The National Science Foundation has awarded EVL a Major Research Instrumentation (MRI) grant to build the Data Observation and Computation Collaboratory (DOCC) in the new Computer Design Research and Learning Center (CDRBC) building. The Data Observation and Computation Collaboratory (DOCC, &rsquo;the dock&rsquo;) is a much-needed visual data science instrument for UIC science and engineering research and research training. DOCC provides high-performance computing, advanced networking, high-speed data storage, interactive high-resolution displays and software and services for Artificial Intelligence / Machine Learning (AI/ML), data analytics, data simulations, visualization, and virtual-reality requirements. Given how varied modern data-science application requirements can be, DOCC is designed as a configurable, heterogeneous computing environment that prioritizes real-time, interactive, collaborative applications and remote data streaming, but can be scheduled off-hours for large, batch-mode processing. 
DOCC will empower users to work with their data and their colleagues in real-time, test codes, view a &rsquo;window in the oven&rsquo;to watch large simulations run, and simultaneously view results along with related data and ensemble runs on large display walls. DOCC has a visual front end that enables users to easily access familiar collaboration tools, scientific notebooks, AI/ML workflows, and popular visualization software. 
Alternatively, users can add new AI/ML models or create them from scratch. And because DOCC will be connected to the campus research network, data and/or computer codes can be ported to remote computer and cloud resources located on campus, regionally, nationally, or internationally. 
A room-sized instrument, DOCC will be located in the high-trafficked atrium of the new CDRLC, home to the UIC Computer Science Department, part of the College of Engineering, situated across from an auditorium and multi-purpose event space. This location will promote UIC data-science research initiatives and the instrument&rsquo;s collaboration potential. DOCC will also be used to conduct campus research meetings, programs and training initiatives. 
Award Number (FAIN): 2320261 
Period of Performance: 10/01/2023 - 09/30/2026 
Project Title: Research Infrastructure: MRI: Track 2 Acquisition of Data Observation and Computation Collaboratory (DOCC)

EVL Awarded NSF MRI Support to Build the Data Observation and Computation Collaboratory (DOCC)

EVL assistant professor Fabio Miranda&rsquo;s IEEE VIS2023 paper entitled <a href="https://www.evl.uic.edu/pubs/2744">&ldquo;ProWis: A visual approach for building, managing, and analyzing weather simulation ensembles in runtime&rdquo;</a> is recognized among the Best Papers Honorable Mention. A dedicated committee of experienced community members selects <a href="https://ieeevis.org/year/2023/info/awards/best-paper-awards">best paper and honorable mention awards</a> as outstanding work from the pool of accepted papers. 
ProWis is an interactive and provenance-oriented system to help weather experts build, manage, and analyze simulation ensembles at runtime. The system follows a human-in-the-loop approach to enable the exploration of multiple atmospheric variables and weather scenarios.

&ldquo;ProWis&rdquo; Awarded IEEE VIS2023 Best Paper Honorable Mention

Candidate: Juan Trelles Trabucco 
Committee members: 
- Dr. Liz Marai 
- Dr. Andy Johnson 
- Dr. Wei Tang 
- Dr. Cecilia Arighi (University of Delaware) 
- Dr. Steven Drucker (Microsoft Research) 
Date/time: Aug 24th, 11 am CT 
Location: ERF 3036 and Zoom 
https://uic.zoom.us/j/84392472211?pwd=RTVwQjZaSlVBcERHcUloc1N6THQ0QT09
Meeting ID: 843 9247 2211 Passcode: UA6mfGMR 
Abstract: 
Images in scientific publications communicate essential information, such as experiments performed and results obtained, that researchers can use as a proxy for the publication'&rsquo;s relevance to their research interests. Domains like biocuration, where biomedical experts analyze the literature to extract and organize information for future retrieval and analysis, can benefit from computationally leveraging these images in their workflows. Prior work in biomedical document classification for biocuration has shown that combining features from images (e.g., acquisition modality) with text features can improve precision and recall. However, the considerations and benefits obtained from computationally integrating such image-based features in biocuration workflows are less clear. 
Based on a multi-year collaboration with text-mining researchers and biocurators, this dissertation identifies and tackles several challenges to computationally using image-data in the biocuration process. These challenges include the scarcity of labeled datasets for training image classifiers, the lack of characterization for the needed modality classes in biocuration, the lack of available labeling systems to label extensive collections of images, and the lack of support for image-based features in academic search engines. This dissertation addresses these issues by proposing two taxonomies for image modalities found in biomedical publications; introducing training strategies using shallower neural networks and hierarchical organization of classifiers; describing two labeling systems, one for domain experts and one for model builders who require support for data understanding; and concludes by merging several building blocks into document search systems that successfully leverage image-based data.

PhD Dissertation Announcement: &ldquo;Integrating Image Features to Support the Biocuration Workflow&rdquo;

Starting Academic Year 23/24 visiting professor Zhiling Lan joins as faculty in the Department of Computer Science and EVL. Dr. Lan comes with significant expertise in high-performance computing and parallel/distributed systems. Prior to her tenure at UIC, she was a professor of Computer Science, at the Illinois Institute of Technology between 2002 and 2023. She is also a guest research faculty at Argonne National Laboratory. 
Dr. Lan also heads the <a href="https://spear.lab.uic.edu/">SPEAR (Systems for Performance, Energy, And Resiliency) lab</a>, which conducts research spanning various areas of parallel and distributed systems including cluster management, interconnection networking, performance modeling and simulation, power and energy efficiency, and fault tolerance. SPEAR&rsquo;smission is to unify systems and AI, where we are committed to creating software systems to expedite AI applications and exploring advanced AI technologies to tackle critical research challenges in computer systems.

EVL Welcomes Professor Zhiling Lan to High Performance Computing Faculty Team

Assistant Professor Sidhart Kumar joins the Computer Science and EVL faculty with expertise in High-Performance Computing.  Kumar&rsquo;s research goal is to provide a comprehensive framework for high-performance data management, critical in extracting meaningful insights from large and complex computational systems. More broadly his interest is in developing scalable algorithms and data structures that can inject interactivity and performance into data- and compute-intensive applications. Kumar's overall research relies on the effective use of techniques from a variety of domains including databases, topology, visualization, and machine learning.

Sidharth Kumar Joins EVL Affiliated Faculty - Assistant Professor, Computer Science

The 2023-2024 University Scholar Program has selected EVL professor G. Elisabeta Marai among its awarded and honored candidates. Dr. Marai is among two other designees within the College of Engineering - Professor Natasha Devroye with the Department of Electrical and Computer Engineering Department, and Professor Karl Rockne with Civil, Materials, and Environmental Engineering. Sponsored by the Office of the President, the program rewards outstanding faculty who have been recognized for their superior performance in research, teaching, and scholarly activities. 
Join us in congratulating professor Liz! 
<a href="https://emails.uofi.uic.edu/newsletter/25/464513625.html">See the full article.</a>

EVL Professor G. Elisabeta Marai Awarded 2023-2024 University Scholar

EVL professor Mike Papka and his research students have been awarded an Honorable Mention in the EuroVis Best Paper Category for &ldquo;ChemoGraph: Interactive Visual Exploration of the Chemical Space&rdquo;. Co-authored by collaborators Bharat Kale, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick Stevens, and Michael E. Papka, ChemoGraph is a novel visual analytics technique for interactively exploring related chemicals. A chemical space is formalized as a hypergraph with novel machine-learning models to compute related chemical compounds applied. It uses a database to find related compounds from an available space and a machine learning model to generate new ones, which helps enlarge the known space. Moreover, ChemoGraph highlights interactive features that support users in viewing, comparing, and organizing computationally identified related chemicals. 
<a href="https://youtu.be/kVpz6TDjQMw ">See a video teaser on EVLTube.</a>

&ldquo;ChemoGraph: Interactive Visual Exploration of the Chemical Space&rdquo; Awarded with Honorable Mention in the EuroVis Best Paper Category

The annual &ldquo;SAGE3: Smart Amplified Group Environment for Harnessing the Data Revolution&rdquo; all hands meeting was held this year at the University of Hawaii at Manoa, in Oahu, Hawaii, June 26 - 30 2023. UIC&rsquo; PI Andrew Johnson, CoPI Luc Renambot, and senior research staff member Lance Long attended the meeting with collaborators from Virginia Tech and the University of Hawaii to discuss the future of the project, achieved milestones, and current challenges. These face-to-face meetings have proven critical to the advancement of the overall project objectives, as developers are able to exchange success stories and lessons learned from their collaborative work. The intensive brainstorming has helped crystalize future directions and potential project expansion. 
Funded by NSF, SAGE3 puts the &ldquo;human in the loop&rdquo; by providing scientists with an intuitive framework that integrates state-of-the-art AI technologies with applications, workflows, smart visualizations and collaboration services to help them access, share, explore and analyze their data, come to conclusions, and make decisions with greater speed, accuracy, comprehension and confidence. The project is scheduled to conclude in 2025.

SAGE3 2023 All Hands Meeting

EVL hosted ChicagoCHI&rsquo;s June presentation &rlquo;Making Design Sense of Hearing&rdquo;, June 22, 2023. Guest Speaker Greg Olsen, Portfolio Scientist Lead in the GN Advanced Science group presented his research augmented hearing, along with design insights and considerations from compensating for age-related hearing loss to enhancing one of the 5 senses beyond the current human capability. The event was organized by EVL alumn and ChicagoCHI chair Victor Mateevisti. 
<a href="https://www.chicagochi.org/2023/06/02/making-design-sense-of-hearing/">For more information.</a>

EVL Hosts ChicagoCHI Presentation

Ph.D. Student: Ashwini G. Naik 
Committee Members: 
Dr. Nikita Soni 
Dr. Debaleena Chattopadhyay 
Dr. Steve Jones (External Member) 
Dr. Robert Kenyon (Co-Advisor) 
Dr. Andrew Johnson (Advisor and Chair) 
Date and Time: May 23, 2023, 9 AM-11 AM Chicago Time 
Location: ERF 2068 
Zoom Link: <a href="https://uic.zoom.us/j/7898336493">https://uic.zoom.us/j/7898336493</a> 
Abstract: 
Strategizing and sensemaking in immersive environments have predominantly been explored for training, learning, and recreational tasks. The ability to embed these concepts into the data analysis pipeline is recently emerging and has seen limited research. In our work, we present Personal Situated Analytics (PSA) that provides individuals the ability to embed themselves in recorded events in multiple degrees of immersion on the Reality-Virtuality spectrum, evaluate the benefits, and study their exploration patterns. With the increasing availability of sensors and capturing devices, we can now actively record and leverage data from our daily activities to gain valuable insights and make informed decisions. PSA at its core formulates a combination of embodied cognition, situated analytics, and conversation analysis while exploiting the benefits of strategic immersion and sensemaking in immersive environments. To that end, we first developed a framework for embedding the individuals in the environment where the conversation originally occurred. Secondly, we conducted a pilot user study (n=12, protocol #STUDY2023-0018), to compare user experiences while exploring recorded conversations in Mixed Reality through the HoloLens2 device, and in Virtual Reality through the Quest2 device. Our proposed framework encompasses various stages such as tracking, data capturing, data cleaning, data synchronization, prototype building, and deploying the final product to end-user hardware. In the first part of the experiment, we used datasets consisting of seated participants (protocol #2022-0354). In the future, we will record and analyze datasets with standing and non-stationary participants (protocol #STUDY2023-0509) in two settings that would employ various collaboration profiles among the participants. Drawing from our experience during the preliminary user study and the feedback we received from the participants, we catalog our lessons learned and insights which can potentially drive advancements in embodied situated analytics and thereby enhance the conversation analysis pipeline.

EVL Awarded NSF MRI Support to Build the Data Observation and Computation Collaboratory (DOCC)

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