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Knarik TunyanView profile

Visiting Assistant Professor

• Linear Algebra
• Numerical Analysis
• Linear Programming
• +11 more

Knarik Tunyan is a Visiting Assistant Professor in the Department of Mathematics/Computer Science at Purchase College, State University of New York, within the School of Natural and Social Sciences. She contributes to undergraduate education through courses in Linear Algebra, Calculus, Differential Equations, and advanced topics in mathematics. Education: PhD in Technology, Tampere University of Technology, Finland MS in Mathematics, Yerevan State University, Armenia Her research integrates applied mathematics with computational science, focusing on Linear Algebra, Numerical Analysis, Linear Programming, and Computational Inverse Problems . She explores mathematical methods in signal and image processing, optimization, network theory, economics, and biostatistics. Recently, she has been investigating the use of technology in mathematics education, including 3D printing and software tools like Mathematica and OpenSCAD. The 15 most recent publications highlight a consistent trajectory in matrix computations, optimization algorithms, and interdisciplinary applications . Early work centered on pivot rules and interior-point methods, particularly their behavior on challenging problems like the Klee-Minty cube. Later contributions expanded into image compression using QkRk factorization, Bayesian metabolic modeling, and educational innovations involving STEAM and 3D visualization. The articles reflect a blend of theoretical rigor and real-world application, spanning fields from computational biology to educational technology. Scientific Contributions and Recognition: Active presenter at international conferences including ICTCM and WCGO Published in reputable journals such as SIAM Journal on Matrix Analysis and Applications , Journal of Theoretical Biology , and Inverse Problems and Imaging Contributions to algorithmic efficiency in least squares and optimization She advises on curriculum development and student learning, particularly in integrating technology into mathematical instruction. Though no formal students are listed, she mentors through senior seminars and research-oriented courses. She has not received explicitly mentioned awards or grants in the provided text. Her work is supported by institutional resources and collaborative networks in computational mathematics and STEM education. Dr. Tunyan is involved in academic outreach and technological experimentation, especially through her presentations on 3D printing and mathematical software. She maintains regular office hours and engages students through digital platforms like Starfish, emphasizing accessibility and active learning.

Mioara JoldesView profile

Professor

• Computer Arithmetic
• Validated Computing
• Computer Algebra
• +5 more

Mioara Joldes is a Directeur de Recherche (DR) at CNRS working in the ROC team at LAAS-CNRS (Laboratory for Analysis and Architecture of Systems) in Toulouse, France. She has been a permanent CNRS researcher at LAAS since 2013. Her work bridges rigorous mathematical computing with practical aerospace applications, particularly in space surveillance and collision avoidance. She collaborates extensively with French space agencies like CNES and has developed algorithms that have been tested on satellites including the ESOC OPS-SAT CubeSat and embedded in the CNES ASTERIA software. Dr. Joldes received her Ph.D. from École Normale Supérieure de Lyon in 2011. In 2019, she earned her Habilitation from Toulouse III Paul Sabatier University with a dissertation focused on building efficient symbolic-numeric objects, algorithms, and software tools with space-based applications. Her academic journey reflects a strong foundation in mathematical computing translated into practical aerospace solutions. Her research spans three interconnected domains: Computer Arithmetic, where she improves the accuracy and reliability of numerical computations; Symbolic-Numeric Algorithms, developing methods that combine symbolic and numerical approaches for validated computing; and Aerospace Applications, particularly in Space Surveillance and Tracking. Her work enables mathematically rigorous error bounds for computations used in critical aerospace systems, ensuring safety in space operations through validated numerics that provide "sure, yet reasonably tight, error bounds." Her recent publications demonstrate a strong focus on collision probability computation in space, validated numerical methods for differential equations, and efficient implementations of mathematical functions. She frequently collaborates with Denis Arzelier, Florent Bréhard, and other researchers in developing algorithms that have transitioned from theoretical foundations to practical space applications, with several papers receiving significant recognition in their fields. Distinguished Paper Award at ISSAC 2019 for work on algebraic reconstruction of measures with holonomic density Best Paper Award at ASAP 2020 for efficient FPGA implementation of the Probit function CNRS Bronze medal in 2021 recognizing her research contributions Dr. Joldes leads the PRESTO International Emerging Actions Project on Probabilistic Reliable and Efficient numerics for Stochastically-constrained Trajectory Optimization. Her research has received funding from CNES and other space agencies, supporting technology transfer from theoretical mathematics to operational space systems. She has supervised multiple students working at the intersection of validated computing and aerospace applications, with her methods being implemented in operational systems used by space agencies worldwide. As a key member of the ROC (Robotique et Calcul) team at LAAS-CNRS, she develops critical software tools like CAMPARY (CudA Multiple Precision ARithmetic librarY) and contributes to Sollya, an environment for developing safe floating-point code. Her work on orbital collision probability evaluation has been featured in major publications including CNRS-Le Journal, La Tribune, Les Echos, and L'usine Nouvelle, demonstrating the real-world impact of her research in ensuring safe space operations.

Jeffrey D. BlanchardView profile

Professor

• Applied Harmonic Analysis
• Compressed Sensing
• Matrix Completion
• +7 more

Jeffrey D. Blanchard is a Professor in the Department of Mathematics and Statistics at Grinnell College. He also holds the endowed Donald L. Wilson Professor of Enterprise and Leadership title and directs the Donald and Winifred Wilson Center for Innovation and Leadership. His academic journey includes a Ph.D. from Washington University in St. Louis (2007), followed by a VIGRE Postdoctoral Fellowship at the University of Utah (2007–2009) and an NSF International Research Fellowship at the University of Edinburgh (2010). His research focuses on applied and computational harmonic analysis, particularly compressed sensing, matrix completion, composite dilation wavelets, and GPU-accelerated scientific computing. These areas intersect with digital signal processing, high-dimensional geometry, and random matrix theory. He has developed efficient algorithms for sparse recovery and large-scale data processing, often leveraging graphical processing units for performance gains. The recent publications reflect a consistent trend in algorithmic development for compressed sensing and sparse approximation, with increasing emphasis on GPU implementations and structured sparsity. His work bridges theoretical analysis with practical computational solutions, often resulting in open-access software tools like GAGA, GGKS, and GGMS. NSF International Research Fellowship (2010) NSF Grants: DMS 1112612, DMS 1620390, OISE 0854991 Harris Faculty Fellowship (2013–2014) MAA Project NExT Fellow (2008–2009) Department of Homeland Security Fellowship (2003–2006) Blanchard has advised numerous undergraduate research projects in areas such as GPU-based k-selection, joint sparsity, and composite dilation wavelets. His research has been supported by multiple National Science Foundation grants focused on algorithm analysis and high-performance computing. He has taught a wide range of courses including Calculus, Numerical Analysis, and Wavelet Applications. He leads a research group that develops GPU-accelerated algorithms for compressed sensing and sparse recovery. His software packages—GAGA, GGKS, and GGMS—are publicly available and used for high-performance computing tasks such as greedy pursuit and order statistics selection on GPUs.

Nunzio TuccittoView profile

Associate Professor

• Molecular Communication
• Nanomaterials
• Physical Chemistry
• +3 more

Nunzio Tuccitto is an Associate Professor of Physical Chemistry at the University of Catania. His research focuses on molecular communication systems for wave-denied environments, hazardous gas detection, and big-data processing for mass spectrometry. He supervises PhD students and leads major EU-funded projects like ERMES. Education : PhD in Chemistry (2007), University of Catania Research Interests : Designing nanomaterials for molecular communication, developing carbon-based sensors for warfare agents/explosives, and advancing machine learning methods for multisensor data. His work bridges physical chemistry, nanotechnology, and biomedical engineering. Recent Research Trends : 2020s publications emphasize quantum dots for biological fluid communication, lemon waste-derived nanomaterials, and environmental pollutant monitoring via drones. Key themes include signal reliability, biocompatibility, and sustainable synthesis techniques. Scientific Awards ACM NanoCom 2024 Best Work-In-Progress Paper Italian Chemical Society 2021 Distinguished Oral Presentation Royal Society of Chemistry's Beynon Prize (2009-2010) FAMELAB-2018 Catania Winner Advising & Grants : Supervises 3 PhD students. Coordinates €3.7M EU ERMES project (2025-2028) and leads multiple national/international grants totaling €26M. Collaborates with institutions in Poland, Belgium, Canada, and Germany. Labs & Teams : Member of the Department Board, vice-coordinator of Materials Science PhD school, and leads 60 researchers in SiciliAn Micronanotech Center's Environment WP.

Rami MansourView profile

Assistant Professor

• Mechanical Engineering
• Additive Manufacturing
• Fatigue and Fracture Mechanics
• +6 more

Rami Mansour is a Tenure Track Assistant Professor in the Department of Mechanical and Production Engineering at Aarhus University, under AU Engineering. His research is centered on mechanical behavior of materials, particularly in additive manufacturing, fatigue, plasticity, and fiber-based networked materials. He contributes to advanced modeling and experimental validation in material science and production engineering. Research Interests: His work spans additive manufacturing , fatigue and fracture mechanics , cyclic plasticity , stochastic modeling of fiber networks , and thermal stress analysis in metal 3D printing . He investigates how microstructural evolution and process parameters affect material performance and durability. The recent publications show a strong focus on fatigue life prediction of stainless steels (304L, 316L), damage modeling in anisotropic materials , and data-driven approaches such as machine learning for moisture dynamics. There is a consistent integration of numerical simulation with experimental validation , especially in additive manufacturing and fiber network mechanics. Scientific Projects: ACCURATE : Achieving Resilience through Manufacturing as a Service, Digital Twins and Ecosystems (2024–2026) Collaborations and Advising: While no formal students are listed, he collaborates extensively with researchers including M. Subasic, M. Alzweighi, A. Kulachenko, and G. Hultgren. His involvement in large-scale modeling and experimental projects suggests active supervision and team leadership. He is engaged in interdisciplinary work bridging mechanics, materials, and digital manufacturing. Laboratories and Facilities: His work involves advanced laboratories for mechanical testing, additive manufacturing (including electron beam melting), and computational modeling. The department supports experimental and simulation-based research in production engineering and material behavior.

• Computational topology
• Topological data analysis
• Machine learning
• +7 more

Francesco Vaccarino is an Associate Professor in the Department of Mathematical Sciences "GL Lagrange" (DISMA) at the Polytechnic University of Turin and a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is actively involved in research, teaching, and doctoral supervision across multiple programs, including Mathematical Sciences, Applied Mathematics, and Artificial Intelligence. Research Interests: Computational topology Topological data analysis (TDA) Machine learning and geometric learning Algebraic and geometric methods in data science Complex networks and higher-order interactions His recent publications reflect a strong interdisciplinary focus, combining topology with machine learning, neuroscience, and physics. Key themes include persistent homology, simplicial network models, and topological visualization of complex systems. He has made significant contributions to understanding brain networks, scientific collaboration patterns, and phase transitions through topological methods. Scientific Awards: The Best Science Visualizations of the Year (Wired.com, 2014) Advising and Grants: He supervises multiple PhD students in Mathematical Sciences and Artificial Intelligence. He has led research projects funded by competitive tenders (e.g., XTERA-FOOD) and commercial contracts (e.g., with FPT Industrial SPA and Stellantis), focusing on AI, digital transformation, and industrial data analysis. He has served as Scientific Director for corporate training programs in AI and data science. Conferences and Leadership: He has been Program Chair for several international events including AMTCS7, TOPDRIM, Toponets15, and ECCS 2013, promoting the application of topology in data science. Labs and Affiliations: He is a core member of SmartData@PoliTO, a leading data science laboratory fostering interdisciplinary research in big data and AI.

Fredrik AnderssonView profile

Associate Professor

• Algebra
• Geometry
• Discrete Mathematics
• +9 more

Fredrik Andersson is an Associate Professor at Linköping University, affiliated with the Department of Mathematics (MAI), specifically within the division of Algebra, Geometry and Discrete Mathematics (ALGD). His work bridges pure mathematics and applied computational systems, with a strong foundation in theoretical physics and recent contributions to information systems. Research Interests: His primary fields include Algebra, Geometry, Discrete Mathematics, and Mathematical Physics. He has made significant contributions to spinor theory and general relativity, particularly in the context of Lanczos potentials and curvature-free connections. More recently, his research has expanded into applied domains such as cloud-based ERP systems, indicating a growing interest in digital transformation and enterprise computing. Publication Trends: His scholarly output spans over two decades, beginning with deep theoretical work in mathematical physics around 2000–2001, followed by a notable shift toward applied computer science and information systems by 2025. This evolution reflects a broad intellectual range and interdisciplinary adaptability, with consistent contributions to high-level mathematical modeling across domains. No scientific awards or honors are mentioned in the available text. Advising and Grants: There is no public information available regarding student supervision, research grants, or funded projects. Further details may be available through internal university resources or direct inquiry. Laboratories and Research Groups: Fredrik Andersson is a member of the Algebra, Geometry and Discrete Mathematics (ALGD) research division at Linköping University. This group conducts research in algebra, geometry, topology, dynamical systems, combinatorics, and graph theory, and consists of approximately twenty academics including faculty, researchers, and doctoral students.

• Wireless Communications
• Remote Sensing
• Distributed Systems
• +6 more

Juan Carlos Merlano Duncan is a Research Scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specializing in the SigCom department. He contributes to the SATSENT project with Prof. Ottersten and Dr. Symeon Chatzinotas, focusing on satellite sensor networks for spectrum monitoring. His roles include advancing technologies in wireless communications, remote sensing, and embedded systems. **Education:** Bachelor's in Engineering from Universidad del Norte (2004) M.Sc. and Ph.D. in Telecommunications from Universitat Politècnica de Catalunya (2009 and 2012) **Research Interests:** Wireless communications, remote sensing, distributed systems, Software Defined Radios (SDR), embedded systems, and AI-driven satellite technologies. His work emphasizes FPGA design, radar systems (e.g., SABRINA project), and cognitive radio networks. **Publications:** Recent work spans AI in satellite communications, digital beamforming, and energy-efficient MIMO systems. Notable themes include STAR-RIS networks, onboard image classification, and THz reconfigurable surfaces. **Grants & Advising:** No explicit grants or advisees listed, though his projects imply collaborative research funding. He has led FPGA implementations for radar and cognitive radio systems. **Labs & Teams:** Core member of SnT’s SigCom group, contributing to satellite telecommunication testbeds using COTS devices and onboard processing architectures.

• Digital Signal Processing
• Nonlinear Dynamics
• Electronics Engineering
• +3 more

Alessio Perinelli is a Researcher (RTD-A) in the Department of Physics at the University of Trento, located at Via Sommarive, 14. He specializes in experimental physics and electronics, focusing on topics like nonlinear dynamics, signal processing, and electronic instrumentation. His research integrates mathematical modeling with practical applications in fields such as brain connectivity analysis, space particle detection, and chaos theory. In teaching, he contributes to courses like Physics Laboratory III and Laboratory of Advanced Electronics , emphasizing hands-on learning in electronics and experimental physics. These courses cover topics ranging from basic electronic circuits to advanced FPGA-based signal processing and digital systems. His recent research highlights include studies on gamma-ray bursts using space-borne detectors (HEPD series), noise-induced chaos in physical models, and the application of permutation entropy in EEG analysis. He is also actively involved in developing hybrid microdosimeters for radiation field characterization and exploring fractal patterns in geophysical systems. Perinelli is a member of the Italian Society of Statistical Physics (SIFS) and has co-authored numerous peer-reviewed publications since 2018, focusing on experimental electronics, data analysis techniques, and interdisciplinary applications of physics principles.

Rennie KaundaView profile

Associate Professor

• Rock Mechanics
• Soil Mechanics
• Slope Stability
• +12 more

Rennie Kaunda is an Associate Professor in the Department of Mining Engineering at the Colorado School of Mines (CSM), where he has been a faculty member since 2014. His work integrates rock and soil mechanics with computational modeling to advance sustainable mining practices. He leads the Mining Geotechnics Research Group, which focuses on innovation in ground control, slope stability, and environmental stewardship in mining operations. PhD, Western Michigan University (2007) MS, University of Arizona (2002) BS, University of Arizona (1999) Prof. Kaunda's research centers on rock and soil mechanics , particularly in slope stability , deep underground excavations , and environmental sustainability in mining . He is a pioneer in applying artificial neural networks and computational modeling to solve complex geotechnical problems in mining and civil engineering. His work spans from predicting blast fragmentation to modeling progressive landslides using limited field data. His recent publications reveal a strong trend in integrating machine learning and data-driven methods with traditional geomechanics. Topics include neural network applications in true triaxial stress analysis, landslide displacement modeling, and optimization of rock fragmentation. His research bridges fundamental mechanics with practical industrial applications, particularly in harsh and deep mining environments. WMU Research Grant David Kuenzi Award GSA Research Fellowship Phi Eta Sigma Honor Society Award ZAL Holdings Fellowship Prof. Kaunda is actively involved in mentoring students and leading interdisciplinary research projects through the Mining Geotechnics Research Group. While specific grant details are not listed, his collaborations with the US Army Corps of Engineers and extensive fieldwork across multiple continents suggest robust funding and industry partnerships. His work emphasizes training the next generation of engineers in sustainable and technologically advanced mining practices. He leads the Mining Geotechnics Research Group at CSM, which focuses on developing advanced technologies for sustainable mining. The group engages in multi-disciplinary research involving rock mechanics, hydrogeology, and computational modeling to improve safety, efficiency, and environmental outcomes in mining operations.

Hank TheissView profile

Academic

• Photogrammetry
• Data Adjustment
• Error Propagation
• +8 more

Hank Theiss is a Research Associate Professor at the University of Arkansas, College of Arts & Sciences , affiliated with the Center for Advanced Spatial Technologies (CAST) since 2020. Previously, he served as Chief Scientist at Centauri (formerly IAI) from 2001-2020, leading photogrammetry research for NGA, and as Visiting Assistant Professor at Purdue University (2000-2001). PhD in Civil Engineering (Photogrammetry) from Purdue University (2000) MS in Civil Engineering (Geomatics) from Purdue (1995) BS in Civil Engineering from Virginia Tech (1994) Research Interests focus on: Sequential bundle adjustment for multi-image analysis Generic sensor modeling (GLAS/GFM) for spaceborne sensors like Key Hole (KH) Error propagation and accuracy assessment in 3D GEOINT products AI/ML/DL augmentation for photogrammetric workflows His scientific awards include: Photogrammetric (Fairchild) Award (2021) Centauri Technical Fellow (2019) Impact Team Award (2016) ASPRS Davidson Award (2016) Millie Bayne Distinguished Service Award (2011) Professional Contributions include developing the first bistatic SAR sensor model, prototyping narrow FOV optical motion imagery algorithms for Global Hawk UAVs, and leading the Community Sensor Model Working Group (CSMWG) to standardize geopositioning capabilities across government/industry/academia.

David StielerView profile

Researcher

• Agent-Based Modeling
• Modular Precast Concrete Construction
• Combinatorial Optimization
• +3 more

David Stieler is a Research Associate at the Institute of Computational Design and Construction (ICD) at the University of Stuttgart. His work focuses on agent-based modeling and modular precast concrete construction , particularly through the Cluster of Excellence IntCDC . Education: Dipl.-Ing. in Architecture, University of Innsbruck, Austria Research Interests include: Combinatorial optimization for component reuse Additive manufacturing in construction Agent-based systems for fabrication-aware design Sustainable, low-carbon building strategies Flow production methods for modularization Scientific Contributions span computational frameworks for circular construction, optimization algorithms for reinforced concrete reuse, and digital workflows for earth-textile hybrid systems. Awards : Dean's Prize of the Faculty of Architecture (University of Innsbruck)

Sema AlaçamView profile

Associate Professor

• Architectural Design
• Computational Design
• Artificial Intelligence in Architectural Education
• +5 more

Sema Alaçam is an Associate Professor at Istanbul Technical University , affiliated with the Department of Architecture . She has active research in computational design , artificial intelligence in architectural education , and sustainable materials like rammed earth and reused wind turbine blades . Her work focuses on: Architectural heritage (e.g., Sinan mosques, Harran houses) Environmental comfort (thermal, natural ventilation) Digital tools (BIM, VR, AI-assisted design) Recent publications include machine learning models for heritage analysis and AI literacy in design education. She leads projects on robotic fabrication and digital stereotomy . Scientific recognition: Multiple İTÜ Academic Performance Awards (2021–2023) Sigradi Best Reviewer Award CAADRIA Best Presentation Award (2014) FABFEST Prizes (2017–2018)

• Visual Communication
• Digital Culture
• Educational Innovation
• +11 more

Dr. Antonio Fernández Coca is a Senior Lecturer in Graphic Expression at the University of the Balearic Islands (UIB) . With a PhD in 2003 focusing on user experience (UX) for web-based communication, he has pioneered the integration of digital tools and transmedia strategies in architectural education since the late 1990s. Education: PhD in Graphic Expression (UIB, 2003). Research Interests: Digital visual communication, educational innovation, UX design, and AI integration in teaching. Leadership: Served as Vice Rector for Digital Campus (2013–2021), redesigned UIB's Digital Classroom, and currently directs staff training programs aligned with Sustainable Development Goals. Publications: Authored Production and Graphic Design for the WWW (1999), The Art of Illustration (2013), and Selfie: Academic Self-Portraits (2021). Coordinated transmedia books and over 3 million educational video views. Projects: Led initiatives like Juguema (multimodal serious games), ZombUIB, and Genius-Up! (VR/AR educational games).

• Computational Design
• Digital Fabrication
• Architectural Education
• +3 more

Prof. Serbulent Vural is a Professor at Karadeniz Technical University's Faculty of Architecture, where he leads research in computational design and digital fabrication. He has held academic positions at KTU since 1997, advancing from Research Assistant to Professor (2023-present). He directs the KTU CODEFAB Laboratory and serves as Rector's Advisor, overseeing institutional design projects and technology integration. Education: Doctorate (2005): Karadeniz Technical University, Faculty of Architecture Postgraduate (2000): Karadeniz Technical University, Faculty of Engineering and Architecture Undergraduate (1996): Karadeniz Technical University, Faculty of Engineering and Architecture Research Focus: Vural explores computational design methodologies, parametric modeling, and digital fabrication in architecture. His work bridges traditional techniques (e.g., Anatolian weaving) with advanced technologies like robotic production. Key themes include architectural pedagogy, urban morphology (e.g., Diyarbakır housing studies), and sustainable material applications. Publication Trends: Recent articles (2018-2024) emphasize computational thinking in design education, robotic fabrication, and parametric applications. His research demonstrates a shift from vernacular architecture studies (2000s) toward technology-driven design innovation, with consistent focus on integrating mathematics and geometry into architectural practice. Awards & Honors: Four 2022 Engineering-Architecture Awards for urban/tribune design 2004 Historical Cities Union Award for urban revitalization Advising & Grants: Supervises doctoral candidates in computational design and urban studies. Secured funding for: Bamboo structural analysis (2022-2024) Robotic fabrication in architecture (2022-2023) Digital design pedagogy (2023-2024) Laboratories & Teams: Manages KTU CODEFAB Lab, specializing in computational design, robotic fabrication, and material experimentation. Collaborates with international researchers on technology-driven architectural solutions.