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[Special Issue CFP] Machine Learning Approaches in Big Data Visualization, IEEE Computer Graphics and Applications (CG&A)
by Nikos Bikakis 15 Sep '21

15 Sep '21

Call for Papers Special Issue "Machine Learning Approaches in Big Data Visualization" IEEE Computer Graphics and Applications (CG&A) https://bit.ly/37EaNcn Data visualization is now one of the cornerstones of data science, turning the abundance of big data being produced through modern systems into actionable knowledge. Data visualization in the big data era raises the need to co-design and more closely align the underlying data management systems with the user-oriented techniques that state-of-the-art visualization systems now offer. Several solutions from those two communities are revisited with big data in mind, such as efficient data storage, adaptive indexing for enabling visual interaction and visual analytics, machine learning (ML)-driven visualization and new ways for visual presentation of massive data, and personalization and automation techniques that can fit to different users’ needs. Overall, modern visualization systems start integrating scalable techniques to efficiently support complex ML-based analysis over billion-object datasets, while limiting the visual response to a few milliseconds. This special issue aims to publish novel works on multidisciplinary research areas spanning from data management and ML to visualization and human-computer interaction. Topics for the Special Issue ------------------------------- Topics of interest include, but are not limited to: - Visualization, exploration, and analytics techniques for various data types (for example: text, stream, field, high-dimensional, graph, and temporal) - ML-driven visualization - Interactive data mining visualization - Progressive visual analytics - Data modeling, storage, indexing, caching, prefetching, and query processing for interactive applications - User-oriented visualization (for example: recommendation, assistance, and personalization) - Visual representation techniques (for example: aggregation, sampling, multi-level, and filtering) - In-situ visual exploration and analytics - Immersive visualization - Setting-oriented visualization (for example: display size, smart phones, and visualization over networks) - High-performance, distributed, and parallel techniques - Visualization hardware and acceleration techniques for visualization - Benchmarks for data visualization and analytics Deadlines ------------------------------- Submissions due: 29 October 2021 Publication: May/June 2022 Submission Guidelines ------------------------------- Please see the author information on how to submit a manuscript. Please submit your papers through the ScholarOne online system and be sure to select this special-issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. Guest Editors ------------------------------- Nikos Bikakis, ATHENA Research Center, Greece Panos K. Chrysanthis, University of Pittsburgh, USA George Papastefanatos, ATHENA Research Center, Greece Tobias Schreck, Graz University of Technology, Austria Contact the guest editors at cga3-2022(a)computer.org -- Nikos Bikakis Information Management Systems Institute ATHENA Research Center Athens | Greece www.nbikakis.com

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Six new PhD positions at the University of Vienna
by Anne Marie Faisst 13 Sep '21

13 Sep '21

We offer a pleasant work environment within a friendly, dynamic, international and young team in Vienna, one of the cities with the highest quality of life worldwide. The working language will be English, and we are committed to diversity and inclusion. Three of the open positions are associated with the projects “Talking charts <https://vda.cs.univie.ac.at/research/projects/project/360/>” and “Interpretability and Explainability as Drivers to Democracy <https://informatik.univie.ac.at/en/research/projects/project/354/>” funded by the Vienna Science and Technology Fund. The other three open positions are on related topics. Please see the details below. We are looking forward to your application! Project “Talking charts” The project combines perspectives and methods from Computer Science and Science & Technology Studies to explore how charts related to climate change and COVID-19 are created and understood both by researchers and public audiences. We welcome candidates with a background in Computing (with a specialization in Human Computer Interaction, Data Visualisation or Data Science) or in Information Science, Science and Technology Studies, or related areas. Read more about the project and the job description here: Project-specific PhD (3-years) https://tinyurl.com/35fpetkd <https://tinyurl.com/35fpetkd> Open topic PhD (4-years): https://tinyurl.com/yhbh66m9 <https://tinyurl.com/yhbh66m9> Please get in touch via email with Laura Koesten (laura.koesten(a)univie.ac.a <mailto:laura.koesten@univie.ac>t) or Kathleen Gregory (kathleen.gregory(a)dans.knaw.nl <mailto:kathleen.gregory@dans.knaw.nl>) if you have any questions about the role descriptions or application process for the Talking Charts project. Project “Interpretability and Explainability as Drivers to Democracy” The project is about machine learning models that are used for making decisions with significant societal impact in democratic societies. In particular, the project's aim is to enable informed evaluation of machine learning models and their usage by the electorate through interpretability and explainability of the used models and communication of these models and their roles in the decision making process in suitable forms. The underlying decision making process is considered to involve different stakeholders with different levels of expertise and achieving the project's aims requires the development of novel machine learning models, visualization approaches, and guidelines. Project-specific PhD https://tschiatschek.net/opening.html <https://tschiatschek.net/opening.html> Please get in touch via email with Sebastian Tschiatschek (sebastian.tschiatschek(a)univie.ac.at <mailto:sebastian.tschiatschek@univie.ac.at>) if you have any questions about the role descriptions or application process for the Interpretability and Explainability project. Our research groups are also filling the following related PhD positions: * Toward explainable models for environmental geoscience: https://bit.ly/2UhPry2 <https://bit.ly/2UhPry2> * Toward explainability of deep-neural-network models https://tinyurl.com/5ck4fned <https://tinyurl.com/5ck4fned> * On reinforcement Learning or probabilistic models, https://tinyurl.com/4ud9jewv <https://tinyurl.com/4ud9jewv> Please get in touch via email with Torsten Möller (torsten.moeller(a)univie.ac.at <mailto:torsten.moeller@univie.ac.at>) with questions about these roles. -- Anne Marie Faisst, BA Universität Wien Fakultät für Informatik Forschungsgruppe Visualization and Data Analysis Coordinator Research Network Data Science @ Uni Vienna Währinger Strasse 29/S6/2.04, A - 1090 Wien contact me via MS Teams

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Final call for participation: DIAGRAMS 2021
by Mikkel Willum Johansen 10 Sep '21

10 Sep '21

Dear all The Diagrams 2021 conference will begin in a few weeks, and this is the final call for participation. Registration will close on September 23, so register now to ensure your place. The schedule for the program is now ready: http://www.diagrams-conference.org/2021/index.php/program/ See more in the call below or on the conference webpage: www.diagrams-conference.org/2021<http://www.diagrams-conference.org/2021> All the best, Mikkel *** FINAL CALL for PARTICIPATION: Diagrams 2021 *** 12th International Conference on the Theory and Application of Diagrams September 28 – 30, 2021 Virtual Event www.diagrams-conference.org/2021<http://www.diagrams-conference.org/2021> *** Highlights *** - FREE REGISTRATION - Proceedings published by Springer - Three Tracks: Main, Philosophy, and Psychology and Education. - Graduate Symposium - Best Paper and Best Student Paper awards Accepted papers and tutorials are listed on the website: http://www.diagrams-conference.org/2021/index.php/program/ ***************** Registration is Open ***************** Visit http://www.diagrams-conference.org/2021/index.php/registration/ to register for Diagrams 2021. Registration closes: September 23, 2021 There is a small cost incurred, covered by the conference organising team, for each person that registers. Therefore please only register if you intend to participate in the event. ***************** Keynote Speakers ***************** Shaaron Ainsworth, University of Nottingham Daniel Rosenberg, University of Oregon Katarina Scheiter, University of Tubingen Atsushi Shimojima, Doshisha University Frederik Stjernfelt, Aalborg University of Copenhagen Francesco Bellucci, University of Bologna, is the Inspirational ECR Speaker for Diagrams 2021 ******************* Novel Program Schedule ********************* Diagrams 2021 will adopt a novel approach to scheduling talks, to accommodate different time zones across the globe. See http://www.diagrams-conference.org/2021/index.php/program/ for more details. ________________________________ Mikkel Willum Johansen Associate professor Department of Science Education University of Copenhagen Tlf: (+45) 28 72 84 41

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Deadline 9/23: VisComm late-breaking works in progress
by Arcia, Adriana 08 Sep '21

08 Sep '21

The 4th Visualization for Communication Workshop (VisComm 2021<http://viscomm.io/>) An IEEE Visualization<http://ieeevis.org/> Workshop, Sunday, October 24th VisComm is accepting late-breaking submissions until September 23rd! Late-Breaking Works in Progress The purpose of this category is to present work in progress and receive feedback from attendees. For research that is in progress, this session will provide a supportive atmosphere for helpful feedback and fresh perspectives on your aims and/or methods. Recommended structure for your one-page submission is: introduction, preliminary methods, preliminary findings (if applicable), and questions for attendees. For practitioners, this is an opportunity to present contributions that showcase innovative visualizations or provide provocations for new ideas to emerge. Your one-page brief should include project background, design objectives, methods or design process, links to visualization design alternatives, preliminary findings (if available), and questions for attendees. VISCOMM COMMUNITY At VisComm, we want to provide avenues for collaboration and networking. We are creating a directory of people willing to be contacted about their areas of expertise. The directory will be unveiled during VIS week and thereafter will be available to anyone who signs up for the VisComm email list. Follow this link to add your entry to the directory<https://forms.gle/FWYGEqKA5eu44NRW9> Organizers viscomm_chairs(a)googlegroups.com<mailto:viscomm_chairs@googlegroups.com> Barbara Millet<https://com.miami.edu/profile/barbara-millet/>, University of Miami Jonathan Schwabish<https://policyviz.com/>, Urban Institute Alvitta Ottley<https://engineering.wustl.edu/Profiles/Pages/Alvitta-Ottley.aspx>, Washington University in St. Louis Adriana Arcia<https://www.nursing.columbia.edu/profile/adriana-arcia-phd>, Columbia University @VisWkshp #VisComm2021 #VisComm #ieeevis #ieeevis2021

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[3rd Call for Paper] Workshops and grand challenge of the 4th IEEE International Conference on Artificial Intelligence and Virtual Reality (IEEE AIVR 2021)
by Anita Hu 30 Aug '21

30 Aug '21

Dear Researchers, IEEE International Conference on Artificial Intelligence and Virtual Reality (IEEE AIVR 2021) is a unique event addressing researches of AI as well as Virtual, Augmented, and Mixed Reality. This year, we have one grand challenge session sponsored by MediaTek and 5 worksohps on interesting topics listed as follows. Please refer to the IEEE AIVR 2021 website ( http://www.ieee-aivr.org/) for the details of paper submission and challenge participation rules. We look forward to seeing you in IEEE AIVR 2021 ! Sincerely, Organization Committee of IEEE AIVR 2021 ===== - *Grand challenge: Visual Attention Estimation in HMD* ( https://ieee-aivr.cs.nthu.edu.tw/challenge/vae) - Awards: According to the points in the final evaluation, we select the top-3 teams for regular awards. - Champion: $USD 1,500 - 1st Runner-up: $USD 1,000 - 3rd-place: $USD 750 - Best accuracy award in the final competition (without considering model efficiency): $USD 600 - Important Dates - Qualification Competition Start Date: August 02, 2021 - Qualification Competition End Date: September 30, 2021 - Final Competition Start Date: October 1, 2021 - Final Competition End Date: October 11, 2021 - Camera Ready Date: October 27, 2021 - Presentation Date: November 16, 2021 - *[AIMLC] Workshop on AI in Music and Live Concerts* - Important Dates: please refer to https://ieee-aivr.cs.nthu.edu.tw/workshops/ai-in-music-and-live-concert - *[AIXR] Workshop on Artificial Intelligence and Ethics in XR* - Important Dates: please refer to https://sites.google.com/view/aixr/aixr-2021 - *[CCVAR] Workshop on Computational Creativity in Virtual and Augmented Reality* - Important Dates: please refer to https://sites.google.com/view/ccvar - *[MARCH] Workshop on Modeling and Animating Realistic Crowds and Humans* - Important Dates: please refer to https://sites.google.com/view/ieee-aivr2021-march - *[XRTM] Workshop on XR Technologies in Museums* - Important Dates: please refer to http://colors.ise.ibaraki.ac.jp/AIVR2021/ =====

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VISSOFT 2021 - Call for Participation
by Carolin Brandt 30 Aug '21

30 Aug '21

VISSOFT 2021 ---- Sep 27-28, 2021, Virtual, co-located with ICSME 2021 --- https://vissoft.info/2021/ Registration link: https://icsme2021.github.io/Registration.html **** Early registration rate until September 4, 2021 **** ---------------------------------------------------------------------------------------------------------------------------------------- VISSOFT 2021 is the 9th IEEE Working Conference on Software Visualization, virtually co-located with ICSME 2021 (https://icsme2021.github.io/index.html) The VISSOFT conference is principally a venue for publishing and discussing research related to software visualization. VISSOFT brings together a community of researchers from software engineering, information visualization, human-computer interaction, computer graphics, and data science to discuss theoretical foundations, algorithms, techniques, tools, and applications related to software visualization. On September 27th and 28th we will discuss a range of excellent papers. Accepted were 9 Technical papers, 12 New Ideas and Emerging Results / Tool Demo papers and two Journal-First presentations. You can find a full list of the accepted papers below! The keynote will be delivered by Michele Lanza from the Università della Svizzera italiana. Daniel Weiskopf from the University of Stuttgart will be our capstone speaker. The program is available at: https://vissoft.info/2021/program.html Follow us on Twitter to stay up to date: https://twitter.com/IEEEVISSOFT ---------------------------------------------------------------------------------------------------------------------------------------- Accepted Papers: ---- Technical Papers ---- 1 A Scalable Log Differencing Visualisation Applied to COBOL Refactoring Céline Deknop, Kim Mens, Alexandre Bergel, Johan Fabry and Vadim Zaytsev 2 CodeCity: On-Screen or in Virtual Reality? David Moreno-Lumbreras, Roberto Minelli, Andrea Villaverde, Michele Lanza and Jesus M. Gonzalez-Barahona 3 CodingTM: Development Task Visualization for SW Code Comprehension Taeyoung Kim, Suntae Kim and Duksan Ryu 4 Continuous Rationale Visualization Anja Kleebaum, Barbara Paech, Jan Ole Johanssen and Bernd Bruegge 5 Global Overviews of Granular Test Coverage with Matrix Visualizations Kaj Dreef, Vijay Krishna Palepu and James Jones 6 Trace Visualization within the Software City Metaphor: A Controlled Experiment on Program Comprehension Veronika Dashuber and Michael Philippsen 7 TransVis: Using Visualizations and Chatbots for Supporting Transient Behavior in Microservice Systems Samuel Beck, Sebastian Frank, Mir Alireza Hakamian, Leonel Merino and André van Hoorn 8 Visualization of Object-Oriented Variability Implementations as Cities Johann Mortara, Philippe Collet and Anne-Marie Déry 9 Visualizing Metric Trends for Software Portfolio Quality Management Patric Genfer, Johann Grabner, Christina Zoffi, Mario Bernhart and Thomas Grechenig ---- NIER/TD Papers ---- 1 Analyzing and Visualizing Projects and their Relations in Software Ecosystems Van Tuan Tran, Cheng Cheng, Fabio Petrillo and Yann-Gaël Guéhéneuc 2 Augmenting Code Review Experience Through Visualization Faruk Balcı, Dilruba Sultan Haliloğlu, Onur Şahin, Cankat Tilki, Mehmet Ata Yurtsever and Eray Tüzün 3 CHANGEVIZ: Enhancing the GitHub Interface with Method Calls Information Lorenzo Gasparini, Enrico Fregnan, Larissa Braz, Tobias Baum and Alberto Bacchelli 4 Codoc: Code-driven Architectural View Specification Framework for Python Casper Weiss Bang and Mircea Lungu 5 Live Visualization of Dynamic Software Cities with Heat Map Overlays Alexander Krause, Malte Hansen and Wilhelm Hasselbring 6 React-bratus: Visualising React.js Component Hierarchies Mircea Lungu and Stephan Boersma 7 Towards a JSON-based Algorithm Animation Language Artturi Tilanterä, Giacomo Mariani, Ari Korhonen and Otto Seppälä 8 Visualizing Data in Software Cities Susanna Ardigò, Csaba Nagy, Roberto Minelli and Michele Lanza 9 Visualizing Discord Servers Marco Raglianti, Roberto Minelli, Csaba Nagy and Michele Lanza 10 Visualizing GitHub Issues Aron Fiechter, Roberto Minelli, Csaba Nagy and Michele Lanza 11 Visually Analyzing the Code Quality of Component-based Web Applications Hagen Tarner, Daniel van den Bongard and Fabian Beck 12 Voronoi Evolving Treemaps Davide Paolo Tua, Roberto Minelli and Michele Lanza ---- Journal First Papers ---- 1 Visual Augmentation of Source Code Editors: A Systematic Mapping Study Matúš Sulír, Michaela Bačíková, Sergej Chodarev and Jaroslav Porubän 2 An Architecture-Tracking Approach to Evaluate a Modular and Extensible Flight Software for CubeSat Nanosatellites Carlos Gonzalez, Camilo Rojas, Alexandre Bergel and Marcos Diaz ---------------------------------------------------------------------------------------------------------------------------------------- Carolin Brandt PhD Student TU Delft // EEMCS // Software Engineering Research Group // TestShift Project E c.e.brandt(a)tudelft.nl<mailto:c.e.brandt@tudelft.nl> // T https://twitter.com/laci_noire // W https://carolin-brandt.de/

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Call for Participation: 1st Workshop on Audio-Visual Analytics on Sept 3, 2021
by Aigner Wolfgang 30 Aug '21

30 Aug '21

The 1st Workshop on Audio-Visual Analytics will focus on identifying research gaps for integrating sonification and visualization. It will be hosted at Audio Mostly 2021, the interdisciplinary conference on design and experience of interaction with sound. Time: September 3, 2021 14:30 – 17:30 CEST (8:30 – 11:30 am EDT) Place: virtually on Zoom Access Link: YouTube Stream - please choose Day 3: https://www.youtube.com/channel/UCCp8hfYyfdnWqOd7p6ccw-g The workshop aims to build a community of researchers from both the visualization and the sonification communities and to identify research gaps for the systematic combination of visualization and sonification. Attending the workshop and the Audio Mostly conference is *free*: https://audiomostly.com Our workshop will take place on the 3rd of September between 2:30 pm and 5:30 pm (CEST, Italy). The Audio-Visual Analytics workshop will be a fully remote, virtual event due to the continuing COVID-19 pandemic and in alignment with the decision not to host a physical meeting for Audio Mostly 2021. Group and plenary discussions will use the virtual platforms Zoom and Miro. We scheduled the larger part of the day for group and plenary discussions and it is open to all Audio Mostly 2021 attendees. The workshop will be organized along parallel working sessions formed around predefined topic streams (Theory, Design Process, Tools, and Evaluation). The participants will be able to choose between these topics based on their interests. We expect the workshop to result in a collection of open research questions on how to combine visualization and sonification. An already confirmed follow-up workshop at IEEE VIS in October 2021 drives this further towards a research agenda for a combined design theory. Details about both workshops can be found here: https://audio-visual-analytics.github.io/am2021.html We are looking forward to see many of you this Friday! Workshop Organizers: - Wolfgang Aigner, St. Pölten University of Applied Sciences, Austria and TU Wien, Austria - Niklas Elmqvist, University of Maryland, College Park, USA - Kajetan Enge, St. Pölten University of Applied Sciences, Austria and University of Music and Performing Arts Graz, Austria - Robert Höldrich, University of Music and Performing Arts Graz, Austria - Michael Iber, St. Pölten University of Applied Sciences, Austria - Alexander Rind, St. Pölten University of Applied Sciences, Austria - Niklas Rönnberg, Linköping University, Sweden - Bruce Walker, Georgia Institute of Technology, USA Contact: kajetan.enge(a)fhstp.ac.at -- WOLFGANG AiGNER Scientific Director Institute of Creative\Media/Technologies (IC\M/T) Department Media & Digital Technologies St. Poelten University of Applied Sciences Matthias Corvinus Strasse 15, 3100 St. Poelten, Austria wolfgang.aigner(a)fhstp.ac.at +43 (0) 2742 313 228 - 611 http://icmt.fhstp.ac.at/en/team/wolfgang-aigner @wolfgangaigner FN 146616m, LG St. Pölten, DVR 1028669F

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Two open positions (tenure track and teaching) at Ontario Tech University
by Christopher Collins 17 Aug '21

17 Aug '21

The Faculty of Science at Ontario Tech University is hiring two computer science faculty members - one research tenure track and one teaching position. The ad mentions 'systems' as the area broadly, but it really is open broadly if the candidate is right. https://universityofontarioit-openhire.silkroad.com/epostings/index.cfm?fus… and https://UniversityOfOntarioIT-openhire.silkroad.com/epostings/index.cfm?fus… If you have any questions or plan to apply, feel free to be in touch. Chris ____________________________________________ Christopher Collins, Ph.D. :: Associate Professor [he/him] Canada Research Chair in Linguistic Information Visualization Faculty of Science :: Ontario Tech University http://vialab.ca

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Postdoctoral associate position at CU Boulder
by Morteza Karimzadeh 15 Aug '21

15 Aug '21

Dear All, We invite applications for a Postdoctoral Research Associate position at the University of Colorado Boulder (CU Boulder), with a flexible starting date of November 2021. Job advertisement below. The candidate does not need to check all these boxes, since they will be part of an interdisciplinary team. The bullet points indicate our wish list. We are highly interested in a VIS- or VA-oriented postdoc with foundation in ML and stats. We are creating research-oriented software infrastructure for interactive learning to facilitate earth data fusion, and we anticipate user studies with experts in the future. We already have an established line of communication with domain operational users and scientists for this purpose. Regards, Morteza Morteza Karimzadeh, PhD Assistant Professor of Geography Affiliate Assistant Professor, Computer Science, Information Science University of Colorado Boulder Traditional Territories of the Arapaho, Cheyenne and Ute Nations 303-492-3252 karimzadeh(a)colorado.edu<mailto:karimzadeh@colorado.edu> Postdoctoral Research Associate Position at CU Boulder University of Colorado Boulder, Boulder, CO Starting date (flexible): 11/1/2021 Application review begins September 15, 2021 on a rolling basis until the position is filled. We invite applications for a Postdoctoral Research Associate position at the Department of Geography, University of Colorado Boulder (CU Boulder), with a flexible starting date of November 2021. The postdoctoral scientist will have expertise in one or more areas of (spatiotemporal) machine learning, spatial statistics, and/or (geo)visual analytics and geovisualization. The postdoc will join a vibrant and growing team of graduate students and postdocs making methodological and applied contributions in the context of funded projects spanning environmental/cryosphere applications, machine learning-based epidemiological modeling, and spatial demography. All projects leverage either linear (e.g., spatial statistics) and/or non-linear (e.g., deep learning) models, therefore, solid foundation in statistics and machine learning is key. Interest and skills in R&D of user-facing visual analytics is an advantage. Our funded projects include a CU Boulder-funded award (Recovering from a Pandemic: Unraveling Neighborhood Geographic Disparities in Consumer and Business Behavior in 2021) in collaboration with CU Boulder economists, an NSF-funded EarthCube project focused on high-resolution mapping and classification of sea ice (Data Capabilities: Enabling Analysis of Heterogeneous, Multi-source Cryospheric Data, Award# 2026962) in collaboration with remote sensing and sea-ice geoscientists, and other projects in collaboration with spatial demographers and epidemiologists at CU Population Center and New York-based Population Council on machine learning-based predictive modeling of COVID-19 and infectious diseases. The postdoctoral position will be homed in the Geography Department at CU Boulder under the supervision of PI Dr. Morteza Karimzadeh, and will actively collaborate with co-PIs, scientists, students and interface with stakeholders across multiple agencies based on the specific assigned project(s), including the National Snow and Ice Data Center (NSIDC), CU Denver's Department of Computer Science, CU Population Center, Population Council, CU Boulder Economics, and the National Geospatial Intelligence Agency (NGA). The University of Colorado Boulder is committed to building a culturally diverse community of faculty, staff, and students dedicated to contributing to an inclusive campus environment. We are an Equal Opportunity employer, including veterans and individuals with disabilities. Who We Are We are a team of geospatial scientists, making methodological and applied contributions in collaboration with domain experts and stakeholders in the context of transdisciplinary projects. Our expertise is situated between geography, computer science, GIS, and data science. We use our knowledge to bridge the physical and human sciences. Our research spans an exceptional array of disciplines. We train our students and scholars - in a friendly, well-supported environment - to be top scientists as well as citizens of the broader world to which we are all connected. The Department of Geography is ranked as one of the top programs among the nation's doctoral-granting departments of geography. CU Geography has one of the nation's highest rates of PhD placement in academic geography programs as well as one of the highest rates of external funding for graduate student research. What Your Key Responsibilities Will Be * Design and implement algorithms, software and computational modules in collaboration with team members. * Draft and lead scholarly publications and reports. * Assist the PI with leading and managing research activities within the group. * Assist the PI with user evaluations and stakeholder engagement. * Mentor graduate and undergraduate students in the team. * Assist in drafting successful research grant proposals. * Interface with other research groups at and beyond CU Boulder. What You Should Know * Starting date (flexible): November 2021. * The initial offer is for 12 months, with strong potential for renewal contingent upon favorable progress and funding availability. * This is a unique postdoctoral research associate opportunity providing the expertise of multiple collaborators in other fields at the disposal of the postdoc for excelling in cutting-edge research. What We Can Offer The salary range for this position is $52,000-$56,000 commensurate with experience. The benefits go well beyond salary at CU Boulder. The applicant will be eligible for CU Boulder's faculty, graduate and family housing apartment rentals with excellent rates close to downtown Boulder. This position is eligible for University of Colorado's generous Research Faculty benefits including retirement, health and life insurance programs. You can find additional information about the options available to you within our benefits plans on the CU System website: http://www.cu.edu/employeeservices/benefits. What We Require: * A Ph.D. in geography, computer science, information science, statistics, geosciences or a cognate field is mandatory. * Solid foundation in machine learning, applied statistics and basic skills in GIS is required. What You Will Need: Given the transdisciplinary nature of this postdoctoral position, we expect that the candidate will possess some of the following, with interest in developing other necessary items depending on the specific projects identified for the postdoc: * Research background and expertise in (applied) machine learning and particularly, deep learning. * Background and experience working with spatial data, geographic information systems and earth observations. * Programming skills in Python, Scikit-learn and deep learning libraries (TensorFlow or PyTorch). Working ability with R and its spatial packages is a plus, especially for spatial stats projects. * Excellent oral and written communication skills are mandatory. * Research background and expertise in spatial statistics and generalized linear models. What We Would Like You to Have (Desired but not Mandatory): * Remote sensing knowledge is highly desirable. * Interest or background in visual analytics for interactive machine learning. * Front-end development and visualization skills using D3.js, leaflet.js and the React framework is desirable. * Experience working with cloud storage and compute instances. * Familiarity with passive and active microwave imagery, airborne and spaceborne lidar altimetry is desirable (examples include SAR imagery from Sentinel-1, lidar altimetry data from Operation IceBridge and ICESat-2, and radar altimetry data from CryoSat-2). * Experience in working with the output of climate models. Special Application Instructions for Applicants: To apply, please submit the following materials through the application portal https://jobs.colorado.edu/jobs/JobDetail/?jobId=32485&emailCampaignId=168f: 1. Resume/CV 2. Cover Letter 3. Research Statement During the application process, you will need to enter contact information for two references and we will request letters of recommendation and additional materials if needed, as the search progresses. Both beginning and senior postdoctoral candidates are encouraged to apply. Please direct your questions to Dr. Morteza Karimzadeh (karimzadeh(a)colorado.edu<mailto:karimzadeh@colorado.edu>). Applications will be reviewed on a rolling basis starting September 15, 2021 until the position is filled. Note: Application materials can not be accepted via email. For consideration, applications must be submitted through CU Boulder Jobs.<https://jobs.colorado.edu/jobs/JobDetail/?jobId=32485&emailCampaignId=168f>

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[Special Issue CFP] Machine Learning Approaches in Big Data Visualization, IEEE Computer Graphics and Applications (CG&A)
by Nikos Bikakis 13 Aug '21

13 Aug '21

Call for Papers Special Issue "Machine Learning Approaches in Big Data Visualization" IEEE Computer Graphics and Applications (CG&A) https://bit.ly/37EaNcn Data visualization is now one of the cornerstones of data science, turning the abundance of big data being produced through modern systems into actionable knowledge. Data visualization in the big data era raises the need to co-design and more closely align the underlying data management systems with the user-oriented techniques that state-of-the-art visualization systems now offer. Several solutions from those two communities are revisited with big data in mind, such as efficient data storage, adaptive indexing for enabling visual interaction and visual analytics, machine learning (ML)-driven visualization and new ways for visual presentation of massive data, and personalization and automation techniques that can fit to different users’ needs. Overall, modern visualization systems start integrating scalable techniques to efficiently support complex ML-based analysis over billion-object datasets, while limiting the visual response to a few milliseconds. This special issue aims to publish novel works on multidisciplinary research areas spanning from data management and ML to visualization and human-computer interaction. Topics for the Special Issue ------------------------------- Topics of interest include, but are not limited to: - Visualization, exploration, and analytics techniques for various data types (for example: text, stream, field, high-dimensional, graph, and temporal) - ML-driven visualization - Interactive data mining visualization - Progressive visual analytics - Data modeling, storage, indexing, caching, prefetching, and query processing for interactive applications - User-oriented visualization (for example: recommendation, assistance, and personalization) - Visual representation techniques (for example: aggregation, sampling, multi-level, and filtering) - In-situ visual exploration and analytics - Immersive visualization - Setting-oriented visualization (for example: display size, smart phones, and visualization over networks) - High-performance, distributed, and parallel techniques - Visualization hardware and acceleration techniques for visualization - Benchmarks for data visualization and analytics Deadlines ------------------------------- Submissions due: 29 October 2021 Publication: May/June 2022 Submission Guidelines ------------------------------- Please see the author information on how to submit a manuscript. Please submit your papers through the ScholarOne online system and be sure to select this special-issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. Guest Editors ------------------------------- Nikos Bikakis, ATHENA Research Center, Greece Panos K. Chrysanthis, University of Pittsburgh, USA George Papastefanatos, ATHENA Research Center, Greece Tobias Schreck, Graz University of Technology, Austria Contact the guest editors at cga3-2022(a)computer.org -- _ nikos

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