Dr. Teseo Schneider
ECR Graphics, 2025
Bio: Teseo Schneider is an Assistant Professor in Computer Science at the University of Victoria, Canada. Teseo earned his Ph.D. in Computer Science from the Universita della Svizzera italiana (2017) with the thesis entitled “Theory and Applications of Bijective Barycentric Mappings.” He earned a PostdocMobility fellowship from the Swiss National Science Foundation (SNSF) to pursue his research at the Courant Institute of Mathematical Science at the New York University, aiming to bridge physical simulations and geometry. His research interests are finite element simulations, mathemUniversityatics, discrete differential geometry, and geometry processing. Teseo is the leading developer of Polyfem (https://polyfem.github.io/), a flexible and easy-to-use Finite Element Library. He is one of the maintainers of libigl (https://github.com/libigl/libigl) and a contributor to wild meshing (https://github.com/wildmeshing), a 2D and 3D robust meshing library.
Title: Robust Geometry Processing for Physical Simulation
Abstract: Numerical solutions of partial differential equations (PDEs) are widely used in engineering, especially for modelling phenomena like elastic deformations or fluid simulations. The finite element method (FEM) is the most commonly used technique for discretizing PDEs because of its versatility and range of available (commercial) implementations. Typically, the PDE solver treats meshing and basis construction as separate problems. However, the basis construction may make assumptions that lead to challenging requirements for meshing software. This can be a significant issue for applications that require fully automatic, robust processing of large collections of meshes or when the PDE solver needs to change the mesh. We present recent advancements that have led to a unified pipeline that considers meshing and element design as a single challenge. This approach enables a PDE solver that can handle simulations on thousands of domains without requiring parameter tuning.
Dr. Fateme Rajabiyazdi
ECR HCI, 2025
Bio: Dr. Fateme Rajabiyazdi is currently an Assistant Professor at the Department of Systems and Computer Engineering at Carleton University and an Affiliate Investigator at the Bruyère Research Institute. From July 2025, she will start her new position as an Assistant Professor at the Department of Computer Science at the University of Calgary. In 2023, she was awarded the Canadian Medical and Biological Engineering Society Early Career Researcher Award. Before joining Carleton, she was a postdoctoral researcher at McGill University, where she received the Quebec Postdoctoral Scholarship in Health Award (FRQS). She received her Ph.D. in Computer Science from the University of Calgary in 2018. Her research is at the intersection of information visualization, health and human-computer interaction. In particular, her research aims to develop innovative data visualization to empower patients to self-manage their care, establish data-driven communication with their caregivers and healthcare providers, and integrate these visualizations into the healthcare system.
Title: Data Visualization as a Catalyst for Fostering Healthy Communities
Abstract: Fostering healthy communities is a multifaceted endeavour that enhances people’s physical, mental, and social well-being. A promising way to achieve this goal is to leverage technological advancements and data visualizations to address complex societal health issues. In this talk, I will discuss my visions and goals for conducting transdisciplinary research to address complex health societal issues by developing innovative interactive technologies and data visualization systems. I will explore three key areas: (1) designing personalizable visualizations that empower patients to communicate their health data with clinicians; (2) developing and integrating data visualizations to support patients in the communities in self-managing their care; and (3) identifying health inequalities via reliable, people-centred visualization systems.
Dr. Leon Lu
Bill Buxton Award (Outstanding Doctoral Dissertation in HCI)
Bio: Leon is a designer, researcher, and educator dedicated to advancing design, technology, and creative practices for social impact. His work focuses on creating inclusive technologies that bridge the gap between accessibility and artistic expression. Collaborating with marginalized communities—most notably blind and low-vision musicians—Leon explores novel interactions through wearable haptics, reimagining how music can be learned and experienced. His research has been featured at top-tier HCI conferences, including TACCESS, ASSETS, and CHI.
Leon earned his PhD from Carleton University in 2024, under the guidance of Dr. Audrey Girouard and currently serves as an Assistant Professor at the University of Toronto Mississauga, where he continues to champion inclusive design and transformative learning experiences.
Title: Designing Assistive Technologies for Blind or Low Vision Music Learners
Abstract: Learning to play music is transformative—it shapes identity, fosters creativity, and builds community. But for blind and low-vision (BLV) learners, traditional music education often falls short, making access and engagement challenging. My doctoral research explores how wearable haptics can bridge this gap, enabling real-time musical communication and enhancing learning experiences for BLV musicians. Through interviews, co-design workshops, and real-world trials, I investigated how technology can make music more accessible, intuitive, and inclusive. In this talk, I will share how these insights are reshaping the way we think about accessible music learning.
Dr. Silvia Sellán
Alain Fournier Award (Outstanding Doctoral Dissertation in Computer Graphics)
Bio: Silvia is an incoming Assistant Professor at Columbia University, where she will be starting the “Geometry and the City” research group on geometry processing and computer graphics. She received her PhD from the University of Toronto in 2024, advised by Professor Alec Jacobson. Since then, she has worked as a Postdoctoral Associate at MIT, under the supervision of Professor Justin Solomon. Her doctoral work has received the 2025 Eurographics PhD Thesis Award and an Honorable Mention for the 2025 SIGGRAPH Thesis Award.
Title: Task-Aware 3D Geometric Synthesis
Abstract: My doctoral work is about the different ways in which three-dimensional shapes come into digital existence inside a computer. Specifically, it argues that this geometric synthesis process should be tuned to the specific end for which an object is modeled or captured, and proposes building algorithms specific to said end. The majority of my thesis work is dedicated to how 3D shapes are designed, and introduces changes to this modeling process to incorporate manufacturing constraints (e.g., that an object can physically be built out of a specific material or with a specific machine), precomputed simulation data (e.g., an object’s response to an impact) or specific user inputs (e.g., 3D drawing in Virtual or Augmented Reality). Importantly, these changes include rethinking the ways in which geometry is commonly represented, instead introducing formats that benefit specific applications, as well as efficient algorithms for converting between them. By contrast, my most recent work concerns itself with the task of capturing real-world 3D surfaces, a process that necessarily involves reconstructing continuous mathematical objects from imperfect, noisy and occluded discrete information. We introduce a novel, stochastic lens from which to study this fundamentally underdetermined process, allowing for the introduction of task-specific priors as well as quantifying the uncertainty of common algorithmic predictions. This perspective is shown to provide critical insights in common 3D scanning paradigms. While geometric capture is the natural first step in which to introduce this statistical perspective, the thesis ends by enumerating other tasks further along the geometric processing pipeline that could benefit from it.