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Tania LizarazoView profile

Associate Professor

• Latin American Cultural Studies
• Transnational Feminisms
• Digital Storytelling
• +6 more

Tania Lizarazo is an Associate Professor at the University of Maryland, Baltimore County (UMBC), affiliated with the Department of Modern Languages, Linguistics & Intercultural Communication. She contributes to the Global Studies Program, Spanish Area, and MA in Intercultural Communication, with additional roles as Affiliate Faculty in Gender, Women’s + Sexuality Studies and Language, Literacy & Culture. Ph.D. in Latin American Literature and Cultures from UC Davis (2015) Research focuses on Latin American cultural studies, transnational feminisms, digital storytelling, and performance studies Key projects include mujerespacificas.org with Colombian Black peasant organizations and sexualidadescampesinas.ucdavis.edu with California farmworkers Author of Postconflict Utopias: Everyday Survival in Chocó, Colombia (University of Illinois Press, 2024) Her recent publications and collaborations emphasize digital storytelling as a tool for community engagement and critical analysis of race, gender, and violence in Latin America. She co-edited Repensando a Policéfalo (2006) and has published in journals like Journal of Latin American Cultural Studies and Corpografías . Her work bridges academic research with social justice initiatives. Current courses include topics on digital humanities, migration, Afro-Latin America, and performance studies. She collaborates with Dr. Thania Muñoz D. on the teaching project Intercultural Tales: Learning With Baltimore’s Immigrant Communities .

• Geometry
• Topology
• Quantum Field Theory
• +5 more

Ryan Grady is an Associate Professor in the Department of Mathematical Sciences at Montana State University, affiliated with the College of Letters & Science. His research bridges geometry, topology, and quantum field theory (QFT), with a focus on derived geometry and higher Lie theory. Research Interests: His work applies QFT techniques to geometric and topological problems, explores derived algebraic structures (e.g., L-infinity spaces, cosheaves), and investigates connections between renormalization group flows and sigma models. Recent publications address K-theoretic invariants, operadic structures in topology, and algebraic models for topological field theories. Scientific Awards: Stannard Award for Graduate Teaching (2021) NExT Fellow (2019) ICCM Best Paper Award (2018) Research Enhancement Grant (2018) Member, MSU Center for Faculty Excellence (2017) Education: Ph.D. and M.S. in Mathematics from the University of Notre Dame (2012, 2009), and B.S. in Mathematics from the Colorado School of Mines (2007). Students: Co-chaired Eric Berry (PhD 2021) and Adam Howard (PhD 2021), advised Garrett Oren (MS 2021), and mentored Bryce Morrow (BS 2023).

• Architecture
• Urban and regional planning
• Design
• +5 more

Professor Alan Penn is a leading academic at University College London's The Bartlett School of Architecture , where he holds the title of Professor in Architectural and Urban Computing. He previously served as Dean of the Bartlett Faculty of the Built Environment from 2009 to 2019 and has been instrumental in establishing Space Syntax Ltd , a UCL knowledge transfer spin-out company. His affiliations include membership in the Space Syntax Laboratory, board membership of UCL Consultants Ltd, and trustee status at Shakespeare North Trust. Education: BSc (1978), Dip Arch (1980), MSc (1983) - all from University College London Alan Penn’s research investigates how spatial design influences social and economic behaviors through innovative space syntax methodologies . Key areas include: Agent-based simulations of human behavior Spatio-temporal representations of built environments Urban spatial network analysis Urban sustainability across multiple dimensions Cognitive markers in architectural design Historical urban growth modeling His recent publications demonstrate a strong focus on computational urbanism, evolutionary city patterns, and behavioral architecture. Research trends show interdisciplinary approaches combining architectural theory with: Machine learning applications Network science analysis Behavioral psychology insights Historical GIS techniques Complex systems modeling Public health considerations Scientific recognition includes: HEFCE Business Fellowship (2001-2005) KTP SE Region Award (2010) Multiple UCL Enterprise awards ‘Spirit of Enterprise’ Award (2008) As Principal Investigator he leads the £5m EPSRC-funded Urban Dynamics Lab , demonstrating sustained research excellence. His work extends to public engagement through: Shakespeare North Trust educational theatre development Media appearances (New Scientist, Slashdot) Public policy contributions

Andrew ElliottView profile

Senior Lecturer

• Statistics
• Data Analytics
• Modeling in Space and Time
• +8 more

Dr Andrew Elliott is a Senior Lecturer in the School of Statistics at the University of Glasgow. His research bridges Statistics , Computational Statistics , and Machine Learning & AI , with applications in Social & Urban Studies and Imaging, Image Processing & Image Analysis . Education: Not explicitly detailed in the text. Dr Elliott's work focuses on modeling in space and time , synthetic data generation , and network analysis . His recent publications explore fairness constraints in AI , agent swarms , and temporal network modeling , reflecting interdisciplinary applications in urban analytics and environmental science. His publications from 2014–2024 span network science , machine learning , image analysis , and geospatial studies . Key trends include privacy auditing , counterfactual explanations , and deep learning for network time series . Dr Elliott supervises doctoral students and has advised Zhengduo Zhao and Weiyue Zheng . He actively contributes to research groups in Statistics & Data Analytics and Machine Learning . Notable collaborations include work with Mihai Cucuringu and Gesine Reinert .

Shing-Tung YauView profile

Professor

• Differential Geometry
• Mathematical Physics
• General Relativity
• +3 more

Shing-Tung Yau is a distinguished mathematician and professor associated with the Shing-Tung Yau Center at Southeast University's School of Physics, reflecting his profound influence in mathematical physics. His career spans premier institutions including Harvard University (emeritus) and Tsinghua University, where he holds active positions. Yau's research centers on differential geometry , mathematical physics , and geometric analysis , with transformative work on Calabi-Yau manifolds underpinning string theory. His investigations into Einstein's equations, black hole thermodynamics, and geometric flows bridge pure mathematics and theoretical physics, driving advancements in quantum gravity and mirror symmetry. His publications reveal consistent focus on geometric structures in theoretical physics, particularly Calabi-Yau applications in string compactification and geometric flows for singularity analysis. Recent works emphasize Kähler-Einstein metrics and stability in algebraic geometry. Scientific accolades include: Fields Medal (1982) for contributions to partial differential equations and Calabi conjecture Wolf Prize (2010) for geometric analysis breakthroughs MacArthur Fellowship (1985) and Crafoord Prize (1994) National Medal of Science (1997) for unifying geometry and physics Yau has mentored over 50 doctoral students, including Gang Tian and Huai-Dong Cao, shaping modern geometric analysis. He leads collaborative initiatives like the Harvard-Yau Center and Tsinghua's Mathematical Sciences Center, fostering cross-disciplinary research in geometric methods for quantum gravity. Current efforts focus on geometric foundations of quantum information and gravitational wave mathematics.

Douglas S. BridgesView profile

Professor

• Constructive Mathematics
• Functional Analysis
• Banach Algebras
• +9 more

Douglas S. Bridges is a Professor of Pure Mathematics at the Department of Mathematics and Statistics, University of Canterbury, New Zealand (1999–). He holds academic qualifications from the University of Edinburgh (B.Sc. Hons), Newcastle (M.Sc.), and Oxford (D.Phil., D.Sc.), and is a Fellow of the Royal Society of New Zealand (FRSNZ) and Corresponding Fellow of the Royal Society of Edinburgh (CorrFRSE). Education: B.Sc. (Hons), Edinburgh; M.Sc., Newcastle; Dip.Ed., Edinburgh; D.Phil., Oxford; D.Sc., Oxford His research spans constructive mathematics , focusing on analysis (functional, real, complex) and topology (apartness spaces). He explores applications to mathematical economics (preference relations, demand functions), quantum logic , and computability theory . Recent work includes foundational studies in constructive reverse mathematics and proximity spaces. Key trends in his publications involve: Constructive foundations of Banach algebras and operator theory Topological properties of apartness spaces Constructive measure theory and numerical representation of preferences Scientific awards: Fellow of the Royal Society of New Zealand (FRSNZ) Corresponding Fellow of the Royal Society of Edinburgh (CorrFRSE) He has supervised PhD theses, including Michael (Yunchuan) Wang’s work on Constructive Analysis of Partial Differential Equations . Contact: d.bridges@math.canterbury.ac.nz .

• Wireless Communication
• Machine Learning
• Signal Processing
• +4 more

Prof. Dr. Haris Gačanin is a faculty member at RWTH Aachen University, affiliated with the Institute for Distributed Signal Processing under the College of Electrical Engineering. His research focuses on integrating machine learning with wireless communication systems, particularly in industrial IoT, edge computing, and network optimization. Current academic rank: Professor Contact: harisg@dsp.rwth-aachen.de Research Interests: Wireless systems, machine learning, signal processing, and network optimization. Key contributions include: Adaptive resource allocation in IIoT and vehicular networks AI-driven channel estimation and feedback mechanisms Security-oriented emitter identification via metric learning Federated/transfer learning for edge environments Hardware-efficient deep learning models for mmWave and THz communications Methodological Focus: Combines reinforcement learning, attention mechanisms, and robust neural architectures with practical implementations on FPGA and vehicular systems.

Joscha GedickeView profile

Professor

• Numerical Analysis
• Computational Mathematics
• Finite Element Methods
• +3 more

Joscha Gedicke is a Professor at the Institute for Numerical Simulation (University of Bonn), specializing in Numerical Analysis , Finite Element Methods , and Scientific Computing . His research focuses on adaptive algorithms, error estimation, and computational methods for partial differential equations (PDEs) and optimal control problems. Contact: gedicke@ins.uni-bonn.de | +49 228 73-69835 Teaching: Lectures on Hybrid High-Order Methods (V5E1), Adaptive Finite Element Methods (S4E1), and Discontinuous Galerkin Methods (V5E5). Research Trends: Gedicke's work spans Numerical Methods for PDEs , Adaptive Finite Element Analysis , Mixed and Discontinuous Galerkin Formulations , and Error Estimation . His recent publications emphasize Virtual Element Methods and Robust Discretizations for magnetostatic and optimal control problems. Collaborative Networks: He collaborates with researchers in computational mathematics, including institutions like TU Munich, University of Milano-Bicocca, and the University of Bonn's research seminar on Mathematics of Computation .

• Quantum Information
• Quantum Computing
• Quantum Many-Body Physics
• +9 more

Univ.-Prof. Dr. Norbert Schuch is a Professor of Physics and Mathematics at the University of Vienna, leading the Quantum Information and Quantum Many-Body Physics group. His research bridges Quantum Information Theory, Quantum Computing, and the study of complex quantum many-body systems, with a focus on Tensor Networks, Topological Order, and Symmetry Breaking. He has offices at both the Faculty of Physics (Boltzmanngasse 9) and Faculty of Mathematics (Oskar-Morgenstern-Platz 1). Research Interests : Quantum Information at the interface of Many-Body Physics, including Entanglement Theory, Topological Quantum Computation, Tensor Network algorithms, and Symmetry-Protected Topological (SPT) phases. His work develops numerical and analytical frameworks to study entanglement order parameters and prepare/experiment with topological states in quantum simulators. Teaching : Courses on Quantum Information, Quantum Computing, Theoretical Physics, and seminars on quantum many-body topics. Prior to Vienna, he was a tenured group leader at Max-Planck-Institute of Quantum Optics and a lecturer at Technical University Munich. Scientific Awards : ERC Consolidator Grant SEQUAM (2020–2025) FWF ESPRIT Programme ESP 306 FWF SFB BeyondC FWF Entanglement Order Parameters Research Trends : His recent publications explore Quantum Algorithms, Tensor Networks for Topological Phase Transitions, Entanglement Spectra, and Symmetry-Protected Phases. Key subfields include Non-Abelian Anyons, Chiral Spin Liquids, and Computational Complexity in Many-Body Systems. Group Members : Current team includes postdocs like Dr. Ilya Kull and Dr. András Molnár, with historical alumni spanning PhDs, Masters, and BSc students now at institutions like Xanadu, MIT, and Quantinuum.

Aoife GowenView profile

Professor

• Hyperspectral Imaging
• Sustainable Transport Policy
• Critical Thinking in Education
• +4 more

Professor Aoife Gowen is a leading academic at the UCD School of Biosystems & Food Engineering , specializing in hyperspectral imaging and its applications across medicine, food safety, and engineering. Her research, supported by prestigious European Research Council (ERC) funding, investigates water molecule interactions with surfaces to improve bone graft materials and develop innovative diagnostic tools for prostate cancer. She also leads Science Foundation Ireland (SFI)-funded projects on hyperspectral monitoring of bacterial growth for food safety. Beyond technical research, Professor Gowen has developed computational tools now integrated into commercial chemical analysis software. Her work spans interdisciplinary domains, including sustainable transport policy, critical thinking education, and promoting gender diversity in engineering. As a key figure in the Women on Walls initiative, she has enhanced visibility for women in STEM fields. Her recent publications focus on spectral technologies for food quality, microplastics characterization, and medical diagnostics, reflecting her commitment to addressing global challenges in health and sustainability. Scientific Awards: ERC Grant for water-surface interaction research Professor Gowen actively collaborates with European networks and industry partners, driving advancements in hyperspectral imaging applications. Her lab’s efforts to bridge computational science with real-world chemical analysis have positioned her as a pioneer in invisible chemistry visualization, impacting medicine, food, and environmental engineering.

Jie GaoView profile

Assistant Professor

• Machine Learning for Communications and Networking
• Internet of Things (IoT) and Industrial IoT
• Cloud and Multi-Access Edge Computing
• +7 more

Dr. Jie Gao is an Assistant Professor at the School of Information Technology , Carleton University, with cross-appointments at Dalhousie University (Adjunct Faculty, 2024) and Carleton University (2025). He holds a Ph.D. in Electrical and Computer Engineering from the University of Alberta (2014) and has held postdoctoral and research associate positions at Ryerson University (2017-2019), University of Waterloo (2019-2020), and Marquette University (2020-2022). His research focuses on machine learning for communications/networking , 6G wireless networks , cloud/multi-access edge computing , IoT/industrial IoT solutions , and network virtualization/digital twins . Research Leadership: Co-investigator on projects related to AI-assisted network slicing, digital twin-driven resource allocation, and integrated satellite-terrestrial networks Led work on energy-efficient UAV-assisted edge computing (IEEE Best Land Transportation Paper Award 2024) Professional Roles: Senior Member, IEEE Lead Associate Editor, IEEE Access Vehicular Technology Society Section (2020-present) Associate Editor, Springer Peer-to-Peer Networking and Applications (2020-present) IEEE Vehicular Technology Society Young Professional Ambassador (2024) Notable Contributions: Authored/co-authored books on Intelligent Computing and Communication for the Internet of Vehicles (Springer, 2023) and Connectivity and Edge Computing in IoT (Springer, 2021) Holds patents on medium access control methods (US Patents 2022, 2024) Received multiple IEEE service awards (2018-2024)

• Geotechnical Engineering
• Earthquake Engineering
• Soil-Structure Interaction
• +7 more

Ramin Motamed is a Professor in the Department of Civil & Environmental Engineering at the University of Nevada, Reno (UNR). His research focuses on geotechnical earthquake engineering, including soil-structure interaction, liquefaction mitigation, and nonlinear site response analysis. He has conducted extensive studies on deep foundations, ground motion analysis, and seismic design of structures. Motamed leads a research group involving postdocs and graduate students, and teaches advanced courses such as Geotechnical Earthquake Engineering and Foundation Engineering Design. His work integrates experimental methods (e.g., shake table tests) with numerical modeling to address challenges in seismic hazard mitigation. Key projects include evaluating helical piles for foundation settlement reduction, improving LRFD resistance factors for drilled shafts in Nevada, and analyzing site-specific ground motions using downhole array data. Motamed’s research has been published in journals like Soil Dynamics and Earthquake Engineering, and he collaborates with institutions globally, including Japan’s E-Defense facility. Current research emphasizes reducing uncertainties in ground motion prediction, optimizing mitigation measures for liquefaction-prone sites, and advancing predictive analytics for geotechnical design using machine learning. His lab facilities and field experiments enable large-scale validation of theoretical models, bridging geotechnical theory and practical engineering solutions. Teaching responsibilities include foundational and graduate courses covering geotechnical engineering principles, earthquake engineering, and advanced foundation analysis. Motamed’s advising includes over a dozen graduate students, many contributing to high-impact research in seismic resilience and geotechnical innovation.

Sarah Burke-SpolaorView profile

Associate Professor

• Gravitational Wave Detection
• Binary Supermassive Black Holes
• Fast Radio Bursts (FRBs)
• +3 more

Dr. Sarah Burke-Spolaor is an Associate Professor in the Department of Physics and Astronomy at West Virginia University and a member of the Center for Gravitational Waves and Cosmology (GWAC) . Her research focuses on dynamic astrophysical phenomena , including binary supermass of mass black holes , pulsar timing arrays for gravitational wave detection , and Fast Radio Bursts (FRBs) . Key Research Areas : Gravitational wave detection via pulsar timing Observational studies of binary supermassive black holes Fast Radio Burst detection and classification Galaxy formation and merger dynamics Dr. Burke-Spolaor mentors a team of students and postdocs including Gregory Walsh, Jessica Sydnor, Reshma Thomas , and Kshitij Aggarwal , whose work includes projects like the BHBinary/Galaxy Evolution Survey and The Petabyte Project for Radio Transients . Her awards include the Alfred P. Sloan Fellowship and recognition as a CIFAR Azrieli Global Scholar . Selected Article Trends : Leading gravitational wave research through NANOGrav's 15-year data set Multi-messenger astronomy targeting binary black hole systems FRB host galaxy characterization across telescopes Exploring unconventional astrophysical transients in the Galactic bulge Advancing pulsar timing array methodologies Developing next-generation radio interferometry techniques Scientific Awards : Alfred P. Sloan Fellow CIFAR Azrieli Global Scholar

Jason E. YbarraView profile

Assistant Professor

• Galactic Star Formation
• Protostellar Outflows
• Physics Education Research
• +2 more

Jason E. Ybarra serves as a Teaching Assistant Professor and Director of the WVU Planetarium and Observatory at West Virginia University. His academic home resides within the Astronomy and Astrophysics department, where he integrates observational astronomy with innovative educational practices. As coordinator for the Sloan Digital Sky Survey (SDSS-V) Faculty and Student Team (FAST) program, he bridges research infrastructure with undergraduate development. Dr. Ybarra's educational background includes: Ph.D. in Astronomy from University of Florida (NASA GSRP Fellow) M.S. in Physics from San Francisco State University (co-discoverer of precessing jet evidence) His research spans galactic star formation in regions like the Rosette Molecular Cloud, protostellar outflow dynamics , and physics education with special focus on neurodiversity inclusion . Historical astronomy investigations feature prominently, particularly in rediscovering early variable star observations. His educational philosophy emphasizes neurodivergent accessibility, reflected in publications on inclusive STEM pedagogy. Recent publications reveal interdisciplinary trends merging astronomical research with computational methods (CNN analysis of historical records) and social sciences (neurodiversity studies). The Sloan Digital Sky Survey serves as a unifying thread across observational, educational, and historical investigations. Scientific recognition includes: NASA Graduate Student Researchers Program (GSRP) fellowship NASA Florida Space Grant Consortium fellowship As an educator, Dr. Ybarra has taught across diverse settings from Davidson College to Drepung Loseling Monastery in India through the Emory-Tibet Science Initiative. His FAST program coordination creates sustained undergraduate research pathways within SDSS-V. Current projects integrate planetarium outreach with neurodiversity-aware instructional design. The WVU Planetarium and Observatory serves as his primary research and educational hub, while SDSS-V provides large-scale collaborative infrastructure. His work uniquely connects historical astronomical practices with modern neuroinclusive education frameworks.

• Photonics
• Optoelectronics
• Nanotechnology
• +4 more

Dr. Weilu Gao is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Utah. He holds a B.S. from Shanghai Jiao Tong University (2011) and a Ph.D. from Rice University (2016), followed by postdoctoral research there until 2019. Before joining Utah, he worked as a Photonics Designer at Lightmatter Inc. (2019–2020). His research focuses on photonics/optoelectronics of nanomaterials, including carbon nanotubes and 2D materials, with applications in computing, sensing, and energy. He has over 90 publications and 5,800+ citations. Research interests include reconfigurable photonics for machine learning, chiral photonic materials, and scientific computing using optical neural networks. Key projects involve developing diffractive optical neural networks (DONNs) for PDE-solving and energy-efficient computing, programmable chiral heterostructures, and wafer-scale aligned carbon nanotube architectures. His work bridges nanomaterial science with optical engineering, emphasizing scalable fabrication and cross-disciplinary applications. Notable achievements include publishing in Nature Communications , Advanced Photonics Research , and ACS Photonics . He leads the Weilu Gao Lab, which actively collaborates on NSF-funded projects (e.g., 2022 NSF award for carbon nanotube-based semiconductors). Professional activities include organizing workshops on chiral photonics and presenting at conferences like ECS Meetings. Grants include NSF funding for semiconductor research and collaborations with institutions like the University at Buffalo and Tokyo Metropolitan University. His lab recruits students and postdocs in scientific computing, photonics, and nanomaterials.