Andrew Wentzel presents his research entitled &ldquo;Digital Twins Visualization&rdquo; at the IEEE VIS2024 Conference at 3:30 (4:30 EDT) October 17, 2024. 
Abstract: 
Digital twin models are of high interest to Head and Neck Cancer (HNC) oncologists, who have to navigate a series of complex treatment decisions that weigh the efficacy of tumor control against toxicity and mortality risks. Evaluating individual risk profiles necessitates a deeper understanding of the interplay between different factors such as patient health, spatial tumor location and spread, and risk of subsequent toxicities that can not be adequately captured through simple heuristics. To support clinicians in better understanding tradeoffs when deciding on treatment courses, we developed DITTO, a digital-twin and visual computing system that allows clinicians to analyze detailed risk profiles for each patient, and decide on a treatment plan. DITTO relies on a sequential Deep Reinforcement Learning digital twin (DT) to deliver personalized risk of both long-term and short-term disease outcome and toxicity risk for HNC patients. Based on a participatory collaborative design alongside oncologists, we also implement several visual explainability methods to promote clinical trust and encourage healthy skepticism when using our system. We evaluate the efficacy of DITTO through quantitative evaluation of performance and case studies with qualitative feedback. Finally, we discuss design lessons for developing clinical visual XAI applications for clinical end users.

EVL PhD Candidate Andrew Wentzel Presents his Research at IEEE VIS2024

A team of collaborating researchers from EVL and others from the Equitable Health Data Science Institute (EHDS) members placed 2nd out of 17 teams in the EPIC COSMOS <a href="https://ehds.uic.edu/events/hackathon/">Hackaton at UIC sponsored by the EHDS</a>. Team members consisted of Ranga Chandrasekaran, Runa Bhaumik, Tommy Cheng, Andrew Wentzel, Nafiul Nipu, Hossein Fathollahian, and Sanjana Srabanti. 
The problem they tackled was: 
The mental health symptoms/diseases in cancer patients are often not recognized and managed. Compare the prevalence of mental health disorders in different cancers. 
The Institute for Equitable Health Data Science Research&rsquo;s mission is to analyze and eliminate potential biases before they are unwittingly embedded in artificial intelligence algorithms in healthcare. In particular, the institute, with its fabric of interdisciplinary collaborations, will shape solutions for biomedical and health data science and technology while prioritizing health equity for Chicago&rsquo;s diverse population and beyond. The institute is co-directed by Prof. Andrew Boyd and Prof. Elisabeta (Liz) Marai.

EVL Team Gets 2nd Place in EPIC Hackathon at UIC

Congratulations to Mike Papka, one of nine speakers at <a href="https://www.tedxchicago.com/">TEDxChicago 2024: Lighting the Way</a> to be held Friday, September 27th at Harris Theater, Millennium Park fro 3pm - 7pm. 
Mike holds a joint appointment as a UIC Computer Science faculty member and serves as the Argonne Leadership Computing Facility director at Argonne National Laboratory. As director of ALCF, Mike oversees the development and deployment of <a href="https://www.anl.gov/aurora">Aurora</a>, the <a href="https://top500.org/">world&rsquo;s second exascale supercomputer</a> and the fastest <a href="https://www.intel.com/content/www/us/en/newsroom/news/intel-powered-aurora-supercomputer-breaks-exascale-barrier.html">AI supercomputer</a>. 
Mike is one of the inaugural recipients of the William S. McCulloch Collegiate Professorship of Computer Science. Warren S. McCulloch was a UIC professor of psychiatry who with Walter Pitts co-invented <a href="https://link.springer.com/article/10.1007/BF02478259">artificial neural networks in 1943</a>. Today, neural nets form the foundation of much AI technology, including deep learning and large language models. 
Mike is a professor of Computer Science, director of EVL, and co-director of the <a href="https://crabtree.uic.edu/">George Crabtree Institute for Discovery and Sustainability</a>.

UIC CS William McCulloch Professor Mike Papka speaking at TEDxChicago 2024

Computer Science (CS) Professor and EVL faculty Micheal E. Papka is being honored among only a few of his colleagues with the Warren S. McCulloch Professorship of Computer Science. This recognition is the first-ever CS Professorship Investiture. Dr. Papka and fellow CS Professor Barbara DiEugenio are the first two faculty to receive this award. 
Among the other honorees are Professor Cornelia Caragea - first holder of the Robert V. Kenyon Professorship of Computer Science and Distinguished Professor Bing Liu - first holder of the Peter L. and Deborah K. Wexler Professorship of Computing. 
At this inaugural event, both Bob Kenyon and his wife Cynthia Vahlkamp and Peter and Deborah Wexler will be reconginized for their very generous donations of professorships. 
The investiture will be held: 
Friday, September 20, 2024 
3:00 PM Reception, 3:30 PM Ceremony 
ERF West Atrium 
842 W Taylor St, Chicago, IL 60607 
For questions, contact <a href="mailto:rszandra@uic.edu">Ms. Renata Szandra</a>

Micheal E. Papka Honored with Warren S. McCulloch Professorships of Computer Science

September 16, 2024 - The University of Illinois Chicago (UIC) is proud to become an Intel AI/oneAPI Center of Excellence, advancing computational science education for AI and next-generation heterogeneous programming. The Center will integrate the open, standards-based oneAPI programming model and the latest AI development techniques into UIC&rsquo;s courses, preparing students to meet the demands of AI, high-performance computing (HPC), and data visualization in today&rsquo;s scientific and engineering landscapes. The Center of Excellence builds on the efforts of Dr. Michael E. Papka, who has supported Chicago-area university oneAPI workshops for the past two years and has been a strong advocate for oneAPI since its inception. 
UIC&rsquo;s AI/oneAPI Center of Excellence will be a hub for developing focused modules to enhance current AI, HPC, and visualization courses. The center will initially focus on developing modules to integrate seamlessly into regular classes and outreach activities, expanding access to advanced computational education for a wider audience. The goal at UIC is to prepare students to interpret and visually represent complex data sets using cutting-edge technologies such as Intel Embree and OSPRay and to teach them how to use SYCL in HPC to meet the challenges of exascale computing. 
&ldquo;The AI/oneAPI Centers of Excellence are aiding the next generation of developers in advancing future software innovation using the power of CPUs, GPUs, and other accelerators,&rdquo; says Dr. Michael E. Papka, Professor of Computer Science at UIC and the Director of the Argonne Leadership Computing Facility, a Department of Energy Office of Science user facility at Argonne National Laboratory. &ldquo;This UIC-based collaboration with Intel offers valuable, real-world experience and opportunities for our students.&rdquo;
The UIC Center&rsquo;s AI and HPC curriculum will present essential tools and libraries, such as the oneAPI infrastructure for AI and Intel rendering tools, empowering students to optimize code for parallel architectures and high-performance multiarchitecture environments. Through hands-on labs and coding assignments, UIC students will tackle real-world optimization challenges, preparing them to leverage the immense power of exascale systems for scientific discovery. The next phase will consider adding AI curriculums addressing HPC and large-scale AI problems harnessing the power of Intel hardware. 
&ldquo;We are excited to see the impact of these educational advancements on our students and the broader scientific community,&rdquo; says Dr. Peter Nelson, Dean of Engineering and Professor of Computer Science at UIC. &ldquo;By integrating cutting-edge tools and technologies, we are fostering a versatile, technologically adept workforce capable of leveraging AI and HPC for scientific discovery.&rdquo;
Students will engage in projects such as visualizing climate change effects, showcasing energy resource distributions with interactive maps, and rendering materials science structures at the atomic level. These projects bridge the gap between theoretical knowledge and practical application, connecting students&rsquo; work with real-world scenarios and emphasizing HPC&rsquo;s role in solving global challenges. Moreover, HPC supports the rise of AI applications in scientific computing by training complex AI models, from natural language processing to autonomous systems. This interaction between HPC and AI is crucial for advancing both fields, fostering innovation, and driving technological progress. 
&ldquo;UIC&rsquo;s Intel AI/oneAPI Center of Excellence will challenge students to drive complex and important computational projects such as simulating climate change impacts, modeling energy resource distributions, and exploring new materials properties. This brings real-world applicability of AI and HPC into the classroom, enabling the next generation of scientists and engineers to push the boundaries in helping to solve global challenges,&rdquo; says Joe Curley, vice president, and general manager of Intel Software Products and Ecosystems. 
This initiative represents a strategic alignment between academic curriculum development and industry needs. By equipping students with the skills and knowledge necessary to leverage AI, HPC, and visualization technologies, UIC is contributing to cultivating a highly skilled workforce capable of advancing the frontiers of science and engineering. 
For more information, please contact: 
Professor Michael E. Papka – <a href=mailto:"papka@uic.edu">papka@uic.edu</a>

University of Illinois Chicago Establishes a Center of Excellence focused on AI

Michael E. Papka has been announced as the new Director of EVL. Mike has a long history with EVL, starting in 1994 when he graduated with his Masters degree in Computer Science - - through many long-term collaborations between Argonne National Laboratory and EVL. 
After receiving his MS at UIC, Mike completed a second MS and PhD with the University of Chicago. Mike holds a joint appointment as a full UIC CS professor and at Argonne, where he has research and senior leadership positions. 
As the Director of the Argonne Leadership Computing Facility (ACLF), Mike leads one of the U.S. Department of Energy&rsquo;s premier facilities for open science. He has spearheaded numerous efforts to build and deploy world-class computing capabilities for open science, notably advancing AI and large-scale data analysis. Under his leadership, ALCF recently joined the exascale era with the development of the Aurora supercomputer. 
We welcome Mike as EVL&rsquo;s new leader!

Michael E. Papka Named EVL Director

EVL faculty and Computer Science (CS) Assistant Professor Fabio Miranda (PI) and Civil, Materials, and Environmental Engineering (CME) Professor Sybil Derrible (co-PI) have been awarded $1.75 million NSF grant entitled: "Collaborative Research: Frameworks: Cyberinfrastructure to Catalyze and Sustain the Urban Computing Community.” Also known as <a href="https://oscur.org/">&ldquo;The Open-Source Cyberinfrastructure for Urban Computing Research&rdquo; (OSCUR)</a>, the grant is part of an overall $5 million project that is collaborative with the University of Washington and NYU. Here at UIC, the overall effort includes the departments of CS, CME, and the College of Urban Planning and Public Affairs (CUPPA). The grant will run from September 2024 to August 2029. 
Project Overview: 
Cities are the loci of resource consumption, economic activity, and innovation; they are where our looming sustainability problems were born and where those problems must be solved. Given our increasing ability to collect, transmit, store, and analyze data, we have the opportunity to go beyond today&rsquo;s imperfect and often anecdotal understanding of cities to enable better operations, better planning, and better policy. To understand cities, we must analyze the data exhaust from their components - infrastructure, environment, and people - and how they interact over space and time. While there are already troves of open data about cities, their potential remains largely untapped due to unique challenges related to diversity, scale, and complexity of both urban data and computations required to obtain insights from these data. In this project, we aim to democratize data-driven and data-intensive approaches in urban computing to empower a broad range of stakeholders to analyze urban data at scale and tackle problems from different domains, including transportation, accessibility, and disaster management. We will address two critical obstacles to greater progress in urban computing: the lack of documented, robust, well-engineered tools and open computing platforms, and a dispersed community of researchers and developers. At the core of our proposal is the development of a cyberinfrastructure that integrates methods and tools for the exploration of urban data that are scalable, reusable, interoperable, and offer solutions to common challenges, including data cleaning, management, and visualization. We will deploy an integrated suite of tools in a collaborative cloud environment, enabling users from different domains to easily reuse existing methods across domains to ensure sustainability, facilitate collaboration between researchers and developers, and develop a cohesive community. 
Keywords: urban data, urban science, big data

UIC Researchers Join National Project to Turn Urban Data into Healthier Cities

The Open-Source Cyberinfrastructure for Urban Computing Research (OSCUR) will create a cohesive ecosystem of tools and resources designed to transform city data into actionable knowledge. This multi-institutional collaboration is supported by a $5 million grant from the National Science Foundation, with $1.75 million allocated to UIC. 
The project includes researchers from UIC's College of Engineering and College of Urban Planning and Public Affairs who will collaborate with investigators from New York University and the University of Washington. UIC will leverage its expertise in visual data analysis, civil engineering, and government and community partnerships to design accessible computational tools focused on environmental justice, transportation, and other public priorities.

OSCUR

The &ldquo;Curio: A Dataflow-Based Framework for Collaborative Urban Visual Analytics&rdquo; paper was accepted to IEEE VIS 2024. Curio is a framework for collaborative urban visual analytics that uses a dataflow model with multiple abstraction levels (code, grammar, GUI elements) to facilitate collaboration across the design and implementation of visual analytics components. Curio allows users to build and iterate on dataflows with reusable modules, supporting collaborative design and tracking changes. We evaluated Curio with domain experts on urban accessibility, climate, and sunlight access. 
Video overview, source code, examples, and tutorials are available here: <a=href"https://urbantk.org/curio/">https://urbantk.org/curio/</a> 
The paper was led by PhD student Gustavo Moreira under EVL faculty and Computer Science assistant professor Fabio Miranda.

&ldquo;Curio&rdquo; Paper Accepted to IEEE VIS 2024

&ldquo;Assessing the Landscape of Toolkits, Frameworks, and Authoring Tools for Urban Visual Analytics Systems&rdquo; has been accepted for publication by Science Direct (Elsevier) in the Computer Graphics 2024 Journal. In this paper, researchers reviewed 135 works to assess the extent to which current open-source toolkits, frameworks, and authoring tools can effectively support the development of components tailored to urban visual analytics, identifying strengths and limitations in addressing the unique challenges posed by urban data. 
Project Overview 
The creation of visual analytics systems focused on urban issues has seen a notable surge. These systems simplify intricate urban analysis workflows into intuitive, interactive visual representations, enabling users to explore, understand, and derive insights from large, complex data. Examples of these datasets include street-level imagery, street networks, and building geometries. Developing urban visual analytics systems, however, is a challenging task that necessitates
significant programming expertise to handle several critical aspects, such as: (1) visualization to allow for data exploration in urban environments, (2) data management to integrate diverse urban data types and sources, (3) data analytics to highlight patterns and trends, and (4) system performance to ensure interactive response times. Furthermore, such development requires collaboration between stakeholders from different disciplines, including urban planning, public policy, public health, and climate sciences. The complexity involved and the tendency for these efforts to occur within the framework of one-off collaborations often lead to the creation of monolithic and isolated prototypes that are rarely made publicly available. Such a situation, with a notable lack of emphasis on interoperability as a design requirement, makes it difficult to extend existing systems and integrate discrete components into other tools.
The paper was led by PhD student Leonardo Ferreira under the advisement of EVL faculty and Computer Science assistant professor Fabio Miranda.

Contact