Find Academic Supervisors

Marius ParaschivoiuView profile

Professor

• Computational Fluid Dynamics
• Finite Element Methods
• Aerodynamic Simulations
• +7 more

Marius Paraschivoiu is a Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University, within the Faculty of Engineering and Computer Science. His research focuses on computational fluid dynamics (CFD), finite element methods, and aerodynamic simulations with applications to wind energy systems, acoustic simulations, and turbulence modeling. He holds a PhD in engineering and has expertise in parallel computing and urban wind energy potential assessment. His work emphasizes optimizing vertical axis wind turbine (VAWT) performance in urban environments, including roof-mounted installations, wake interactions, and turbulence effects. Paraschivoiu has extensively studied the impact of building geometry, corner placements, and fluid-structure interactions on turbine efficiency. His CFD-based analyses address challenges like mesh adaptation, multiphase flows, and real-gas modeling for hydrogen systems. Key research themes include improving wind energy harvesting through innovative turbine designs, mitigating aerodynamic noise, and enhancing flow uniformity in complex configurations. Paraschivoiu’s contributions span over 50 peer-reviewed articles, with recent focus on urban microclimate effects, VAWT array optimization, and turbine blade morphing concepts. He maintains an active research website at Concordia University and collaborates on applied projects involving CFD validation and industrial gas turbine combustor emissions.

Charles H. NobleView profile

Professor

• Product Design & Development
• Marketing Strategy
• Consumer Behavior
• +3 more

Charles H. Noble is the Jerry & Kay Henry Professor of Business and Roy and Audrey Fancher Faculty Research Fellow at the University of Tennessee, Knoxville’s Haslam College of Business. He previously served as Associate Dean for Research and Faculty at Haslam and held roles at Boston College and the University of Mississippi. His research focuses on product and service design processes, innovation management, and marketing strategy. Education: Ph.D. in Marketing, Arizona State University (1996) M.B.A. in Marketing and International Business, Babson College (1989) B.S. in Finance, Boston College (1986) Research Interests: Professor Noble explores design and development processes across industries, emphasizing open innovation, new product development (NPD) speed, and strategic alliances. His work bridges theoretical frameworks with practical applications in sectors like retail, consumer goods, and commercial real estate. He advocates for interdisciplinary approaches to enhance innovation outcomes and sustainability. Publications Trends: His recent articles address post-pandemic innovation environments, business model design under media influence, and cross-functional team dynamics in product development. Editorials in journals like Journal of the Academy of Marketing Science highlight his leadership in shaping innovation research agendas. Awards/Honors: Henry Professor of Business (endowed chair) Fancher Faculty Research Fellow Recognition for research and teaching excellence Advising & Grants: While specific grants are not detailed, his editorial board roles and consulting engagements suggest significant academic and industry collaboration. He advises on NPD strategies and has mentored scholars in innovation management. Labs/Teams: Engaged in collaborative initiatives through Haslam’s research centers, focusing on digital transformation and open innovation frameworks.

Neil D. B. BruceView profile

Associate Professor

• Computer Vision
• Deep Learning
• Machine Learning
• +6 more

Neil D. B. Bruce is an Associate Professor in the School of Computer Science at the University of Guelph, Canada. His research focuses on computer vision, deep learning, and computational neuroscience, with a strong emphasis on visual saliency, neural networks, and semantic segmentation. He holds a BSc in Computer Science & Pure Math from the University of Guelph, an MASc in Systems Design Engineering from the University of Waterloo, and a PhD in Computer Science from York University. Prior to Guelph, he held academic positions at Ryerson University and the University of Manitoba. Dr. Bruce leads the Vision Lab, exploring topics like attention mechanisms, image processing, and AI-driven solutions for visual computing challenges. His work bridges theoretical models with practical applications, including real-world gaze behavior analysis and exposure blending techniques. Key contributions include saliency prediction frameworks (e.g., AIM model) and semantic segmentation networks (EML-Net, Iterative Gating Networks). His research also intersects with interdisciplinary fields such as neuroscience and healthcare informatics, as seen in recent studies on avian influenza outbreak detection using social media data. Teaching highlights include courses in neural networks, data science, and machine learning. He actively supervises graduate and undergraduate research projects, emphasizing computational methods and AI innovation.

• Digital Manufacturing
• Sustainability Engineering
• Additive Manufacturing
• +5 more

Professor Jonathan Corney holds the Chair of Digital Manufacture in the School of Engineering at the University of Edinburgh. His research focuses on advanced manufacturing technologies, including digital twin applications, smart factory optimization, sustainability engineering, and additive manufacturing. He leads projects addressing human factors in industrial environments, predictive analytics for production processes, and intellectual property challenges in modern manufacturing systems. His academic background encompasses mechanical engineering with specialization in CAD/CAM systems, hydroforming technology, and patent analysis for design innovation. Corney has pioneered methods like the Economic and Environmental Impact Assessment for Sustainability (EENIAS), and developed decision support frameworks for energy-efficient scheduling and garment reprocessing in circular economies. Key research themes include: Smart factory design through real-time worker movement analysis Cyber-physical systems for supply chain optimization Machine learning applications in manufacturing process control Human-centric automation and safety protocols His recent work emphasizes predictive modeling using spatio-temporal graph networks, digital twin integration in assembly processes, and sustainable manufacturing practices. Over 150 peer-reviewed articles demonstrate his contributions to near-net-shape manufacturing, intellectual property management, and crowdsourced design methodologies.

Andrew MaidenView profile

Professor

• Computational Optics
• Ptychography
• Coherent Diffractive Imaging
• +5 more

Professor Andrew Maiden is a faculty member at the University of Sheffield's School of Electrical and Electronic Engineering, specializing in Computational Imaging. He leads the Semiconductor Materials and Devices Research Group. His research focuses on advancing optical systems through computational methods like ptychography, which enhances microscopy and imaging precision. With a PhD from Durham University (2005) and an MEng from the University of Birmingham (2001), Maiden's career includes pioneering work with Professor John Rodenburg on ptychography and a brief industry stint commercializing microscopy technologies. He teaches Digital Signal Processing (DSP) to third-year students and advises researchers such as Cao S (PhD graduate). Research interests include Coherent Diffractive Imaging (CDI), electron microscopy phase imaging, and inverse problem solutions. His work bridges computational algorithms with practical applications in optics and materials science. Maiden has contributed to over 50 peer-reviewed publications and holds patents on ptychography-related imaging techniques. His lab focuses on developing high-resolution imaging tools without traditional lenses, emphasizing low-dose radiation and high-throughput bio-imaging. Teaching and mentorship play key roles in his academic contributions, shaping future engineers in signal processing and computational methods. Collaborations span academia and industry, reflecting his dual focus on innovation and real-world application.

Christopher GilliamView profile

Assistant Professor

• Signal Processing
• Radar Systems
• Sampling Theory
• +5 more

Dr. Christopher Gilliam is an Assistant Professor in Applied Signal Processing at the University of Birmingham's Department of Electronic, Electrical and Systems Engineering. He holds an MEng (1st Class Hons) in Electrical & Electronic Engineering (2008) and a Ph.D. in Signal Processing (2013), both from Imperial College London. Prior to joining Birmingham in 2022, he was a Postdoctoral Fellow at The Chinese University of Hong Kong (2013–2017) and a Research Fellow at RMIT University, Australia (2017–2022). Research Interests: Sensor signal processing, radar imaging, sampling theory, motion estimation, quantum navigation, and medical imaging. Labs: Microwave Integrated Systems Laboratory (MISL). Committees: Member of IEEE Signal Processing Society and APSIPA Technical Committees. His work focuses on advancing signal processing techniques for radar systems, navigation, and medical imaging. Recent research highlights include drone-based SAR imaging, motion correction in MRI, and fusion of classical/quantum sensors for inertial navigation. He is actively supervising PhD students and contributes to projects sponsored by DSTG. Publications span radar SLAM, probabilistic navigation algorithms, and deep learning-driven medical imaging solutions. His research bridges theoretical signal processing with practical applications in autonomous systems and healthcare.

Steve MarronView profile

Professor

• Statistics
• Data Science
• Machine Learning
• +4 more

Steve Marron is the Amos Hawley Distinguished Professor of Statistics and Operations Research at the University of North Carolina at Chapel Hill (UNC-CH). He holds a joint appointment in the School of Data Science and Society and is a professor in the Department of Biostatistics at the Gillings School of Global Public Health. Additionally, he serves as an adjunct professor in the Department of Computer Science within the College of Arts & Sciences. His research focuses on statistics, data science, and machine learning, with a particular emphasis on integrating diverse data types such as genomics, imaging, and demographic data. Education: Marron earned an AA from Orange Coast College (1974), BS from University of California, Davis (1977), and PhD from UCLA (1982). He has held faculty positions at UNC-CH since 1982 and Cornell University (2001-2002). His honors include Fellowships from the Institute of Mathematical Statistics and American Statistical Association, and he is a top-cited mathematician (1991-2001). Research interests include object-oriented data analysis, high-dimensional data methods (HDLSS), visualization techniques like SiZer, and statistical methodology for imaging and genomics. Notable contributions include Distance-Weighted Discrimination (DWD), Principal Nested Spheres, and JIVE for data integration. His work has applications in cancer genomics, medical imaging, and bioinformatics. Awards and recognitions include the Amos Hawley Professorship, S. N. Roy Memorial Lectureship, and Saw Swee Hock Visiting Professorship. Marron has advised numerous students and collaborated on NIH-funded grants, including studies on cancer genomics and imaging. His lab focuses on developing statistical tools for complex, multi-source data analysis.

Noreen McDonaldView profile

Professor

• Transportation Planning
• Urban Planning
• Public Health
• +3 more

Noreen McDonald is a Professor and Senior Associate Dean for Social Science and Global Programs in the College of Arts and Sciences at the University of North Carolina at Chapel Hill. She holds a joint appointment in the Department of City and Regional Planning. Her research focuses on transportation planning, particularly the intersection of infrastructure, technology, and public health. She leads projects addressing urban freight systems, road safety, and healthcare mobility challenges. Key affiliations include the Carolina Transportation Program and the Center for Urban and Regional Studies. Current research initiatives involve optimizing non-emergency medical transport, analyzing parcel delivery impacts, and rethinking traffic impact assessments. She has published extensively on youth travel patterns, school siting policies, and the effects of emerging mobility services on vulnerable populations. Her work bridges academic research and policy application, with a focus on equity and sustainability. She is actively involved in shaping interdisciplinary programs and global partnerships within the university's social sciences division.

• Control Theory
• Applied Mathematics
• Computational Mechanics
• +7 more

Goong Chen is a Professor at Texas A&M University (TAMU) within the College of Arts & Sciences. His research focuses on Control Theory, Applied Mathematics, and interdisciplinary applications in computational mechanics, fluid dynamics, and quantum systems. He holds a Ph.D. from the University of Wisconsin (1977) and a B.S. from National Tsing-Hua University (1972). His research interests span computational biomechanics, forensic modeling, nanofluidics, and mathematical physics. Recent work includes modal analysis of animal motion, crash mechanics of aircraft, and forensic reconstruction of disasters. He has contributed to theoretical advancements in PDEs, nonlinear dynamics, and quantum computing. Chen’s articles address cutting-edge topics like thermoelastic plates, Volterra equations, and DFIM systems. He has pioneered numerical methods for complex systems using OpenFOAM and finite element techniques. His computational models have been applied to real-world scenarios such as submarine implosions and chemical warfare forensics. No academic awards are explicitly listed, but his extensive publication record reflects significant contributions to applied mathematics and engineering. He leads research teams focused on interdisciplinary challenges in computational science and engineering.

• Statistical Mechanics
• Probability Theory
• Discrete Geometry
• +3 more

Richard Kenyon is the Erastus L. DeForest Professor of Mathematics at Yale University, serving as Director of Undergraduate Studies. His research focuses on statistical mechanics, probability, and discrete geometry, with notable contributions to dimer models, random tilings, and integrable systems. He has explored topics such as limit shapes, phase transitions, and combinatorial configurations. His work intersects algebraic geometry, combinatorics, and mathematical physics, often involving the analysis of lattice models and their applications. His research includes open problems such as tiling optimization, geometric spanning surfaces, number theory questions, and rigidity of tilings. Kenyon's gallery showcases visualizations of mathematical concepts, including random triangulations, Vinnikov curves, and conformal mappings. His academic contributions span over three decades, with recent articles addressing dimers, webs, and eigenvalue properties. He actively collaborates on projects like the six-vertex model, multiwebs, and renormalizable dynamical systems. Kenyon’s academic service includes directing undergraduate studies at Yale and contributing to initiatives in discrete differential geometry. His work highlights the interplay between pure mathematics and applied probability, with applications in physics and combinatorial optimization.

Yan Kyaw TunView profile

Assistant Professor

• Edge Computing
• Multi-Access Edge Computing
• Resource Allocation
• +12 more

Yan Kyaw Tun is a Tenure Track Assistant Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design, located in Copenhagen, Denmark. His research lies at the intersection of wireless communications, edge computing, and artificial intelligence, with a strong focus on next-generation networks (5G/6G), UAV-assisted systems, and intelligent resource management. His educational background includes a Ph.D. in Computer Engineering from Kyung Hee University, South Korea, where he was awarded the Best Ph.D. Thesis Award in 2021, and a Bachelor of Engineering in Marine Electrical Systems and Electronic Engineering from Myanmar Maritime University. Dr. Tun's research interests span Edge Computing , Multi-Access Edge Computing (MEC) , Resource Allocation , Unmanned Aerial Vehicles (UAVs) , Reinforcement Learning , Energy Efficiency , and Integrated Sensing and Communication (ISAC) . His work leverages AI and optimization techniques to enhance the performance of wireless networks, particularly in space-air-ground integrated systems and satellite-HAP environments. The recent publications highlight a clear trend toward intelligent and sustainable networking: the integration of STAR-RIS (Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces), Federated Learning for satellite-HAP systems, and AI-driven optimization for UAV trajectories and beamforming. These works are published in high-impact venues such as IEEE Transactions on Mobile Computing and IEEE ICC , showcasing his leadership in cutting-edge communication technologies. His scientific accolades include: IEEE ComSoc Outstanding Young Researcher Award for EMEA Region (2024) Best Ph.D. Thesis Award (2021) Student Best Paper Award at APNOMS 2019 Korea Network Operation and Management Conference Award (2020) Korea Computer Congress 2018 Award Dr. Tun is actively engaged in the academic community as an advisor and grant participant. Though no direct advisees are listed, his involvement in large collaborative projects—evidenced by co-authorship with senior researchers like Prof. Choong Seon Hong—indicates mentorship and team leadership. He has served on the editorial boards of IEEE Internet of Things Journal , IEEE Open Journal of the Communications Society , and IEEE Network , and has secured research support through participation in IEEE-organized workshops and special issues. He is a key organizer of upcoming workshops, including the 'Sustainable AI for Next-Generation Wireless Communications and Networking' at IEEE GLOBECOM 2025 and the 'Digital Twin Networks' workshop at IEEE/CIC International Communications in China 2025, reflecting his role in shaping future research directions in intelligent and green networking.

• Evolutionary Genetics
• Microbial Symbiosis
• Genome Reduction
• +7 more

Rosario Gil García is a Professor in the Department of Genetics at the Faculty of Biological Sciences, University of Valencia. She is affiliated with the Institute for Biological Systems Integration (I2SYSBIO) and leads research within the GENEVOL Evolutionary Genetics group. Her work bridges molecular genetics, evolutionary biology, and systems biology. Her research focuses on evolutionary genetics of microbial symbioses , particularly in insects. Key areas include genome reduction, minimal genomes, endosymbiont evolution (e.g., Buchnera , Tremblaya , Wolbachia ), and the functional dynamics of gut microbiota in cockroaches and aphids. She investigates how long-term symbiosis shapes genome architecture and metabolic dependencies. The recent publication trends highlight a strong emphasis on minimal cellular systems , synthetic biology applications , and vector control strategies using Wolbachia-mediated incompatibility in Aedes albopictus . Her work combines comparative genomics, experimental microbiology, and systems-level modeling to understand the limits of life and harness symbiosis for biotechnological innovation. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: While no list of advisees is provided, her role as a PhD supervisor (having been supervised herself) and her leadership in a major research group suggest active mentoring. She is likely involved in competitive research grants related to evolutionary genomics and synthetic biology, though specific funding sources are not listed. Labs and Teams: She is an integral member of the GENEVOL Evolutionary Genetics research group and the I2SYSBIO institute, both of which foster interdisciplinary research in biological systems, evolution, and genomics. These affiliations provide a collaborative environment for advanced genomic and experimental studies.

• Computer Architecture
• Computer Systems
• Approximate Computing
• +10 more

Pejman Lotfi-Kamran is an Associate Professor at the School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Tehran, where he also serves as the head of the school and director of Turin Cloud Services. His research focuses on computer architecture, systems, approximate computing, and cloud computing, with an emphasis on performance and energy efficiency for big-data applications. His educational background includes: Ph.D. in Computer Science, EPFL (2013) M.Sc. in Electrical and Computer Engineering, University of Tehran (2005) B.Sc. in Electrical and Computer Engineering, University of Tehran (2002) Lotfi-Kamran's research spans computer architecture innovations, including data and instruction prefetching, networks-on-chip, coherence protocols, and many-core processor design. He has pioneered work on scale-out processors, neural acceleration for GPUs, and approximate computing frameworks. His publications appear in top venues such as ISCA, HPCA, MICRO, and IEEE/ACM journals. His recent articles reflect a strong trend in improving system performance through intelligent prefetching, efficient NoC designs, and energy-aware architectures. Key themes include reducing frontend bottlenecks, optimizing cache behavior, and enhancing data delivery in large-scale systems. His work often combines cross-stack insights with hardware-software co-design for real-world impact. Scientific awards and recognitions include: 2017 CADS Best Paper Award 2016 Young Faculty Award from Iran's National Elites Foundation 2012-2013 Intel Ph.D. Fellowship 2012 and 2011 HiPEAC Paper Awards 2011 HPCA Best Student Paper Finalist Multiple academic honors from University of Tehran He has advised several graduate students including Paria Darbani, Ali Ansari, Mohammad Bakhshalipour, and Farid Samandi, many of whom have co-authored significant papers. His teaching spans institutions like Sharif University of Technology, Iran University of Science and Technology, and EPFL, covering advanced computer architecture and multiprocessor systems. He has led research projects such as AxBench and CloudSuite on Simics, and contributed to national initiatives like Iran’s National Grid. He is actively involved in tool development and continues to shape research in next-generation computing systems. He leads the Turin Cloud Services initiative at IPM and is deeply engaged in both theoretical and applied aspects of computer systems research, with ongoing work in neural acceleration, approximate computing, and scalable architectures.

Caroline SchuppliView profile

Researcher

• Evolutionary Biology
• Cognitive Development
• Social Learning
• +5 more

Dr. Caroline Schuppli is a Max Planck Research Group Leader at the Max Planck Institute of Animal Behavior in Konstanz and a Freigeist Fellow by the Volkswagen Foundation. She serves as IMPRS QBEE faculty , Adjunct Researcher at the University of Zürich, and Director of the SUAQ Orangutan Research Project in Indonesia since 2017. Her work bridges evolutionary biology and cognitive ecology through longitudinal studies of Sumatran orangutans. Education: PhD in Evolutionary Biology (2012-2016), University of Zürich MSc in Anthropology (2010-2012), University of Zürich BSc in Biology (2007-2010), University of Zürich Her research investigates how social learning , environmental complexity , and maternal behavior shape cognitive evolution in great apes. Key themes include: Comparative analyses of wild vs. captive orangutan cognition Development of ecological skills and cultural repertoires Role of curiosity and innovation in cognitive evolution Interplay between life history and brain size trade-offs Recent publications emphasize nested skill acquisition , maternal behavior plasticity , and cross-taxa comparisons of social learning mechanisms. She has mentored PhD candidates like Nora Slania , Adriana Luna , and Emma Lokuciejewski . Scientific Awards: Freigeist Fellowship (2021) Swiss National Science Foundation Postdoc Funding (2019-2020) As President of the SUAQ Foundation and collaborator with institutions across Switzerland and Germany, she integrates fieldwork at Suaq Balimbing with global comparative frameworks.

Michelle BorkinView profile

Assistant Professor

• Data Visualization
• Human-Computer Interaction
• Visual Analytics
• +5 more

Michelle Borkin is an Assistant Professor in the Khoury College of Computer Sciences at Northeastern University’s Boston campus, where she co-leads the Visualization @ Khoury Lab and co-directs the Northeastern Visualization Consortium (NUVis). She additionally serves as Affiliated Faculty with the NULab for Text, Maps, and Networks and with the Information Design & Data Visualization Program in the College of Arts, Media, and Design. Education PhD, Applied Physics, Harvard University School of Engineering and Applied Sciences (2014) MS, Applied Physics, Harvard University BS, Astronomy & Astrophysics and Physics, Harvard University Research Interests Borkin’s research integrates data visualization and human-computer interaction to create novel techniques that enable discovery across disciplines. Her work spans: Multidimensional brushing-and-linking methodologies 3D data visualization and selection techniques Tree and network visualization Visualization evaluation methodologies and perception/cognition theory Accessibility and visualization for social good Medical and astrophysical visualization applications Publication Trends Across more than 50 peer-reviewed papers, Borkin’s research exhibits three dominant threads: (1) foundational studies on visualization perception and memorability, (2) design and evaluation of novel interactive tools for complex data (medical, astronomical, political, and social media), and (3) methodological contributions such as the Design Study “Lite” Methodology that accelerate visualization pedagogy and community-engaged research. Awards & Honors CHI 2020 Best Paper Award IEEE VIS 2020 Best Poster Honorable Mention IEEE VIS 2018 Best Poster Award NSF Graduate Research Fellowship NDSEG Graduate Fellowship TED Fellow Advising & Grants Borkin currently advises five PhD students—Jane Adams, Mackenzie Creamer, Franc O, Aditeya Pandey, and Laura South—and has previously mentored Michail Schwab and Uzma Haque Syeda. Her research has been supported by NSF, NDSEG, and TED fellowships, as well as internal Northeastern awards. Labs & Teams Co-Lead, Visualization @ Khoury Lab Co-Director & Co-Founder, Northeastern Visualization Consortium (NUVis) Affiliated Faculty, NULab for Text, Maps, and Networks Affiliated Faculty, Information Design & Data Visualization Program, CAMD