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Georgios PortokalidisView profile

Research Professor

• Systems Security
• Binary Analysis
• Software Hardening
• +1 more

Georgios Portokalidis is an Associate Research Professor at IMDEA Software Institute and Visiting Research Professor at Stevens Institute of Technology. He leads research in software systems security with focus on binary analysis, software hardening, and operating system security. His research develops practical defenses against software vulnerabilities through techniques like binary debloating, system call filtering, and hardware-assisted security. Current projects explore Rust language security, processor-assisted protection mechanisms, and vulnerability mitigation through code reduction. Publication trends show evolution from foundational binary analysis to applied security hardening, with recent emphasis on Rust security, hardware-assisted defenses, and real-world system protection. Work demonstrates consistent focus on practical, deployable security solutions. He has supervised numerous PhD students and postdocs, currently mentoring researchers at IMDEA. His group investigates binary analysis, software debloating, and system hardening techniques. Major grants include DARPA YFA (2021-2023) and ONR funding (2017-2022) supporting adaptive binary debloating research. Leads the systems security research group at IMDEA Software Institute, collaborating with international partners. Maintains active research partnerships and regularly contributes to top security conferences as program committee member.

Carlos J. MirandaView profile

Assistant Professor

• Graphic Design
• User Experience (UX) Design
• Animation
• +7 more

Carlos J. Miranda is an Assistant Professor at Florida A&M University (FAMU) in the School of Journalism & Graphic Communication. He specializes in teaching Graphic Design, User Experience (UX) Design, and Animation, leading initiatives like the Google + FAMU UX Design program. Previously, he served as an Adjunct Professor at FAMU (2019–2022) and Associate Professor at Tallahassee Community College (1998–2022). He holds an M.F.A. in Applied Arts from Florida State University and a BFA in Fine Arts from Florida International University. His research interests span graphic design pedagogy, digital art creation, and interdisciplinary projects merging music composition with visual art. Notable works include the short story Yellow House (2023), experimental films like Blue (2019), and the Bangladesh/US collaborative documentary Lashkata Ghar (2017). His artistic style combines surreal imagery with humor and sensuality, often utilizing mixed media and 3D rendering techniques. Miranda's career also includes mentorships under Academy Award-winning sound engineer Richard Portman and conceptual artist Jochen Gerz. His creative outputs range from orchestral arrangements to digital photography, reflecting a commitment to blending artistic disciplines. He currently advises no formal students but leads multiple courses including GRA 3135 (UX Design), GRA 3164 (Computer Animation Modeling), and GRA 4942 (Design Practicum II).

• Experimental Film
• Surrealist Cinema
• Documentary Film
• +3 more

Jeremy Moss is an Associate Professor of Film and Director of the Film and Media Arts Program at Franklin & Marshall College. His work bridges experimental filmmaking, surrealist aesthetics, and critical engagement with themes of fluidity and transgression. Born in Saint George, Utah, his films critically explore cultural norms and environmental landscapes through non-normative cinematic forms. Moss' films have screened globally at venues like TIFF Bell Lightbox, Anthology Film Archives, and festivals such as Jihlava International Documentary Film Festival. Education details are not explicitly stated, but his training in independent narrative and documentary filmmaking informs his pedagogical approach. Research interests center on avant-garde film practices, the materiality of film media, and cultural critique through experimental forms. Moss co-founded the Gleaners Film Festival (2022), a platform showcasing non-normative works, and programs for Moviate Underground Film Festival. His films are distributed by Light Cone. Key themes across his works include resistance to fixed narratives, boundary exploration, and sensory experimentation. Advising details are unavailable, but his teaching includes courses on film production, experimental techniques, and documentary practices.

Paul E. HandView profile

Associate Professor

• Machine Learning
• Artificial Intelligence
• Signal Processing
• +3 more

Paul E. Hand is an Associate Professor of Mathematics and Computer Science at Northeastern University, affiliated with both the College of Science and the Khoury College of Computer Sciences. He holds a Bachelor of Science in Applied and Computational Mathematics from the California Institute of Technology (2004) and a PhD in Mathematics from the Courant Institute at New York University (2009), where he received the Kurt O. Friedrichs Prize for outstanding dissertation. PhD in Mathematics, Courant Institute, NYU (2009) BS in Applied and Computational Mathematics, Caltech (2004) His research focuses on developing theoretical frameworks and algorithms for machine learning and artificial intelligence, particularly in signal recovery, phase retrieval, and vision/imaging. He also explores intersections of deep learning with convex optimization and has contributed to bilinear recovery problems. Recent publications emphasize generative models, inverse problems, and robust optimization techniques. Key themes include deep learning with provable recovery guarantees , convex programming for signal inversion , and manifold-based optimization . Kurt O. Friedrichs Prize for Outstanding Dissertation (2009) NSF CAREER Grant DMS-1848087 He has taught courses on Deep Learning, Machine Learning, and Signal Processing at Northeastern University since 2016, previously holding academic roles at Rice University (2016-2018) and MIT (2009-2016). He directs educational outreach initiatives and developed the educational resource Leading Lesson for multivariable calculus problem-solving.

• Decision Analysis
• Consistency
• Fuzzy sets
• +12 more

Michele Fedrizzi is a full professor of Mathematical Methods of Economics and Actuarial and Financial Sciences at the Department of Industrial Engineering, University of Trento. He holds academic affiliations across multiple institutions, including the Faculty of Economics (University of Trento), Faculty of Computer Science (University of Bolzano), Department of Economics and Management, and doctoral programs in Social Sciences and Materials, Mechatronics and Systems Engineering. His research focuses on decision analysis, fuzzy systems, and consensus modeling in group decision-making. Past research included statistical distributions, fuzzy extensions of classical models (e.g., linear regression), and risk equity evaluation. Current interests involve consensus dynamics in group decisions, preference modeling, and the Analytical Hierarchy Process (AHP). Fedrizzi serves as a referee for journals like European Journal of Operational Research, Fuzzy Sets and Systems, and IEEE Transactions on Systems, Man, and Cybernetics. He organized the XXXII AMASES Conference (2008) and the International Workshop on Preferences and Decisions (2009). He was a member of the University of Trento’s Administrative Board (2004–2008) and reviewed PhD theses at institutions like Åbo Akademi University (Finland) and the University of Padova.

Jesse RatzkinView profile

Lecturer

• Geometric Analysis
• Differential Geometry
• Partial Differential Equations
• +5 more

Jesse Ratzkin is a Lecturer at the University of Würzburg's Chair of Mathematics VI (Mathematics in the Natural Sciences). He holds a PhD from the University of Washington (2001) and a B.A. from UC Berkeley (1995). His research focuses on geometric analysis, including mean curvature, Q-curvature, eigenvalues of the Laplace-Beltrami operator, and isoperimetric inequalities. He has held academic positions globally, including a tenured role at the University of Cape Town (2010–2016). His research has been funded by grants such as the National Research Foundation of South Africa (2013–2016) and NSF fellowships. Notable publications include works on Q-curvature metrics, Sobolev inequalities, and geometric flows. He actively participates in academic service, including editorial roles and organizing international conferences. Teaching spans institutions like the University of Cape Town, where he designed courses in PDEs, linear algebra, and complex analysis. He has supervised PhD students like Murray Christian and mentored over 8 final-year projects. His outreach efforts include high school math programs in South Africa and Ireland.

• Nonlinear Differential Equations
• Mathematical Analysis
• Optimal Control
• +3 more

Francisco Javier Fernandez Fernandez is a Professor at the University of Seville's Department of Mathematical Analysis. His research focuses on nonlinear differential equations, optimal control, environmental modeling, and mathematical analysis. He teaches courses such as 'Derivation and Integration of Functions of a Real Variable' and 'Professional Software in Environmental Issues' across various mathematics and interdisciplinary programs. His research group, 'Nonlinear Differential Equations,' explores topics like Stieltjes differential equations, population dynamics, and eutrophication control. Recent work emphasizes applications in environmental systems (e.g., Vespa Velutina population modeling, urban heat islands) and digital twin technologies for real-time simulation. Publications from 2025 highlight advancements in Stieltjes derivative theory and functional spaces, while earlier works address water circulation optimization and 3D eutrophication models. His contributions span over two decades, with a strong emphasis on bridging mathematical theory and environmental engineering challenges. No scientific awards are listed, but his extensive publication record reflects sustained academic impact. Advising and grant details are not explicitly mentioned in the provided texts, though his teaching roles suggest involvement in mentoring students through coursework.

• Nonparametric function and density estimation
• Shape-restricted inference
• Constrained regression models
• +2 more

Mary C. Meyer is a Professor in the Department of Statistics at Colorado State University. Her research focuses on nonparametric function and density estimation, particularly under shape restrictions, with applications across ecological modeling, survey methodology, and statistical computing. Education: Ph.D. in Statistics from the University of Michigan (1996) Research Interests: Nonparametric function and density estimation Shape-restricted inference Constrained regression models Bayesian nonparametric methods Penalized isotonic regression Statistical software development Recent Publications show a focus on constrained regression splines, domain mean estimation, and applications in forest dynamics and survey methodology. She has developed several R packages including cgam and tools for cone projections. Grants: Funded by NSF grant DMS-0905656 for research on constrained optimization algorithms. Email Contacts: meyer@stat.colostate.edu and mmeyer@stat.uga.edu

Timothy HongView profile

Associate Professor

• Water Resources Modelling
• Water Pollution Modelling
• Hydro-informatics
• +4 more

Dr Timothy Hong is an Associate Professor in Civil and Building Services Engineering at London South Bank University (LSBU). He holds a Ph.D. in Environmental Engineering (1995-1998) from an unspecified institution, an MSc in Environmental Management (1985-1987), and a BEng in Civil/Environmental Engineering. Before academia, he worked as an environmental engineer in industry and served as Senior Research Scientist (Level 2) & Modelling Group Leader at GNS Science (New Zealand) from 1999 to 2009. He currently leads modules in Hydraulics, Environmental Engineering, and Water Engineering at LSBU. His research focuses on water resources systems, pollution modelling, hydro-informatics using AI, and socio-economic integration in environmental solutions. Key projects include AI-driven wastewater treatment systems with Chonnam National University, real-time hydrological modelling with Korea Rural Research Institute, and uncertainty analysis in groundwater systems with GNS Science. He has collaborated with institutions in South Korea and New Zealand. His recent publications emphasize Bayesian methods for wastewater process control, neural networks for performance prediction, and integrated water quality management systems. He contributes to UN Sustainable Development Goals related to clean water and responsible consumption. Teaching responsibilities include module leadership for Undergraduate and Postgraduate programs in Civil Engineering. His professional roles include Examination Coordinator for the School of BSE.

Wallied OrabiView profile

Associate Professor

• Optimization and Decision Support for Sustainable Infrastructure
• Automation in Construction
• Sustainable Building Construction
• +3 more

Wallied Orabi, Ph.D., is an Associate Professor and Undergraduate Program Director at Florida International University (FIU), specializing in Civil Engineering. His research focuses on optimizing sustainable and resilient infrastructure systems, automation in construction, and sustainable building practices. He holds a Ph.D. in Civil Engineering, contributing to advancements in infrastructure resilience and decision-support frameworks for construction projects. Dr. Orabi's work emphasizes integrating environmental, economic, and safety considerations into infrastructure development. His research interests include sustainable infrastructure design, cost estimation methodologies for bridge construction, and the application of technology (e.g., eye-tracking) to enhance construction safety. His articles highlight interdisciplinary approaches to transportation systems optimization, disaster recovery planning, and cost-benefit analyses of construction techniques like Accelerated Bridge Construction (ABC). Dr. Orabi’s publications span over two decades, demonstrating a consistent focus on infrastructure sustainability, resilience, and cost efficiency. His work addresses real-world challenges such as work zone safety, post-disaster reconstruction, and environmental impact mitigation. While no scientific awards are explicitly mentioned, his contributions to infrastructure optimization are widely recognized in academic circles. His advising and grant activities are not detailed in the provided texts. Dr. Orabi is affiliated with FIU’s Department of Civil Engineering, contributing to academic and industry partnerships through his research and teaching roles.

Don VinsonView profile

Professor

• Sport Coaching
• Performance Analysis
• Pedagogical Theory
• +7 more

Professor Don Vinson is a Course Leader for the MSc Sports Coaching and holds the academic rank of Professor of Sport Coaching at the University of Worcester's School of Sport and Exercise Science. He balances roles as a teacher, researcher, and practitioner, specializing in sport coaching pedagogy, performance analysis, and leadership. His research focuses on Coach Developer learning, Landscapes of Practice, and evaluating programs like the Invictus Games Düsseldorf 2023 (Royal British Legion-funded) and UK Coaching initiatives. Education qualifications include a PhD in Physical Activity and Health (University of Central Lancashire, 2008), a PGCert in Teaching and Learning in Higher Education (Liverpool John Moores University, 2006), and a BSc in Physical Education and Sports Science (University of Hull, 2001). He is a Senior Fellow of the Higher Education Academy and holds a University Teaching Fellowship. Research funding exceeds £160,000, including projects with UK Sport, UK Coaching, and the League Managers’ Association. He reviews for academic journals and served as Associate Editor of the Graduate Journal of Sport, Exercise, and Physical Education Research (2015–2020). Professionally, he advises National Governing Bodies like the Football Association, British Cycling, and England Hockey, where he also serves as Head Coach for the U16 women’s hockey squad and part of the Coach Developer Workforce. His awards include being shortlisted for England Hockey’s Performance Coach of the Year (2011) and multiple teaching fellowships. He leads the Coach Developer and Performance Analyst Research Group and collaborates with organizations such as the International Council for Coach Education (ICCE) and the Cluster for Research into Coaching (CRiC). His work emphasizes creating value in coach development systems and non-linear coaching approaches across grassroots and elite levels.

• Cryptography
• Distributed Computing
• Secure Multi-Party Computation (MPC)
• +7 more

Chen-Da Liu-Zhang is a Lecturer and Researcher at the Lucerne University of Applied Sciences and Arts, leading the Information Systems Lab and Blockchain Lab. He is also a Research Scientist at the Web3 Foundation. His academic journey includes a PhD from ETH Zurich (advised by Prof. Ueli Maurer), a master's degree from ETH Zurich, and dual bachelor's degrees in computer science and mathematics from Universidad Autónoma de Madrid. His research focuses on secure distributed systems, encompassing cryptography, distributed computing, multi-party computation (MPC), blockchain technology, consensus protocols, and quantum computing security. Key areas include asynchronous protocols, communication complexity, constructive cryptography, and network-agnostic security. Recent work emphasizes optimizing cryptographic broadcast protocols, achieving efficient MPC with linear communication, and advancing blockchain-related flooding protocols. He has contributed to over 40 publications in top venues like CRYPTO, EUROCRYPT, and TCC. His lab leadership positions reflect his role in bridging academic research with practical applications in distributed systems. Serving on program committees for CT-RSA 2025, S&P 2025, and Asiacrypt 2024 highlights his active role in the cryptography community. Notable collaborations include work with Prof. Vipul Goyal at Carnegie Mellon University and NTT Research.

• Energy Management Systems
• Renewable Energy Systems
• Model Predictive Control
• +3 more

Harald Kirchsteiger is a Professor at the University of Applied Sciences Wels , affiliated with the Research Center Wels and the ASiC Center of Excellence Energy . His research focuses on energy management systems, renewable energy integration, and model predictive control for energy systems. He leads and participates in multiple EU-funded projects including RESINET (resilience of energy grids), InduGrid (industrial microgrids), and HyBRID (hydrogen applications). His work addresses challenges in grid stability, battery optimization, and energy storage solutions. Recent projects involve developing predictive control models for photovoltaic systems and optimizing nonlinear energy management problems. He has authored over 40 publications with an h-index of 12, focusing on smart grid technologies and energy efficiency. Key research areas include distributed energy systems, battery inverter efficiencies, and energy resilience strategies. Collaborations span academic and industrial partners across Europe, addressing challenges in decarbonization and grid modernization.

Adam LowranceView profile

Associate Professor

• Low-dimensional Topology
• Knot Theory
• 3-Manifold Theory
• +3 more

Adam Lowrance is an Associate Professor of Mathematics and Statistics at Vassar College, where he has served since 2012. He holds a BA in Mathematics and Computer Science from Amherst College and a PhD in Mathematics from Louisiana State University. His research focuses on low-dimensional topology, particularly knot theory and 3-manifold theory. Recent work has explored properties of 2-bridge knots, Turaev genus, Khovanov homology, and geometric invariants. His publications frequently intersect algebraic and geometric approaches to topological problems. Teaching responsibilities include Linear Algebra (MATH 221) and Advanced Linear Algebra (MATH 364). He maintains an active research program with a focus on undergraduate research, as evidenced by grants such as the NSF RUI initiative. Professional activities include service on departmental committees and contributions to topological research communities. Contact details: adlowrance@vassar.edu , Rockefeller Hall Box 302.

Joseph IbrahimView profile

Professor

• Biostatistics
• Bayesian Survival Analysis
• Prior Elicitation
• +6 more

Joseph Ibrahim is an Alumni Distinguished Professor in the Department of Biostatistics at the Gillings School of Global Public Health, University of North Carolina at Chapel Hill, where he has served since 2002. He currently holds dual leadership roles as Director of Graduate Studies for the Department of Biostatistics and Director of the Biostatistics for Research in Genomics and Training Grant. His methodological innovations in Bayesian survival analysis and missing data methodologies have significantly advanced public health research, particularly in cancer genomics applications. Professor Ibrahim's research program centers on developing statistical frameworks for complex clinical and genomic data. His seminal contributions include Bayesian cure rate models, prior elicitation techniques, and diagnostic tools for high-dimensional survival analysis. Current work focuses on integrating multi-omics data with longitudinal tumor burden metrics and refining adaptive clinical trial designs for biomarker-driven populations. These methodologies directly address critical challenges in precision oncology and pharmacovigilance, enabling more robust inference from real-world evidence. His 2025 publications reveal three dominant trends: (1) Advancements in cure rate modeling for joint longitudinal-survival data with change points, (2) Computational innovations for high-dimensional penalized models using autoencoders and R packages like hdbayes, and (3) Methodological refinements for Bayesian trial design incorporating historical controls. These works consistently bridge theoretical statistics with cancer research applications, particularly in tumor phylogeny inference and signal detection for adverse events. Scientific awards include: Samuel S. Wilks Memorial Award (2024) from the American Statistical Association for distinguished contributions to biostatistics Professor Ibrahim has mentored 48 pre-doctoral students and 8 postdoctoral fellows, with exceptional thesis publication records in top statistical journals. As principal investigator of the T32 Cancer Genomics Training Grant since 2004, he has secured funding for 35 doctoral students. His curriculum leadership includes modernizing eight graduate courses and establishing new data science computing sequences since 2015. Current advising focuses on Bayesian methodology development for cancer genomics applications. He directs the department's Biostatistics for Research in Genomics initiative and leads the T32 Cancer Genomics Training Grant team, which integrates statistical methodology development with translational cancer research across UNC's Lineberger Comprehensive Cancer Center and clinical partners.