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Last Reminder >>> [PhD Position Opening] Prae-doc position on Visual Analytics and Information Diffusion @ TU Vienna – 30/40 hrs (m/f/d)
by Miksch Silvia 28 Jan '24

28 Jan '24

## Apologies if you receive multiple copies of this message ## --------------------------------------------------------------- ** FUNDED PHD POSITION AT TU VIENNA ** --------------------------------------------------------------- Funded PhD position within the ViSual ANalytics for Event-based Diffusion on Networks (SANE) project @ TU Wien f/m/d (30-40h) We are hiring a talented PhD candidate in an international project on the visual analytics of complex diffusion processes over temporal networks. You will work in the context of SANE, a project held by TU Vienna (Austria), the University of Cologne (Germany) and the University of Newcastle (United Kingdom). This project arrangement gives you unique career opportunities, including student exchanges abroad, regular meetings with researchers from the other institutions participating to the project. We are looking for a PhD candidate to work from the TU Wien, at the Institute of Visual Computing and Human-Centered Technology, in the Research Unit of Visual Analytics. We offer a position as project assistant (prae-doc) limited to 3 years for 30 hours/week (that can beextended to 40). Gross annual (monthly) salary of Euro 43,650 (2,464.80) according to FWF regulations. In this position, you will begin your doctoral journey studying problems related to the topic of event-based(or “temporal”) network visualization. In Event-based networks, the time coordinates where the nodes and the edges are “active” are an explicit element of the representation, differently from traditional timeslicing where a time structure is imposed over the input data. You will apply these concepts to the problem of Information Diffusion. Information Diffusion studies how “information” flows and spreads through an underlying network, and has been used to model, simulate, and predict natural and human-made phenomena in countless different domains (e.g., pathogen spread, malware outbreak in computer networks, viral marketing, etc.). However, little research has been done on this problem within the context of visualization. Wanna know more? Check the project description and complete job posting at https://www.cvast.tuwien.ac.at/projects/sane --------------------------------------------------------------- Deadline for applications: 29 January 2024 Expected start: March 2024 --------------------------------------------------------------- Questions? You can reach me at Alessio.arleo(a)tuwien.ac.at

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[Open for Submissions] 1st Workshop on Visual Process Analytics (VIPRA 2024) - Co-Located EuroVis 2024
by Arleo, Alessio 22 Jan '24

22 Jan '24

##################################################### 1st Workshop on Visual Process Analytics (VIPRA 2024) https://vipra-workshop.github.io/homepage/ ##################################################### Call for Papers ---------------- The 2024 Workshop on Visual Process Analytics (Vipra 2024) is the 1st annual workshop that provides an opportunity for participants to discuss state-of-the-art event visualization and process mining and learn how both techniques can mutually benefit each other. In this workshop we aim to bring together researchers from both Visual Analytics and Process Mining, to learn, create a common language, spark collaborations, and advance both fields. Process Mining is a data-driven discipline that focuses on extracting valuable insights and knowledge from the vast amount of event data generated within organizations. It involves the discovery, analysis, and improvement of process models by leveraging techniques from data science, machine learning, and data analytics. By examining event logs and historical data, process mining aims to provide a clear, objective view of how processes actually operate, identifying bottlenecks, deviations, and opportunities for optimization. In turn, this supports organizations in making more data-informed decisions, and enhance operational efficiency. Visual analytics is an interdisciplinary field that combines data visualization, analytical techniques, and interactive interfaces to help people make sense of complex and often large datasets. It focuses on using the power of visual representations to facilitate data exploration, pattern recognition, and decision-making. By enabling users to interact with data through graphical interfaces, visual analytics promotes a deeper understanding of information, uncovers hidden insights, and supports the detection of trends, anomalies, and relationships that might be challenging to discern through traditional data analysis methods alone. We believe that process mining and visual analytics can mutually benefit each other. Until now, there has been limited interaction between the two fields, despite their shared objectives. In process mining, the emphasis has traditionally been on data extraction and process discovery, often neglecting the visualization aspect, whereas in visual analytics, event visualization efforts have often overlooked the wealth of process mining techniques that can enhance visualizations and analysis. Bridging this gap and fostering collaboration between the two fields will not only lead to more informed, efficient, and data-driven improvements in various domains but also advance the research and innovation in both process mining and visual analytics, ultimately contributing to a more holistic and integrated approach to understanding and optimizing complex processes. Topics and Scope ---------------- We encourage submissions from all areas on the intersection of visual analytics and process mining. The 2024 Workshop on Visual Process Analytics will cover a range of topics exploring the intersection of PM and VA including (but not limited to): - VA to support exploration and comparison of discovered process models - VA to support the comparison of event logs and process models, e.g., in conformance checking - VA to support the generation of hypotheses about the business process and the identification of process improvement ideas - VA to represent temporal and spatial uncertainty in PM models - Research challenges, pitfalls, and opportunities related to the intersection of VA and PM - The role of AI in PM, and how Visualization and explainable-AI solutions can support model comprehension, exploration, and refinement Paper Submission, Publication, and Format Guidelines -------------------------------------- We will accept short papers with up to 5 pages plus one page of references (5 + 1). We encourage a diverse range of submissions and demonstrations in any of the short paper types listed below: - Application/Case-study papers (format: 5 + 1) - Research papers (format: 5 + 1) - Position papers and system demos papers (format: 2 + 1) All material will be submitted via the Precision Conference System (PCS): https://new.precisionconference.com/submissions For all submissions, please use the EuroVis 2024 LateX2e Style. On Overleaf, this template can be imported easily by selecting "New Project" -> "Upload Project" and uploading the zip file. Use EGAuthorGuidelines-eurovis24-short.tex for your submission: https://medialib.cmcdn.dk/medialibrary/80234312-1C55-406C-86A7-410099EB2739… Accepted papers will be included in the EuroGraphics Digital Library and will be assigned a DOI as fully citable publications. Contact vipra.workshop at gmail.com if you have any questions or visit https://vipra-workshop.github.io/homepage/ Important Dates --------------- - Deadline for submission: March 1st, 2024 - Notification of acceptance: April 12th, 2024 - Camera-ready papers due: April 26th, 2024 - Vipra 2024 Workshop: May 27th, 2024 (in conjunction with EuroVis 2024) All submission deadlines are at 23:59 GMT on the date indicated. Organizers ---------- Alessio Arleo, TU Wien Stef van den Elzen, Eindhoven University of Technology Tatiana von Landesberger, Universität Köln Luise Pufahl, TU München - Heilbronn Jana-Rebecca Rehse, Universität Mannheim Francesca Zerbato, Universität St. Gallen

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[PhD Position Opening] Prae-doc position on Visual Analytics and Information Diffusion @ TU Vienna – 30/40 hrs (m/f/d)
by Arleo, Alessio 08 Jan '24

08 Jan '24

--------------------------------------------------------------------------------- ** REMINDER: FUNDED PHD POSITION AT TU VIENNA ** --------------------------------------------------------------------------------- Funded PhD position within the ViSual ANalytics for Event-based Diffusion on Networks (SANE) project @ TU Wien f/m/d (30-40h) We are hiring a talented PhD candidate in an international project on the visual analytics of complex diffusion processes over temporal networks. You will work in the context of SANE, a project held by TU Vienna (Austria), the University of Cologne (Germany) and the University of Newcastle (United Kingdom). This project arrangement gives you unique career opportunities, including student exchanges abroad, regular meetings with researchers from the other institutions participating to the project. We are looking for a PhD candidate to work from the TU Wien, at the Institute of Visual Computing and Human-Centered Technology, in the Research Unit of Visual Analytics. We offer a position as project assistant (prae-doc) limited to 3 years for 30 hours/week (that can beex-tended to 40). Gross annual (monthly) salary of Euro 43,650 (2,464.80) according to FWF regulations. In this position, you will begin your doctoral journey studying problems related to the topic of event-based (or “temporal”) network visualization. In Event-based networks, the time coordinates where the nodes and the edges are “active” are an explicit element of the representation, differently from traditional timeslicing where a time structure is imposed over the input data. You will apply these concepts to the problem of Information Diffusion. Information Diffusion studies how “information” flows and spreads through an underlying network, and has been used to model, simulate, and predict natural and human-made phenomena in countless different domains (e.g., pathogen spread, malware outbreak in computer networks, viral marketing, etc.). However, little research has been done on this problem within the context of visualization. Wanna know more? Check the project description and complete job posting at https://www.cvast.tuwien.ac.at/projects/sane --------------------------------------------------------------- Deadline for applications: 29 January 2024 Expected start: March 2024 (Negotiable) --------------------------------------------------------------- Questions? You can reach me at Alessio.arleo(a)tuwien.ac.at<mailto:Alessio.arleo@tuwien.ac.at>

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[PhD Position Opening] Prae-doc position on Visual Analytics and Information Diffusion @ TU Vienna – 30/40 hrs (m/f/d)
by Arleo, Alessio 20 Dec '23

20 Dec '23

## Apologies if you receive multiple copies of this message ## --------------------------------------------------------------- ** FUNDED PHD POSITION AT TU VIENNA ** --------------------------------------------------------------- Funded PhD position within the ViSual ANalytics for Event-based Diffusion on Networks (SANE) project @ TU Wien f/m/d (30-40h) We are hiring a talented PhD candidate in an international project on the visual analytics of complex diffusion processes over temporal networks. You will work in the context of SANE, a project held by TU Vienna (Austria), the University of Cologne (Germany) and the University of Newcastle (United Kingdom). This project arrangement gives you unique career opportunities, including student exchanges abroad, regular meetings with researchers from the other institutions participating to the project. We are looking for a PhD candidate to work from the TU Wien, at the Institute of Visual Computing and Human-Centered Technology, in the Research Unit of Visual Analytics. We offer a position as project assistant (prae-doc) limited to 3 years for 30 hours/week (that can beex-tended to 40). Gross annual (monthly) salary of Euro 43,650 (2,464.80) according to FWF regulations. In this position, you will begin your doctoral journey studying problems related to the topic of event-based (or “temporal”) network visualization. In Event-based networks, the time coordinates where the nodes and the edges are “active” are an explicit element of the representation, differently from traditional timeslicing where a time structure is imposed over the input data. You will apply these concepts to the problem of Information Diffusion. Information Diffusion studies how “information” flows and spreads through an underlying network, and has been used to model, simulate, and predict natural and human-made phenomena in countless different domains (e.g., pathogen spread, malware outbreak in computer networks, viral marketing, etc.). However, little research has been done on this problem within the context of visualization. Wanna know more? Check the project description and complete job posting at https://www.cvast.tuwien.ac.at/projects/sane --------------------------------------------------------------- Deadline for applications: 29 January 2024 Expected start: March 2024 --------------------------------------------------------------- Questions? You can reach me at Alessio.arleo(a)tuwien.ac.at <mailto:Alessio.arleo@tuwien.ac.at>

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Open PhD Position on
by Arleo, Alessio 19 Dec '23

19 Dec '23

--------------------------------------------------------------- ** FUNDED PHD POSITION AT TU VIENNA ** --------------------------------------------------------------- Funded PhD position within the ViSual ANalytics for Event-based Diffusion on Networks (SANE) project @ TU Wien f/m/d (30-40h) We are hiring a talented PhD candidate in an international project on the visual analytics of complex diffusion processes over temporal networks. You will work in the context of SANE, a project held by TU Vienna (Austria), the University of Cologne (Germany) and the University of Newcastle (United Kingdom). This project arrangement gives you unique career opportunities, including student exchanges abroad, regular meetings with researchers from the other institutions participating to the project. We are looking for a PhD candidate to work from the TU Wien, at the Institute of Visual Computing and Human-Centered Technology, in the Research Unit of Visual Analytics. We offer a position as project assistant (prae-doc) limited to 3 years for 30 hours/week (that can beex-tended to 40). Gross annual (monthly) salary of Euro 43,650 (2,464.80) according to FWF regulations. In this position, you will begin your doctoral journey studying problems related to the topic of event-based (or “temporal”) network visualization. In Event-based networks, the time coordinates where the nodes and the edges are “active” are an explicit element of the representation, differently from traditional timeslicing where a time structure is imposed over the input data. You will apply these concepts to the problem of Information Diffusion. Information Diffusion studies how “information” flows and spreads through an underlying network, and has been used to model, simulate, and predict natural and human-made phenomena in countless different domains (e.g., pathogen spread, malware outbreak in computer networks, viral marketing, etc.). However, little research has been done on this problem within the context of visualization. Wanna know more? Check the project description and complete job posting at https://www.cvast.tuwien.ac.at/projects/sane --------------------------------------------------------------- Deadline for applications: 29 January 2024 Expected start: March 2024 --------------------------------------------------------------- Questions? You can reach me at Alessio.arleo(a)tuwien.ac.at<mailto:Alessio.arleo@tuwien.ac.at> ================================================================ Alessio Arleo, Ph.D. Vienna University of Technology (TU Wien) Faculty of Informatics Institute of Visual Computing & Human-Centered Technology Favoritenstrasse 9-11 /193-07 A-1040 Vienna, Austria, Europe email: alessio.arleo(a)tuwien.ac.at<mailto:alessio.arleo@tuwien.ac.at> url: https://alessioarleo.com phone: +43-1-58801-188211 =================================================================

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[CfP] 1st Workshop on Visual Process Analytics (VIPRA 2024) - Co-Located EuroVis 2024
by Arleo, Alessio 19 Dec '23

19 Dec '23

##################################################### 1st Workshop on Visual Process Analytics (VIPRA 2024) - May 27th, 2024 (in conjunction with EuroVis 2024), Odense, Denmark – https://vipra-workshop.github.io/homepage/ ##################################################### Call for Papers ---------------- The 2024 Workshop on Visual Process Analytics (Vipra 2024) is the 1st annual workshop that provides an opportunity for participants to discuss state-of-the-art event visualization and process mining and learn how both techniques can mutually benefit each other. In this workshop we aim to bring together researchers from both Visual Analytics and Process Mining, to learn, create a common language, spark collaborations, and advance both fields. Process Mining is a data-driven discipline that focuses on extracting valuable insights and knowledge from the vast amount of event data generated within organizations. It involves the discovery, analysis, and improvement of process models by leveraging techniques from data science, machine learning, and data analytics. By examining event logs and historical data, process mining aims to provide a clear, objective view of how processes actually operate, identifying bottlenecks, deviations, and opportunities for optimization. In turn, this supports organizations in making more data-informed decisions, and enhance operational efficiency. Visual analytics is an interdisciplinary field that combines data visualization, analytical techniques, and interactive interfaces to help people make sense of complex and often large datasets. It focuses on using the power of visual representations to facilitate data exploration, pattern recognition, and decision-making. By enabling users to interact with data through graphical interfaces, visual analytics promotes a deeper understanding of information, uncovers hidden insights, and supports the detection of trends, anomalies, and relationships that might be challenging to discern through traditional data analysis methods alone. We believe that process mining and visual analytics can mutually benefit each other. Until now, there has been limited interaction between the two fields, despite their shared objectives. In process mining, the emphasis has traditionally been on data extraction and process discovery, often neglecting the visualization aspect, whereas in visual analytics, event visualization efforts have often overlooked the wealth of process mining techniques that can enhance visualizations and analysis. Bridging this gap and fostering collaboration between the two fields will not only lead to more informed, efficient, and data-driven improvements in various domains but also advance the research and innovation in both process mining and visual analytics, ultimately contributing to a more holistic and integrated approach to understanding and optimizing complex processes. Topics and Scope ---------------- We encourage submissions from all areas on the intersection of visual analytics and process mining. The 2024 Workshop on Visual Process Analytics will cover a range of topics exploring the intersection of PM and VA including (but not limited to): - VA to support exploration and comparison of discovered process models - VA to support the comparison of event logs and process models, e.g., in conformance checking - VA to support the generation of hypotheses about the business process and the identification of process improvement ideas - VA to represent temporal and spatial uncertainty in PM models - Research challenges, pitfalls, and opportunities related to the intersection of VA and PM - The role of AI in PM, and how Visualization and explainable-AI solutions can support model comprehension, exploration, and refinement Paper Submission and Format Guidelines -------------------------------------- We will accept short papers with up to 5 pages plus one page of references (5 + 1). We encourage a diverse range of submissions and demonstrations in any of the short paper types listed below: - Application/Case-study papers (format: 5 + 1) - Research papers (format: 5 + 1) - Position papers and system demos papers (format: 2 + 1) All material will be submitted via the Precision Conference System (PCS): https://new.precisionconference.com/submissions For all submissions, please use the EuroVis 2024 LateX2e Style. On Overleaf, this template can be imported easily by selecting "New Project" -> "Upload Project" and uploading the zip file. Use EGAuthorGuidelines-eurovis24-short.tex for your submission: https://medialib.cmcdn.dk/medialibrary/80234312-1C55-406C-86A7-410099EB2739… Contact vipra.workshop at gmail.com if you have any questions or visit https://vipra-workshop.github.io/homepage/ Important Dates --------------- - Deadline for submission: March 1st, 2024 - Notification of acceptance: April 12th, 2024 - Camera-ready papers due: April 26th, 2024 - Vipra 2024 Workshop: May 27th, 2024 (in conjunction with EuroVis 2024) All submission deadlines are at 23:59 GMT on the date indicated. Organizers ---------- Alessio Arleo, TU Wien Stef van den Elzen, Eindhoven University of Technology Tatiana von Landesberger, Universität Köln Luise Pufahl, TU München - Heilbronn Jana-Rebecca Rehse, Universität Mannheim Francesca Zerbato, Universität St. Gallen

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Discord-Server (Zweite Aussendung)
by Johanna Schmidt 04 Dec '23

04 Dec '23

Liebe Mitglieder*Innen, für die neuen Mitglieder, und falls jemand von Euch die letzte Aussendung verpasst hat, hier ein Einladungslink für unseren Discord-Server: https://discord.gg/3efthBMg (7 Tage gültig) Nur zur Erinnerung, die Sprecher haben im letzten Fachgruppenmeeting beschlossen, dass wir Discord für eine direktere Kommunikation unter den Mitgliedern und dem Leitungsgremium verwenden werden. Falls es Ideen/Wünsche für weitere Channels gibt, bitte gerne an uns wenden! Wir werden laufende Neuigkeiten auf Discord und auch nach wie vor via Email verbreiten. Liebe Grüße, Johanna Schmidt Lars Linsen Daniel Weiskopf --

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Kommunikationskanal: Discord
by Johanna Schmidt 04 Dec '23

04 Dec '23

Liebe Mitglieder*Innen, die Sprecher haben im letzten Fachgruppenmeeting beschlossen, dass wir Discord für eine direktere Kommunikation unter den Mitgliedern und dem Leitungsgremium verwenden werden. Wir haben nun dafür einen Discord-Server aufgesetzt. Einige von euch habe ich direkt in Discord eingeladen (so bereits ein Account vorhanden war), hier aber noch einmal für alle der Einladungslink: https://discord.gg/vYWEnfJ5 (7 Tage gültig) Wir haben einen allgemeinen Kommunikationskanal und einen für das Leitungsgremium eingerichtet. Falls es Ideen/Wünsche für weitere Channels gibt, bitte gerne an uns wenden! Wir werden laufende Neuigkeiten auf Discord und auch nach wie vor via Email verbreiten. Wir freuen uns auf die Diskussionen mit euch! Liebe Grüße, Johanna Schmidt Lars Linsen Daniel Weiskopf -- Dr. Johanna Schmidt Head of Visual Analytics Group VRVis Forschungs-GmbH,www.VRVis.at, FN: 195369h, HG Wien mail:johanna.schmidt@vrvis.at tel +43(0)1 9089892 302

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[Funded PhD Position] ViSual ANalytics for Event-based Diffusion on Networks @ TU Wien f/m/d (30-40h) [DL: December 8, 2023]
by Miksch Silvia 27 Nov '23

27 Nov '23

** FUNDED PHD POSITION AT TU VIENNA ** We are hiring a talented PhD candidate in an international project on the visual analytics of complex diffusion processes over temporal networks. You will work in the context of SANE, a project held by TU Vienna (Austria), the University of Cologne (Germany) and the University of Newcastle (United Kingdom). This project arrangement gives you unique career opportunities, including student exchanges abroad, regular meetings with researchers from the other institutions participating to the project. We are looking for a PhD candidate to work from the TU Wien, at the Institute of Visual Computing and Human-Centered Technology, in the Research Unit of Visual Analytics. We offer a position as project assistant (prae-doc) limited to 3 years for 30 hours/week (that can be extended to 40). Gross annual (monthly) salary of Euro 43,650 (2,464.80) according to FWF regulations. In this position, you will begin your doctoral journey studying problems related to the topic of event-based network visualization. In Event-based (also known as “temporal”) networks, In Event-based (also known as “temporal”) networks, the time coordinates where the nodes and the edges are “active” are an explicit element of the representation, differently from traditional timeslicing where a time structure is imposed over the input data. You will apply these concepts to the problem of Information Diffusion. Information Diffusion studies how “information” flows and spreads through an underlying network, and has been used to model, simulate, and predict natural and human-made phenomena in countless different domains (e.g., pathogen spread, malware outbreak in computer networks, viral marketing, etc.). However, little research has been done on this problem within the context of visualization. Wanna know more? Check the project description and complete job posting at https://www.cvast.tuwien.ac.at/projects/sane *** Deadline for applications: 8 December 2023 *** Expected start: January 2024 Questions? You can reach me at alessio.arleo(a)tuwien.ac.at <mailto:alessio.arleo@tuwien.ac.at> ================================================================ Alessio Arleo, Ph.D. Vienna University of Technology (TU Wien) Faculty of Informatics Institute of Visual Computing & Human-Centered Technology Favoritenstrasse 9-11 /193-07 A-1040 Vienna, Austria, Europe email: alessio.arleo(a)tuwien.ac.at url: https://alessioarleo.com phone: +43-1-58801-188211 =================================================================

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Antw: [EXT] Protokoll Fachgruppentreffen 2023 (out-of-office message)
by Dorit Merhof 01 Nov '23

01 Nov '23

I am out of the office until 8th November without email contact. I'll respond to your message after my return. In case of emergency, please contact Nicole Kerscher (email: nicole.kerscher(a)ur.de) Best regards, Dorit Merhof

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