Renny Edwin Fernandez is an Associate Professor in the Department of Engineering at Norfolk State University's College of Science, Engineering and Technology. His multidisciplinary research focuses on microsensing platforms for healthcare, pollution control, and agriculture applications. Education: PhD in Electrical Engineering (2010) from Indian Institute of Technology Madras His research integrates microfabrication, microfluidics, and machine learning to develop wearable biosensors, disposable electrodes, and IoT-enabled soil monitoring systems. Key trends in his recent publications include: Real-time health monitoring via flexible nanosensors Machine learning integration in agricultural IoT Plasma-aided printing of conductive nanomaterials Smart PPE systems with NFC technology Scientific Awards: Research Initiation Award (2020) for cognitive monitoring systems in extreme environments Dr. Fernandez mentors graduate and undergraduate researchers at NSU, with prior teaching experience at University of Indianapolis and Florida International University. He holds a patent for biosensor technology and has developed innovative solutions for: Salivary cortisol detection Soil nutrient analysis Cell viability assessment Smart irrigation systems
Giovanni De Micheli is a Professor of Electrical Engineering and Computer Science at EPF Lausanne, Switzerland. He also serves as Director of the Integrated Systems Centre and the Institute of Electrical Engineering at EPFL, and chairs the Scientific Committee of CSEM in Neuchatel. Previously, he held academic roles at Stanford University for 18 years, including Full Professor, Associate Professor, and Assistant Professor in the Department of Electrical Engineering. His research spans synthesis of digital circuits, hardware/software co-design, low-power design, and Networks on Chip (NoC) technology. 2003: IEEE Emanuel Piore Award 2000: Golden Jubilee Medal of the IEEE CAS Society 2000: ACM Fellow 1994: IEEE Fellow 1990: IEEE/CS Distinguished Service Award 1988: NSF Presidential Young Investigator Award His seminal contributions include pioneering C-based synthesis and Boolean matching algorithms for digital circuits, foundational work in dynamic power management using stochastic control, and the development of Network-on-Chip (NoC) technology. His publications, such as "Networks on Chips: A New SoC Paradigm" and "Dynamic Power Management for Portable Systems" , have shaped modern SoC design practices. With over 400 technical articles, 9 books, and an H-index of 56, his work remains highly influential.
Prof. Pia Fricker is an Associate Professor and Vice Head of the Department of Architecture at Aalto University's School of Arts, Design and Architecture in Finland. She holds the Professorship of Computational Methodologies in Landscape Architecture and Urbanism, directing the Urban Studies and Planning Programme. Her research integrates urban design, landscape architecture, and digital design culture, focusing on data-driven methods, immersive environments, and adaptive urban development. Collaborations include ETH Zurich, Singapore University of Technology and Design, and Hafencity University Hamburg. Key projects include the Metaversity and Future Smart Cities initiatives. Fricker has led over 80 publications and exhibitions globally, including at the Venice Biennale and National Design Centre Singapore. She is an editorial board member for the Journal of Digital Landscape Architecture and peer reviewer for multiple journals. Awards include the Digital Landscape Architecture Award (2018) and DLA Scientific Merit Award (2021). Her teaching emphasizes computational pedagogy and digital innovation in design education. Education: PhD in Architecture (ETH Zurich, 2021) Postgraduate in Didactics (ETH Zurich, 2011) MAS in Computer Aided Architectural Design (ETH Zurich, 2003) MSc Arch in Urban Design & Landscape Architecture (Technical University of Karlsruhe, 2001) Research Interests: Computational design, parametric modeling, mixed reality, climate-adaptive ecosystems, generative AI, and sustainable urban development. Her work bridges emerging technologies with ecological and urban challenges, emphasizing interdisciplinary collaboration. Grants & Projects: Metaversity (2023–2025, Principal Investigator) Future Smart Cities Sasakawa (2023–2024, Principal Investigator) ABRA (2020–2023, Project Member) Awards: DLA Awards (2018, 2021) DLA Review Committee Awards (2020–2022) Exhibition Recognitions (Venice Biennale, National Design Centre Singapore) Labs/Teams: Leads the Urban Studies and Planning Programme and collaborates with interdisciplinary teams on projects like the RAILCORRIDOR Singapore initiative. Active in digital twin development and AI-driven design tools.
Dirk Koch is an Associate Professor in the Department of Computer Science at the University of Manchester. He specializes in reconfigurable computing, FPGA architecture, and hardware acceleration. His research addresses challenges in field-programmable gate arrays (FPGAs), high-level synthesis, and stream processing. He leads the Advanced Processor Technology group and contributes to the Digital Futures Institute for Data Science and AI. Education: Doctorate in Computer Engineering Affiliations: Centre for Digital Trust and Society, EPSRC Functional Oxide Reconfigurable Technologies Programme His work focuses on optimizing FPGA performance, reducing power consumption, and advancing reconfigurable hardware systems. Recent projects include bitstream manipulation frameworks, runtime stream processing pipelines, and FPGA fabric optimization techniques. He has collaborated extensively with industry partners like AMD-Xilinx. Dirk Koch has supervised 11 research projects, including work on clock region process variation analysis and FPGA virus scanning. He holds grants from EPSRC and has published 62 peer-reviewed works.
Robert Xiao is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Designing for People research cluster. He holds a Ph.D. from Carnegie Mellon University and a BMath from the University of Waterloo. His research focuses on interactive technologies, including VR/AR interfaces, sensing systems, and cybersecurity. Notable contributions include Lumitrack (tracking system), TouchTools (touch interaction), and CVE-2023-37271 (Python sandbox exploit). Education: Ph.D., Human-Computer Interaction Institute, Carnegie Mellon University; BMath, Computer Science & Combinatorics, University of Waterloo Affiliations: Core member of UBC's Designing for People cluster Research interests span novel input modalities, mixed-reality systems, and security challenges. He actively competes in DEF CON CTF (multiple 1st places) and publishes in top venues like CHI, UIST, and ISMAR. Recent work explores VR decision-making, low-latency tracking, and collaborative AR/VR environments. Awards: SIGCHI Outstanding Dissertation Award, CHI Honorable Mention, DIS Honourable Mention Teaching includes courses on computer systems (CPSC 213), human-computer interaction (CPSC 554X), and cybersecurity (CPSC 436S). His lab develops tools like SurfShare (surface sharing) and VirtualNexus (collaborative AR).
Daniel Cardoso Llach is an Associate Professor at Carnegie Mellon University's School of Architecture , where he chairs the Master of Science in Computational Design program and co-directs the CoDe Lab . His scholarship merges history, science and technology studies (STS), and computational design , focusing on the cultural and socio-technical dimensions of design automation. Education: PhD and MS in Architecture: Design and Computation from MIT , BArch from Universidad de los Andes Research Grants: Supported by the Graham Foundation for historical CAD exhibitions and by the Alexander Von Humboldt Foundation for postwar computational design research in Germany His work interrogates the politics of software, the materiality of computational systems , and the ethical implications of AI/robotics in architectural practice. Recent projects include reconstructing early CAD systems and analyzing data-driven urban technologies. Scientific awards include: Alexander Von Humboldt Fellowship (2024–2025) ACM CSCW Methods Mention for emulation-based software research (2021)
Sylvain Lefebvre is a permanent researcher at INRIA (Institut National de Recherche en Informatique et en Automatique) in France, where he leads the MFX research team since 2018. Previously, he was part of the ALICE group at INRIA Nancy (2009-2018) and the REVES team in Sophia Antipolis (2006-2009). His career includes a postdoctoral position at Microsoft Research Seattle (2005) following his PhD at INRIA Rhones-Alpes under Fabrice Neyret. His educational background includes a PhD in Computer Graphics from Université Joseph Fourier (Grenoble) in 2005, preceded by a Master in Computer Graphics from INP Grenoble in 2001. His habilitation thesis focused on Runtime Texture Synthesis. Lefebvre's research centers on simplifying content creation for highly detailed patterns, structures, and shapes with applications spanning Computer Graphics to additive manufacturing. He develops fast, controllable by-example synthesis approaches that generate content while enforcing user-specified constraints. His work addresses computational challenges through novel data structures and algorithms optimized for GPUs and FPGAs, including his Silice programming language. The ERC-funded ShapeForge project (2012-2017) advanced shape generation for 3D printing, leading to the IceSL software for digital modeling and fabrication. Analysis of his 15 most recent publications reveals a strong focus on additive manufacturing optimization, with recurring themes in structural integrity, material efficiency, and geometric algorithms. His work bridges computer graphics theory with practical fabrication constraints, particularly in microstructure design, slicing techniques, and mechanical metamaterials. The interdisciplinary nature spans computer science, materials engineering, and robotics. EUROGRAPHICS Young Researcher Award (2010) ERC Starting Grant for ShapeForge project (2012) Lefebvre has advised over 25 PhD students and interns including Marco Freire, Thibault Tricard, and Jimmy Etienne. His ShapeForge project received significant ERC funding, supporting research in computational fabrication. He serves on numerous program committees including SIGGRAPH, Eurographics, and SIGGRAPH Asia, reflecting his leadership in the computer graphics community. As leader of the MFX team since 2018, Lefebvre directs research in computational fabrication, focusing on IceSL software development for 3D printing workflows. The team integrates computer graphics techniques with manufacturing constraints, developing tools that simplify complex object design and fabrication while addressing real-world challenges in material usage and structural integrity.
Dr. Yali Ling serves as an Assistant Professor in the Fashion Merchandising and Design program within the Department of Family and Consumer Sciences at California State University, Long Beach's College of Health and Human Services. Her research bridges traditional textile engineering with cutting-edge sustainable material innovation. Education: Ph.D. in Textile Technology Management, North Carolina State University (2021-2024) M.S. in Fashion Design and Engineering, Wuhan Textile University (2018-2021) B.S. in Fashion Design, Wuhan Textile University (2014-2018) Research Focus: Dr. Ling's work pioneers sustainable textile production through hemp/cotton blends and recycled materials, while advancing digital fashion technologies via 3D body scanning applications. Her expertise spans yarn engineering for performance textiles and functional apparel design addressing ergonomic challenges in diverse populations. This dual focus creates synergies between eco-conscious manufacturing and precision garment engineering. Publication Trends: Her 15 most recent publications (2019-2025) reveal three converging trajectories: (1) Sustainable material innovation (hemp textiles, eco-spinning), (2) Triboelectric wearable technology development, and (3) Anthropometric-driven apparel design. These strands collectively address industry demands for environmentally responsible production while enhancing human-technology interfaces in textile applications. Scientific Recognition: 2024 Best Poster Presentation at Textile Research Open House (NCSU) 2022 VF Graduate Student Impact Award ($5,000) 2021 Wuhan Textile University Special Graduate Scholarship ($1,500) 2020 Chinese Ministry of Education National Scholarship ($3,000) 2020 CNTAC "Maker China" Innovation Excellence Award 2019 China Natural Dialectics Research Association Symposium Prize Professional Engagement: Dr. Ling maintains active industry partnerships through her sustainable textile research while mentoring undergraduate students in the Fashion Merchandising and Design program. Her current work focuses on scaling hemp-based textile production and developing AI-integrated pattern generation systems. Research Infrastructure: While specific laboratory facilities aren't detailed in available materials, her publications indicate collaborations with Wilson College of Textiles' advanced manufacturing facilities and access to 3D body scanning technologies for anthropometric research.
Zachary Tatlock is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he leads the Programming Languages & Software Engineering Group (PLSE) and the SAMPL Group. His research spans programming languages, formal verification, compilers, and computational fabrication. He is also an Amazon Scholar with AWS's Automated Reasoning Group and previously advised OctoML. Tatlock's work bridges theoretical foundations with practical systems, focusing on making it easier to write tricky code while ensuring correctness through rigorous proofs and measurements. PhD in Computer Science & Engineering, University of California, San Diego (2014) Thesis: Reducing the Costs of Proof Assistant Based Formal Verification Advisor: Sorin Lerner BS in Computer Science (Honors) and Mathematics, Purdue University (2007) Professor Tatlock's research focuses on the intersection of programming languages, formal methods, and systems. His work in compilers and formal verification aims to make it easier to write tricky code while ensuring correctness through rigorous proofs. He explores computational fabrication techniques that bridge digital design with physical manufacturing. His recent work on equality saturation (via the egg framework) has transformed program optimization and synthesis. Tatlock also investigates floating-point numerics, distributed systems verification, and hardware/software co-design, always seeking to balance theoretical rigor with practical implementation. Tatlock's recent publications demonstrate a strong focus on equality saturation techniques (egg framework), computational fabrication, and verified systems. His work increasingly integrates machine learning with program analysis and synthesis. There's a clear trajectory toward more practical applications of formal methods in real-world systems, particularly in numerical computing and fabrication. His research group has made significant contributions to e-graph technology, floating-point accuracy, and the verification of distributed systems. Distinguished Paper Award for Rewrite Rule Inference Using Equality Saturation (OOPSLA 2021) Spotlight Paper Award for Dynamic Tensor Rematerialization (ICLR 2021) Distinguished Paper Award for egg: Fast and Extensible Equality Saturation (POPL 2021) Faculty Appreciation for Career Education & Training (FACET) Award (2020) NSF CAREER Award: Verifying Distributed System Implementations (2017) Distinguished Paper Award for Automatically Improving Accuracy for Floating Point Expressions (PLDI 2015) Distinguished Teaching Award Nomination (2015) Professor Tatlock has advised numerous doctoral, master's, and undergraduate students who have gone on to prominent positions in academia and industry, including faculty positions at the University of Utah and Brown University, and leadership roles at companies like OctoML and Certora. His research is supported by significant funding from NSF, DARPA, DOE, and industry partners, totaling millions of dollars. Current grants include projects on computer-aided reasoning, formal verification, computational fabrication, and machine learning systems. He has served on numerous program committees and organized workshops including FPTalks, EGRAPHS, and PNW PLSE. As co-leader of the Programming Languages & Software Engineering (PLSE) research group and affiliate of the SAMPL Group at the University of Washington, Tatlock has developed influential tools including egg (an equality saturation toolkit), Carpentry Compiler, and Odyssey. His group actively collaborates with industry partners including Amazon Web Services, where he serves as an Amazon Scholar. The group has made significant contributions to equality saturation, floating-point accuracy, program synthesis, and computational fabrication, with applications ranging from compiler optimization to 3D printing.
Bedrich Benes is a Professor and Associate Department Head in the Department of Computer Science at Purdue University. He holds a Ph.D. and M.S. in Computer Science from Czech Technical University in Prague (1998 and 1991, respectively). His research focuses on generative methods for geometry synthesis, procedural modeling, simulation of natural phenomena, and additive manufacturing. He has published over 200 research papers and secured grants from organizations like the NSF, NASA, and DOE. Editor-in-Chief of Elsevier's Graphical Models Senior Member of ACM and IEEE Fellow of Eurographics Association Research interests include graphics, visualization, geometric modeling, and computational biology. He leads projects on tree digital twins, urban forestry modeling, and immersive VR/XR education. Advised students include Bosheng Li and Xiaochen Zhou, who recently defended their Ph.D. theses. Notable contributions include neural ranking algorithms for forest reconstruction and tools like Tree-D Fusion for tree dataset generation. His work bridges computer graphics with environmental science and agriculture.
Prof. Dr. Franziska Mathis-Ullrich is a Professor at Friedrich-Alexander-University Erlangen-Nuremberg (FAU) leading the Surgical Planning and Robotic Cognition Lab (SPARC) in the Department of Artificial Intelligence in Biomedical Engineering. Previously, she was an Assistant Professor at Karlsruhe Institute of Technology (KIT) from 2019 to 2023. Her research focuses on minimally invasive robotic systems, soft robotics, and embedded machine learning for surgical applications. She holds a PhD in Microrobotics from ETH Zurich (2017), with earlier degrees from the same institution. Education: B.Sc. and M.Sc. in Mechanical Engineering and Robotics (ETH Zurich, 2009–2012) Ph.D. in Microrobotics (ETH Zurich, 2017) Research Interests: Minimally invasive medical robotics, soft robotic systems, AI-driven surgical assistance, microrobotics, and robot-assisted surgery. Her work emphasizes translating robotics innovations into clinical applications through interdisciplinary collaboration. Key Awards: IEEE ICRA Best Paper Award in Medical Robotics (2014) IEEE BioRob Best Student Paper Award (2016) ICRA Microassembly Challenge First Prize (2014 & 2015) Forbes 30 under 30 (2017) Grants & Projects: Leading a Bavarian State Ministry-funded project on endometriosis diagnostics (€3M). Active in multidisciplinary collaborations with Erlangen University Hospital. Serves as Vice-President of the German Society for Computer- and Robot-assisted Surgery (CURAC). Labs & Teams: Directs the SPARC Lab, which develops cognitive robotic systems for surgical planning and execution. Collaborates with institutions like Max Planck, Fraunhofer, and Helmholtz.
Emily Whiting is an Associate Professor of Computer Science at Boston University and Director of the Shape Design & Computation Lab. She also serves as Director of PhD Admissions and Co-Director of the BU Computer Graphics Lab. Her research focuses on computational fabrication, architectural geometry, and computer-aided design, bridging digital geometry processing, engineering mechanics, and rapid prototyping. She holds a PhD from MIT (2012), an SM in Design & Computation from MIT (2006), and a BASc in Engineering Science from the University of Toronto (2004). Previously, she was faculty at Dartmouth and a Marie Curie Postdoctoral Fellow at ETH Zurich. Her research interests include 3D printing optimization, structural design for fabrication, and tools for functionally-valid object creation. Notable projects include work on elastic garments, climbing experience replication, and print-wind instrument design. Her work has been featured on TEDx and PBS NOVA, and she has received awards such as the NSF CAREER Award and Sloan Research Fellowship. Education: PhD (MIT), SM (MIT), BASc (University of Toronto) Labs: Shape Design & Computation Lab, BU Computer Graphics Lab Key Projects: Knitting 4D garments, Environment-Scale Fabrication, Thermal-comfort casts Recent professional activities include program committee roles at SIGGRAPH 2025 and UIST 2024, and serving as Program Co-Chair for Pacific Graphics 2024. She advises a team of PhD and MS students, with alumni now in academia and tech industries.
David E. Breen is a Professor in the Department of Computer Science within the College of Computing & Informatics (CCI) at Drexel University. He leads the Geometric Biomedical Computing Group and is affiliated with the Metadata Research Center and the Center for Biological Discovery from Big Data. His research spans interdisciplinary domains including biomedical image informatics, geometric modeling, textile modeling, and bio-inspired self-organization algorithms. Education: PhD, Computer and Systems Engineering, Rensselaer Polytechnic Institute MS, Computer and Systems Engineering, Rensselaer Polytechnic Institute BA, Physics, Colgate University His research interests focus on computational methods for biomedical applications, including shape and image analysis for cancer diagnosis, 3D reconstruction of biological tissues, and video analysis of animal behavior. He also investigates geometric modeling techniques for textiles and self-organizing systems. His work integrates computer science with biology, medicine, and engineering to solve complex problems in biomedical computing. The recent publications highlight a strong trend in computational modeling of textiles, biomedical image informatics, and AI-driven data analysis. Key themes include geometric modeling of knitted fabrics, deep learning for medical image classification, agent-based modeling of cancer metastasis, and metadata generation for biological image collections. His work bridges fundamental geometric algorithms with practical applications in healthcare and digital archives. Scientific Awards: No specific awards mentioned in the provided text. Breen has advised numerous students and collaborators across multiple domains, particularly in biomedical computing and textile modeling. His research has been supported through affiliations with major centers and collaborations with institutions such as Johns Hopkins University and the Max Planck Institute. He has been involved in projects related to NSF Center for Visual & Decision Informatics and has contributed to over 100 technical publications. He leads the Geometric Biomedical Computing Group , which conducts research at the intersection of biology, medicine, engineering, and computer science. The group develops algorithms and software for geometry-related computing problems in biomedical applications. Collaborations include the Drexel Integrated Laboratory for Cellular Tissue Engineering, Dr. Dan Marenda's Lab, and Dr. Aleister Saunder's Lab in Drexel's Biology Department.
Bettina Nissen is a Lecturer in Interaction Design and Programme Director for Design Informatics at the University of Edinburgh's School of Design within Edinburgh College of Art. Her position bridges academic teaching and research with practical applications in data-driven design. She directs the Design Informatics MA program while maintaining an active research profile through the Institute for Design Informatics. Dr. Nissen's research interests focus on making complex technological concepts accessible through tangible means. Her expertise spans Research through Design , Data Physicalisation , Digital Fabrication , and Designing with Data . She explores how physical representations of data can enhance understanding and engagement with complex systems, particularly in contexts of trust, consent, and economic value. Her recent publications reveal a strong trajectory toward community-centered approaches to data governance and indigenous knowledge systems. The work shows increasing engagement with decolonial design methodologies, more-than-human interactions, and feminist economic perspectives on technology. A notable pattern emerges in her focus on tangible interfaces for abstract concepts like blockchain, trust, and value systems. Best paper award at CHI 2024 for "Cosmovision of data: An indigenous approach to technologies for self-determination" Dr. Nissen currently supervises three PhD students (Yifei Li, Carlos Guerrero Millan, and Yixun Li) and has secured funding from multiple prestigious sources including AHRC, EPSRC, ESRC, and EU programs. Her research projects include PACTMAN (EPSRC-funded work on trust in pervasive environments), After Money (ESRC-funded collaboration with Royal Bank of Scotland), Crypto-Knitting with People's Bank of Govanhill, DCODE (EU-funded network), REPHRAIN research center, and the VisHub visualization laboratory. She actively participates in interdisciplinary research communities through the Visual+Interactive Data group and the Regulation and Design (RAD) Lab, fostering collaborations between design, technology, and policy domains.
Bernhard Thomaszewski is a Lecturer at the Department of Computer Science at ETH Zürich. His research focuses on computational mechanics, robotics, and computer graphics, with an emphasis on simulation-based design and material modeling. He explores topics such as deformable contact, flexible materials, and robotic mechanisms. His work bridges theoretical foundations and practical applications, including medical imaging, garment simulation, and biomechanical systems. Notable research interests include the development of novel algorithms for real-time simulation, optimization-driven design of mechanical systems, and integration of machine learning with physical models. He has contributed to advancements in finite element modeling, differentiable simulation, and topology optimization for robotic and biomedical applications. His recent projects highlight interdisciplinary collaboration, addressing challenges in areas like orthodontic treatment prediction, automated pipeline design, and neural network-driven material characterization. While no specific grants or awards are explicitly listed, his prolific publication record underscores his impactful contributions to computational engineering and computer science.
