireless networks. The analysis of his recent publications (2020–2024) reveals a strong trend toward advanced modulation and coding schemes such as SCMA , faster-than-Nyquist signaling , and polar codes , often integrated with machine learning (e.g., neural network-aided detection) and high-resolution localization techniques. His work frequently appears in high-impact IEEE journals like IEEE Transactions on Communications and top conferences including ICC and GlobeCom . Dr. Marsland has not been explicitly mentioned as receiving scientific awards in the provided texts. He actively advises graduate students and has collaborated extensively with researchers including H. Yanikomeroglu , R.H. Gohary , and T. Shehata . His research has been supported through academic grants and industrial partnerships, though specific grant details are not listed. He supervises work in areas such as MIMO systems, SCMA, polar coding, and indoor positioning. Dr. Marsland leads a research group focused on wireless communications and signal processing, with active projects in next-generation multiple access, low-latency detection, and robust communication in fading and interference-prone environments. His lab contributes to both theoretical advancements and practical implementations in modern wireless systems.

Brynle Barrettمشاهده پروفایل

دانشیار

• Quantum Sensors
• Ultra-Cold Matter
• Atomic and Optical Physics
• +۳ مورد دیگر

Brynle Barrett is an Associate Professor in the Department of Physics at the University of New Brunswick. His research focuses on experimental atomic and optical physics, particularly the development of high-accuracy quantum sensors using ultra-cold matter. He designs quantum accelerometers and gyroscopes leveraging the wave nature of atoms, with applications in Earth observation, navigation, and fundamental physics testing. Key research areas include light-matter interactions, laser cooling/trapping of neutral atoms, ultra-stable lasers, and precision measurements of fundamental constants. His work addresses gravitational and electromagnetic field sensitivity through matter-wave interferometry, enabling instruments like atomic clocks and gravimeters. Applications span geodesy, volcanic monitoring, and GPS-free navigation systems. Recent publications emphasize hybrid quantum accelerometers, multi-axis interferometer systems, and microgravity experiments. His teaching contributions include laboratory courses on laser spectroscopy and atom trapping, designed to train students in cutting-edge quantum technologies. Barrett leads projects on inertial sensors for mobile platforms, Sagnac effect studies, and tests of the weak equivalence principle using dual-species atom interferometers. His work bridges fundamental physics with practical sensor development, positioning quantum technologies for real-world deployment.

• Wireless Digital Communications
• Noncoherent Receiver Design
• Error Control Coding
• +۵ مورد دیگر

Dr. Ian D. Marsland is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University (Faculty of Engineering and Design). He holds a Ph.D. from the University of British Columbia and has been affiliated with Carleton since 1999. His research focuses on wireless digital communications, noncoherent receiver design, error control coding, and indoor localization using wireless networks. He has contributed to advancements in SCMA, FTN signaling, and polar codes, with a strong emphasis on iterative decoding applications. Education: B.Sc.Eng. (Honours) in Mathematics and Engineering, Queen's University (1987) M.Sc. in Electrical Engineering, University of British Columbia (1994) Ph.D. in Electrical Engineering, University of British Columbia (1999) Research Interests: Wireless communication systems (stationary/mobile) Error control coding (LDPC, turbo, polar codes) Noncoherent receiver design Faster-than-Nyquist (FTN) signaling and neural network-aided detection Multidimensional constellations for SCMA systems Indoor localization via wireless networks Recent Research Trends: Dr. Marsland’s recent work emphasizes low-complexity detection algorithms for FTN signaling, SCMA constellation design, and polar code optimization. His publications highlight advancements in throughput-based coding, sphere decoding for SCMA, and high-resolution positioning techniques using MUSIC-based methods. Grants & Advising: While specific grants or student advisees are not detailed in the provided texts, his research portfolio indicates sustained involvement in collaborative projects with industry and academic partners. His lab focuses on next-generation wireless systems and signal processing innovations. Labs & Teams: His research is conducted within Carleton’s Department of Systems and Computer Engineering, emphasizing interdisciplinary work in communications and signal processing. Collaborators include researchers from institutions like the University of Toronto and industry partners.

Denis Larocqueمشاهده پروفایل

استاد

• Non-parametric statistical methods
• Data mining
• Multidimensional Data Analysis
• +۶ مورد دیگر

Denis Larocque is a Full Professor in the Department of Decision Sciences at HEC Montréal, specializing in statistical methods, data mining, and multidimensional data analysis. He serves as Director of the Doctorate in Administration (Ph.D.) program and is affiliated with the GERAD (Group for Research in Decision Analysis) and CIRRELT (Interuniversity Research Center on Enterprise Networks, Logistics and Transport). His academic background includes a M.Sc. and Ph.D. in Statistics from the University of Montreal. His research focuses on non-parametric statistical methods, survival analysis, reinforcement learning applications in transportation systems, and machine learning techniques such as random forests. Recent work includes studies on traffic signal control optimization, causal inference in medical data, and predictive modeling in healthcare. Larocque has supervised over 100 students and projects, including 2 doctoral theses and 4 master’s theses in the last five years. He teaches advanced data science courses and has contributed to interdisciplinary research across transportation, healthcare, and marketing domains. His publications span journals in statistics, transportation engineering, and bioinformatics. He actively collaborates with industry partners, applying statistical and machine learning methodologies to solve real-world problems in sectors such as finance, logistics, and healthcare. His work emphasizes practical applications of data-driven decision-making and methodological advancements in statistical computing.