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Fwd: [insuplee_group] PRECISE Seminar (this Thursday 2/8 @noon): Michele Caprio, Ph.D.
by Michele Caprio Feb. 7, 2024

Feb. 7, 2024

Dear SIPTians, For those of you who are interested in the relationship between Machine Learning and IPs, I'll be giving a talk tomorrow at 12 noon EST. You can find the zoom link in the forwarded email below. Hope to see you there! Yours, Michele ---------- Forwarded message --------- From: Wai-Ping Ng <wng(a)seas.upenn.edu> Date: Mon, Feb 5, 2024 at 7:34 PM Subject: [insuplee_group] PRECISE Seminar (this Thursday 2/8 @noon): Michele Caprio, Ph.D. To: Wai-Ping Ng <wng(a)seas.upenn.edu> *|MC_PREVIEW_TEXT|* View this email in your browser PRECISE Center presents Michele Caprio, Ph.D. Postdoc, University of Pennsylvania Imprecise Probabilities Machine Learning Thursday, 8 February 2024 Noon - 1 pm 3330 Walnut Street Levine Hall Room 307 Philadelphia, PA 19104 For remote attendees, please use this <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…> link. ABSTRACT In this talk, I will present Imprecise Probabilities (IPs), from their historic philosophical motivations to their applications to frequentist and Bayesian statistics. In turn, I will explore how the statistical approaches to IPs allowed to start the field of Imprecise Probabilistic Machine Learning, and why such a field is of paramount importance in modern ML. I will provide plenty of references, together with some new results on the comparison between Conformal Prediction and Imprecise Probabilistic Machine Learning, and how the latter can be used to derive regions that are narrower than the conformal ones, while retaining the same probabilistic guarantees. BIO Michele Caprio is a Postdoc at the PRECISE Center <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…> of the University of Pennsylvania <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…>, under the guidance of Prof. Insup Lee <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…>. He is an incoming Lecturer (Assistant Professor) in Machine Learning at the Department of Computer Science <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…> of the University of Manchester <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…>. He is also part of the Manchester Centre for AI Fundamentals <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…>, and an incoming Supervisor at the UKRI AI Center for Doctoral Training <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…> in Decision Making for Complex Systems. His main research interests are Uncertainty Quantification in AI and ML, Probabilistic ML, and Imprecise Probabilities. In 2023, he won the IJAR Young Researcher Award <https://urldefense.com/v3/__https://us18.mailchimp.com/mctx/clicks?url=http…>, a prize awarded every two years to a young scholar who demonstrates excellence in research at an early stage of the scientific career. _______________________________________________ insuplee_group mailing list insuplee_group(a)lists.seas.upenn.edu https://lists.seas.upenn.edu/mailman/listinfo/insuplee_group

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SIPTA school 2024: website online and registrations open
by Floris Persiau Feb. 7, 2024

Feb. 7, 2024

To all interested researchers, young(er) and old(er),We’re happy to announce that we’ve finalised the programme of the 11th SIPTA School, and that it can be found on the school’s recently launched website: https://school24.sipta.org/. We recall from our previous mail that the school’s aim is to introduce doctoral students – and other interested researchers – to the basics of imprecise probabilities, from its foundations in (applied) mathematics and logic to its applications in quantum physics, economy and AI. More information on the full programme, the lecturers, etc. can of course be found on the school’s website.DATE AND LOCATION The SIPTA School 2024 takes place from Monday 12 to Friday 16 August 2024 in the wonderful city of Ghent, Belgium,REGISTRATION The registration portal is open as of today. For doctoral students at a Flemish University, the registration fee is € 0 and the deadline for registration is 30 June 2024. For all other participants, the registration fee depends on the moment of registration. There is an early bird fee of € 100, which requires you to register before 15 April 2024. After this deadline, a late bird fee of € 125 will apply, and the deadline for registration is 30 June 2024 as well. All fees include admission to the lectures, lunches, coffee breaks, a pizza night and a kayak session. Moreover, we also provide you with the option to hire a private room for the duration of the summer school, which comes at a cost of € 330. If you want to make use of this option, then you must register before 15 April 2024.GRANTS We can distribute 5 grants to students who experience financial barriers to attending the summer school. In addition to waiving the registration fee, every grant provides free accommodation, and covers (part of) your transport costs up to € 250. The deadline for application is 10 April 2024; more information on how to apply for these grants can be found in the Registration section of the school’s website.We look forward to welcoming and meeting you in Ghent!Please spread the word!With kind regards,Floris Persiau and Alexander Erreygers

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CfP of TX4Nets
by Cristina Rottondi Feb. 6, 2024

Feb. 6, 2024

Dear SIPTA members, I take the liberty to disseminate the CfP of the first edition of the Workshop on Trustworthy and eXplainable Artificial Intelligence for Networks (TX4Nets), co-located with IFIP Networking 2024. Contributions on uncertainty quantification with applications to the field of telecommunication networks are welcome. Best regards, Cristina Rottondi *** Please accept our apologies if you receive multiple copies of this call for paper*** ------------------- 1st International Workshop on Trustworthy and eXplainable Artificial Intelligence for Networks (TX4Nets) co-located with IFIP Networking 2024<https://networking.ifip.org/2024/index.php/> Thessaloniki, Greece, 3-6 June 2024 Link to the official workshop website: https://sites.google.com/view/tx4nets2024 ------------------- *** TX4Nets 2024 CALL FOR PAPER *** link to CFP: https://sites.google.com/view/tx4nets2024/call-for-papers Aim and Scope In light of next communication networks characterized by zero-touch network management, network operators have started the deployment of automated AI-based frameworks addressing various use cases including resource allocation, failure prediction and identification, traffic prediction. However, these deployments predominantly function as black boxes, with practitioners unable to comprehend the internal reasoning or decision processes of these automated AI-based frameworks. In this context, eXplainable Artificial Intelligence (XAI) emerges as a promising collection of frameworks and technologies designed to enhance the transparency of black-box models. XAI achieves this by providing explanations for the decisions made, enabling practitioners to eliminate bias influencing models, understand when to trust or distrust model decisions, and gain insights into the problem at hand. In addition to this, it also becomes of paramount importance to design and adopt models and methods that are inherently able to quantify their uncertainty in taking decisions based on conformal prediction. This, in turn, facilitates a reliable and Trustworthy deployment of machine learning and Artificial Intelligence models. While the application of Trustworthy and Explainable Artificial Intelligence has been extensively explored in diverse domains such as healthcare and finance, its implementation in communication networks has been relatively sparse, despite being considered of paramount importance. This workshop seeks to address this gap by shedding light on the potential applications of Trustworthy and Explainable AI in achieving transparent AI-based automation for networking. The primary objective of the workshop is to foster collaboration among AI/ML and telecom engineers, facilitating the sharing and exchange of experiences and ideas related to all aspects of trustworthy and explainable AI for network management. Topics of Interest The topics of interest for TX4Nets 2024 include, but are not limited to: * XAI for Model Trustworthiness in Networks * XAI for Trustworthy Network management * XAI-driven Network Performance Optimization * Trustworthiness in AI Models for Communication Networks * XAI for trustworthy AI in Optical, Wireless, Microwave, B5G/6G Networks * XAI for Optical, Wireless, or Microwave Networks * XAI for Autonomous Networks * XAI for Zero Touch Networks * XAI for the Edge/Cloud and Internet-of-Things * XAI for network security, privacy, resilience, reliability, and safety * XAI Applied to Networking * XAI Applied to Network Management * XAI applied to Failure Management * Security and Explainability in AI for Communication Networks * Reliability and Explainability in AI for Communication Networks * Human-in-the-Loop Systems for AI in Communication Networks * Fair Federated Learning for Communication Networks * Fair AI-based Resource Allocation in Communication Networks * Model Uncertainty Quantification and Explainability for Communication Networks * Model Uncertainty Quantification and Explainability for Network Security * Conformal Predictions Applied to Communication Networks * Impact of Adversarial Attacks on Communication Networks AI Model Trustworthiness * Case Studies and Deployments of XAI in Communication Networks * XAI for Open RAN in 6G Networks * AI for trustworthy IoT and Autonomous System Applications * Ethical Considerations in AI for Communication Networks * Interoperability and Standards in AI for Communication Networks * Regulatory Landscape for AI in Communication Networks * New Business Models for XAI * Explainable Reinforcement Learning in Communication Networks * Causal Machine Learning for Networking * Causal Reinforcement Learning for Networking * XAI for federated learning-based solutions of 5G/6G and future networks * XAI for transfer learning-based solutions of 5G/6G and future networks * XAI for digital twin-based solutions of 5G/6G and future networks Important Dates Paper Submission: March 27, 2024 Notification of Acceptance: April 27, 2024 Camera-ready Submission: May 2, 2024 Workshop Date: 3 June 2024 (tentative) Paper Submission Authors are invited to submit original contributions that have not been published nor has been submitted for publication elsewhere. Papers should be prepared using the IEEE double-column conference style (10pt font) and are limited to 6 pages including references. Papers must be submitted electronically in PDF format on EDAS through this link: https://www.edas.info/newPaper.php?c=31469&track=123080 All papers will be peer reviewed and the comments will be provided to the authors. Once accepted, the paper will be included in the conference proceedings and will be eligible for submission to the IEEE Xplore Digital Library. At least one author of each accepted paper is required to register and present the work in the workshop. Further information can be found on the official website of TX4Nets 2024: https://sites.google.com/view/tx4nets2024 Workshop Organizers Cristina Rottondi, Politecnico di Torino, Italy Marco Savi, University of Milano-Bicocca, Italy Omran Ayoub, University of Applied Sciences of Southern Switzerland, Switzerland Tania Panayiotou, University of Cyprus, Cyprus Sebastian Troia, Politecnico di Milano, Italy

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Special session on imprecise probabilities at SMPS 2024
by Van Camp, Arthur Feb. 2, 2024

Feb. 2, 2024

Call for papers Special Session on THEORETICAL AND APPLIED ASPECTS OF IMPRECISE PROBABILITIES to be held at the 11th International Conference on Soft Methods in Probability and Statistics (SMPS 2024) http://www.smps2024.com<%22> Salzburg (Austria), September 4-6, 2024 Session topic and goal This session is devoted to Imprecise Probability Theory. This theory involves all the mathematical models that can be used as more flexible tools than usual Probability Theory when the available information is scarce, vague or incomplete. It includes lower previsions, n-monotone capacities, belief functions, possibility measures, or non-additive measures, among others. This special session aims to include papers related to Imprecise Probabilities that either present a significant advance in the foundations or show potential applications in real problems. In addition, papers where the connection between imprecise probability theory and other fields such as fuzzy sets or game theory is emphasized are also welcome. Theoretical topics of interest include (but are not limited to): • (coherent) uncertainty models • non-additive set functions • choice functions • sets of desirable gambles • qualitative reasoning about uncertainty • limit laws for imprecise probabilities • philosophical foundations • elicitation and inference • robust statistics • decision making • algorithmic issues Applications include (but are not limited to): • data mining • classification and machine learning • risk and reliability analysis • finance • life sciences • system control and design Dates Paper submission deadline: February 29, 2024 Author notification: April 21, 2024 Conference: September 4-6, 2024 Submissions Please select the Invited Session “Theoretical and applied aspects of imprecise probabilities” when submitting your paper in the conference management tool www.conftool.net/smps2024/<http://www.conftool.net/smps2024/>. Papers submitted should be between 6 and 8 pages. Required LaTeX style etc., a link to the submission platform, and additional information can be found on the conference homepage www.smps2024.com<http://www.smps2024.com>. Elsevier will sponsor SMPS 2024 with a best paper award of €1000. Additionally, there will be a special issue related to the conference in the International Journal of Approximate Reasoning. Organizers We would be obliged if you would let us know in case you intend to submit a paper to this session, at your earliest convenience. Any questions or remarks can be addressed to: Arthur Van Camp (a.van.camp(a)tue.nl<mailto:a.van.camp@tue.nl>), Eindhoven University of Technology (The Netherlands) Enrique Miranda (mirandaenrique(a)uniovi.es<mailto:mirandaenrique@uniovi.es>), University of Oviedo (Spain)

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Re: IMEKO 2024 World Congress - Deadline extended!
by Kreinovich, Vladik Jan. 31, 2024

Jan. 31, 2024

FYI, IMEKO 2024 XXIV World Congress of the International Measurement Confederation IMEKO,<https://www.imeko2024.org/> Hamburg, Germany, August 26-29, 2024, https://www.imeko2024.org/home measurement-related papers that use imprecise probabilities are always welcome at this series of conferences From: haide.Borrmann(a)ptb.de<mailto:haide.Borrmann@ptb.de> <haide.Borrmann(a)ptb.de<mailto:haide.Borrmann@ptb.de>> On Behalf Of imeko2024(a)ptb.de<mailto:imeko2024@ptb.de> Sent: Wednesday, January 31, 2024 6:19 AM [cid:image001.gif@01DA5433.D0B99720] Organizing Committee Secretariat WC2024 Physikalisch-Technische Bundesanstalt Bundesallee 100 D-38116 Braunschweig E-Mail: imeko2024(a)ptb.de<mailto:imeko2024@ptb.de> https://www.imeko2024.org/

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FW: Call for abstracts for ISRERM 2024
by Kreinovich, Vladik Jan. 31, 2024

Jan. 31, 2024

FYI, imprecise probabilities are one of the highlighted topics From: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> <beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de>> Sent: Monday, January 29, 2024 9:35 AM [Institute for Risk and Reliability Logo] [University of Hannover Logo] Call for abstracts for ISRERM 2024 [https://cossan.irz.uni-hannover.de/uploadimages/image/Header.png] Dear Colleague, It's our pleasure to invite you to submit an abstract to the International Symposium on Reliability Engineering and Risk Management (ISRERM) to be held at Hefei University of Technology, China, from October 18th to 21st, 2024. Please also take a look at several mini-symposia. The detailed description of the these mini-symposiums can be found here<http://cossan.irz.uni-hannover.de/lists/lt.php?tid=KkpfVQRSBlcGWR8FDANXSQwO…> as well as below. The International Symposium on Reliability Engineering and Risk Management (ISRERM) is a significant biennial international conference that serves as a pivotal platform for the exchange of knowledge and innovative applications in the fields of reliability-based, risk-based, and uncertainty-informed decision making. Its primary focus lies in addressing safety-related aspects throughout the entire lifecycle of engineering systems. Over the years, ISRERM has garnered international recognition, with a rich history of hosting conferences at esteemed institutions worldwide. Past symposiums have been hosted at prestigious locations such as Tongji University, Shanghai, China (2008, 2010), Kanagawa University, Yokohama, Japan (2012), Taiwan University of Science & Technology, Chinese Taipei (2014), Yonsei University, Seoul, South Korea (2016), National University of Singapore, Singapore (2018), Beijing University of Technology, China (2020), and Leibniz University Hannover, Germany (2022). It is with great excitement that we announce the forthcoming 9th ISRERM, scheduled to be held at Hefei University of Technology, China, from October 18th to 21st, 2024. ISRERM serves as a platform fostering interdisciplinary dialogue on reliability assessment, risk and uncertainty quantification, mitigation, and management, as well as effective decision-making strategies. Our primary objective is to bridge the knowledge gaps among diverse disciplines grappling with similar challenges and to transform scholarly discussions into strong frameworks for dealing with emerging reliability and risk management problems. The deadline for the abstract submission is February 29, 2024. The official registered submission website is as follows: https://isrerm2024.aconf.org<https://isrerm2024.aconf.org/> 1. If you are visiting this page for the first time, please create a new profile by clicking on the homepage "Sign up". Once the profile has been created, it is possible to access your profile again at any time, by entering your email and password. 2. Please log in to fill in and save your personal information ("Dashboard" → “My Profile"). Next click the “Downloads” tab on the left side of homepage to download the template file of the abstract (ISRERM_2024_Abstract_templates.zip). 3. Submit the abstract in the submission area. You can get to the submission area through the “Submission” tab on the left side of homepage. Information about Registration, Exhibition, and Sponsorship opportunities will be made available soon. Please visit regularly the symposium website for news and updates. If you have any question, please feel free to contact the organizers via the following e-mail address: isrerm2024(a)hfut.edu.cn<mailto:isrerm2024@hfut.edu.cn> With warm regards Yours sincerely Jie Li, Conference Chair, Academician of CAS, EASA, University Distinguished Chair Professor, Tongji University Jingfeng Wang, Chair of Local Organizing Committee, Professor, Hefei University of Technology Lunhai Zhi, Co-Chair of Local Organizing Committee, Professor, Hefei University of Technology Yongbo Peng, Co-Chair of Local Organizing Committee, Professor, Tongji University ISRERM 2024 Secretariat Hefei University of Technology Hefei 230009, China Email: isrerm2024(a)hfut.edu.cn<mailto:isrerm2024@hfut.edu.cn> Website: https://isrerm2024.aconf.org<https://isrerm2024.aconf.org/> ________________________________ MS03: Uncertainty Modeling and Quantification for Model Updating and Structural Health Monitoring Abstract: Structural Health Monitoring (SHM) aims at condition assessment and service life monitoring of structural systems, often based on the availability of system vibration data. Model updating has been developed as a key technique for SHM, where the parameters or the numerical model itself are calibrated to tune the model prediction close to the actual system behaviour. However, uncertainties are inevitable in both the measuring and modeling processes, which leads to the necessity of non-deterministic approaches to modeling and quantifying the uncertainties. This Mini-Symposium is dedicated to gathering experts from both academia and industries to showcase the latest advances on the uncertainty treatment in model updating and SHM and their practical applications. * Topics for potential contributions include but are not limited to: * Stochastic/interval model updating; * Inverse quantification of mixed aleatory and epistemic uncertainty; * On-line model updating for nonlinear dynamic systems; * Model updating and SHM applications in large-scale structures. MS03 Organizers: * Masaru Kitahara, The University of Tokyo, Tokyo, Japan. E-mail: kitahara(a)bridge.t.u-tokyo.ac.jp<mailto:kitahara@bridge.t.u-tokyo.ac.jp> * Michael Beer, Leibniz University Hannover, Hannover, Germany. E-mail: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> * Siu-Kui Au, Nanyang Technological University, Singapore, Singapore. E-mail: ivanau(a)ntu.edu.sg<mailto:ivanau@ntu.edu.sg> * Takeshi Kitahara, Kanto Gakuin University, Yokohama, Japan. E-mail: kitahara(a)kanto-gakuin.ac.jp<mailto:kitahara@kanto-gakuin.ac.jp> ________________________________ MS05: Stochastic finite element methods and their applications on model updating Abstract: Stochastic finite element method is an important tool widely used in many aspects such as reliability analysis, safety assessment and model updating et al. At present, various stochastic finite element methods have been developed. As typical representatives among these methods, the perturbation methods and the Garlekin based methods like PC and GPC, have been successfully applied to solve the stochastic problems in extensive industrial fields. However, highly accurate and efficient stochastic finite element methods are still developing to implement the stochastic analysis of large-scale structural models. This research direction has been attracting many researchers’ attention. Model updating is a key content in structural health monitoring. When considering the randomness of structural modelling and measurement data, the stochastic model updating becomes unavoidable. To solve stochastic model updating problems, the stochastic finite element methods can play a significant role instead of the usually used Bayesian methods. This direction is a hot topic in current structural model updating, which has a very good application prospect in practical structural health monitoring. The symposium aspires to create a conducive environment for scholars, researchers, and practitioners to exchange insights and findings, fostering collaborative endeavors and innovations in the domain of stochastic finite element method. The inclusion of diverse theoretical explorations and practical applications is anticipated to provide a comprehensive perspective on the evolving role of stochastic finite element method to address the inverse problem in health monitoring. Topics for potential contributions include but are not limited to: * Recent advances in stochastic finite element method. * Advanced computational techniques in Stochastic Static and Dynamics. * Recent mathematical and numerical developments in stochastic structural engineering static and dynamics. * New surrogate modeling techniques tailored to some computationally-demanding problems. * Stochastic finite element method in reliability analysis, safety assessment. * Stochastic model updating. * Model update with structural health monitoring. * Engineering practice of structural health monitoring accommodating uncertainties. * Novel uncertainty quantification techniques in model updating. * Data-driven approaches for model updating. MS05 Organizers: * Prof. Dr. Bin Huang, Wuhan university of technology, Wuhan, China. E-mail: binhuang(a)whut.edu.cn<mailto:binhuang@whut.edu.cn> * Dr. Heng Zhang, Yangtze University, Jinzhou, China. E-mail: supzhangheng(a)163.com<mailto:supzhangheng@163.com> * Dr. Hui Chen, College of Post and Telecommunication, Wuhan Institute of Technology, Wuhan, China. E-mail: huichenvip(a)163.com<mailto:huichenvip@163.com> * Dr. Zhifeng Wu, Huazhong University of Science and Technology, Wuhan, China. E-mail: wuzhifeng(a)hust.edu.cn<mailto:wuzhifeng@hust.edu.cn> * Prof. Dr. Michael Beer, head of Institute for Risk and Reliability, Leibniz Universität Hannover (LUH), Germany. E-mail: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> * Prof. Sifeng Bi, University of Strathclyde, Glasgow, United Kingdom. E-mail: sifeng.bi(a)strath.ac.uk<mailto:sifeng.bi@strath.ac.uk> ________________________________ MS08: Data-driven and Uncertainty-aware Modeling of Complex and Nonlinear Systems Abstract: The recent years have seen significant progress in modeling complex and nonlinear systems, with a notable shift towards data-driven methodologies and a heightened recognition of the inherent uncertainties associated with such systems. Non-deterministic modeling approaches, including probabilistic, interval, fuzzy, or imprecise methods, necessitate accurate specification of uncertain model parameters. However, direct measurement of these quantities is often impractical or cost-prohibitive, leading to the widespread application of data-driven and uncertainty-aware modeling techniques. This mini-symposium aims to bring together experts, researchers, and practitioners from academia and industry to explore and discuss the latest developments, methodologies, and applications related to data-driven modeling and the incorporation of uncertainty-aware techniques in understanding complex and nonlinear systems. Papers discussing advances in techniques from both uncertainty forward and inverse propagation by probabilistic theory, as well as interval methods and concepts based on imprecise probabilities are invited. Next to these non-deterministic and data-driven approaches for numerical modelling, stochastic model updating, system identification, damage localization, sensor placement optimization is highly welcomed. Topics for potential contributions include but are not limited to: * Stochastic model updating * Highly efficient uncertainty propagation * Quantification of multiple uncertainty sources * Data-driven modelling * Imprecise probability * System identification * Sensor placement optimization * Digital twin MS08 Organizers: * Yanlin Zhao, University of Science and Technology Beijing, Beijing, China. E-mail: zhaoyanlin(a)ustb.edu.cn<mailto:zhaoyanlin@ustb.edu.cn> * Yongtao Bai, Chongqing University, Chongqing, China. E-mail: bai.yongtao(a)cqu.edu.cn<mailto:bai.yongtao@cqu.edu.cn> * Sifeng Bi, University of Strathclyde, Glasgow, United Kingdom. E-mail: Sifeng.bi(a)strath.ac.uk<mailto:Sifeng.bi@strath.ac.uk> * Michael Beer, Leibniz University Hannover, Hannover, Germany. E-mail: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> * David Moens, Katholieke Universiteit Leuven, Leuven, Belgium. E-mail: david.moens(a)kuleuven.be<mailto:david.moens@kuleuven.be> ________________________________ MS09: Addressing Aleatoric and Epistemic Uncertainty with Imprecise Probabilities Abstract: Uncertainties appearing in engineering problems can be broadly classified as aleatoric and epistemic. The first group refers to intrinsic uncertainty stemming out of randomness, while the latter reflects lack of knowledge, conflicting sources of information, etc. One possibility for tackling such class of problems is resorting to imprecise probabilities which, in essence, can be interpreted as a collection of classical probabilistic models that account for aleatoric uncertainty and which are indexed by, e.g. interval variables that capture epistemic uncertainty. Although imprecise probabilities offer an extremely wide and flexible framework, its practical deployment is not devoid of challenges. Therefore, the aim of this MS is bringing together some of the latest developments on imprecise probabilities, including (but not limited to): * Different models for representing uncertainty such as, e.g. p-boxes, imprecise stochastic processes, distribution-free models, etc. * Novel formulations for coping with aleatoric and epistemic uncertainty, such as advanced simulation methods; surrogate models, etc. * Inverse uncertainty quantification in the presence of aleatoric and epistemic uncertainty. * Practical applications involving challenging engineering problems. MS09 Organizers: * Marcos Valdebenito, TU Dortmund University, Germany, marcos.valdebenito(a)tu-dortmund.de<mailto:marcos.valdebenito@tu-dortmund.de> * Michael Beer, Leibniz University Hannover, Germany. E-mail: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> * Matthias Faes, TU Dortmund University, Germany. E-mail: matthias.faes(a)tu-dortmund.de<mailto:matthias.faes@tu-dortmund.de> * Zhan Kang, Dalian University of Technology, China. E-mail: zhankang(a)dlut.edu.cn<mailto:zhankang@dlut.edu.cn> * Chao Jiang, Hunan University, China. E-mail: jiangc(a)hnu.edu.cn<mailto:jiangc@hnu.edu.cn> ________________________________ MS14: Global Reliability Analysis of Complex Nonlinear Stochastic Dynamical Systems Abstract: The study of complex nonlinear stochastic dynamical systems is of paramount importance in both science and engineering. These systems exhibit a myriad of uncertainties, stemming from various sources such as material properties, external excitations, and inherent nonlinearities. These uncertainties introduce significant ambiguity into the response of systems, making precise analysis and design a formidable challenge. The coupling of nonlinearity and stochasticity necessitates a refined understanding of uncertainty propagation, which is indispensable for ensuring the safety and reliability of engineering systems. This symposium invites you to contribute to the discussion on the complexities of global reliability analysis in engineering structures. We welcome contributions that address, but are not limited to, the following themes: * Novel approaches for modeling and analyzing complex nonlinear systems subjected to stochastic influences. * Techniques for addressing the safety challenges associated with high-dimensional uncertainty inputs in engineering systems. * Methods to assess the propagation of stochastic effects in high-degree-of-freedom nonlinear systems. * Exploration of reliability analysis in emerging dynamic systems, such as those involving fractional-order differentiation or negative stiffness mechanisms. * Development of efficient and accurate methods for advanced global reliability assessment in complex systems. * Leveraging surrogate models and machine learning approaches to enhance reliability analysis in nonlinear stochastic dynamical systems. * Innovative strategies that combine physical understanding with data-driven approaches for more robust reliability analysis. * Techniques for precisely assessing low failure probabilities under rare events, critical in high-consequence systems. * Effective and efficient reliability methods in the context of reliability-based design optimization of complex nonlinear stochastic dynamical systems. * optimization of complex nonlinear stochastic dynamical systems. * We strongly encourage and warmly welcome contributions that address real-world applications and propose pioneering theories within disciplines such as civil engineering, aerospace engineering, construction engineering, mechanical engineering, energy engineering, automotive engineering, and other relevant fields. MS14 Organizers: * Meng-Ze Lyu, Tongji University, Shanghai, China. E-mail: lyumz(a)tongji.edu.cn<mailto:lyumz@tongji.edu.cn> * Jian-Bing Chen, Tongji University, Shanghai, China. E-mail: chenjb(a)tongji.edu.cn<mailto:chenjb@tongji.edu.cn> * Michael Beer, Leibniz Universität Hannover, Hannover, Germany. E-mail: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> * Hector Jensen, Universidad Técnica Federico Santa María, Valparaíso, Chile. E-mail: hector.jensen(a)usm.cl<mailto:hector.jensen@usm.cl> ________________________________ MS24: Quantification and Propagation of Uncertainties in Stochastic Dynamics: Computational Challenges and Solutions Abstract: This mini-symposium is dedicated to exploring the computational challenges of modeling uncertainties in dynamical systems and loads, with a particular focus on improving the assessment of structural reliability. The symposium will address various dimensions of uncertainty, including stochastic excitations, structural reliability, and the sophisticated task of accounting for uncertainties in input load modeling. The aim is to highlight the use of advanced computational techniques that play a central role in improving the accuracy and reliability of dynamical system models. It provides a platform for the exchange of insights and strategies between researchers and facilitates a comprehensive understanding of the complexity involved in dealing with uncertainties. The topics to be discussed include, but are not limited to: This mini-symposium invites researchers to contribute their expertise and insights to enhance collaborative discussions that improve the understanding and application of computational methods in the treatment of uncertainties in stochastic dynamics. * Reliability of structural systems: Exploring methods and concepts for assessing and improving the reliability of structural systems under dynamic conditions. * Stochastic excitations: Exploring the effects of stochastic excitations on dynamical systems and discussing methods to seamlessly incorporate uncertainties into modeling frameworks. * Accounting for uncertainties: Exploring strategies for robust consideration of uncertainties, with a focus on practical applications and implications for structural analysis. * Advanced computational techniques: Emphasizing the role of advanced computational techniques in mitigating the computational challenges posed by dynamical systems with uncertainties. This mini-symposium invites researchers to contribute their expertise and insights to enhance collaborative discussions that improve the understanding and application of computational methods in the treatment of uncertainties in stochastic dynamics. MS24 Organizers: * Marco Behrendt, Leibniz Universität Hannover, Hannover, Germany. E-mail: behrendt(a)irz.uni-hannover.de<mailto:behrendt@irz.uni-hannover.de> * Meng-Ze Lyu, Tongji University, Shanghai, China. E-mail: lyumz(a)tongji.edu.cn<mailto:lyumz@tongji.edu.cn> * Jian-Bing Chen, Tongji University, Shanghai, China. E-mail: chenjb(a)tongji.edu.cn<mailto:chenjb@tongji.edu.cn> * Michael Beer, Leibniz Universität Hannover, Hannover, Germany. E-mail: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> ________________________________ MS31: Uncertainty quantification in wind engineering Abstract: The field of wind engineering plays a pivotal role in ensuring the safety and resilience of structures against the dynamic wind forces. However, the inherent uncertainty associated with both the extreme wind loads and structural dynamic behaviors pose a significant challenge to accurate and reliable structural design. Illustrative instances of these uncertainties include the stochastic nature of wind excitations, challenges in accurately estimating the wind power spectrum, and uncertainties in structural aerodynamics. By bringing together researchers, practitioners, and industry professionals, this mini-symposium aims to foster collaboration and innovation in the pursuit of more robust and resilient wind engineering practices. Topics for potential contributions include but are not limited to: * Probabilistic Models: Presentations will delve into the development and application of probabilistic models to characterize the uncertainty in wind loads. Discussions will focus on incorporating meteorological data, turbulence models, and environmental factors into probabilistic frameworks; * Data-Driven Approaches: This session will explore innovative data-driven methods for uncertainty quantification, leveraging machine learning and big data analytics to enhance the accuracy of wind load predictions. Case studies highlighting the practical implementation of these approaches will be emphasized; * Sensitivity Analysis: Understanding the sensitivity of structures to uncertain parameters is crucial. This segment will cover sensitivity analysis techniques, assessing the impact of varying wind conditions, structural configurations, and terrain features on the overall uncertainty; * Industry Perspectives: Experts from both academia and industry will share insights into the practical implications of uncertainty quantification in wind engineering. Presentations will address real-world challenges faced by engineers and showcase successful applications of uncertainty-aware design. MS31 Organizers: * Xu Hong, Hefei University of Technology, Hefei, China. E-mail: xhong(a)hfut.edu.cn<mailto:xhong@hfut.edu.cn> * Genshen Fang, Tongji University, Shanghai, China. E-mail: 2222tjfgs(a)tongji.edu.cn<mailto:2222tjfgs@tongji.edu.cn> * Zhiqiang Wan, Northwestern Polytechnical University, China, E-mail: wanzhiqiang(a)nwpu.edu.cn<mailto:wanzhiqiang@nwpu.edu.cn> * Lunhai Zhi, Hefei University of Technology, Hefei, China. E-mail: zhilunhai1979(a)163.com<mailto:zhilunhai1979@163.com> * Michael Beer, Leibniz University Hannover, Germany, E-mail: beer(a)irz.uni-hannover.de<mailto:beer@irz.uni-hannover.de> * Seymour M.J. Spence, University of Michigan, US, E-mail: smjs(a)umich.edu<mailto:smjs@umich.edu> ________________________________ Institute for Risk and Reliability Callinstr. 34 30167 Hannover Germany www.irz.uni-hannover.de<http://cossan.irz.uni-hannover.de/lists/lt.php?tid=KkoHCVFSAAdXCh9VCAIGSQwC…> To forward this message, please do not use the forward button of your email application, because this message was made specifically for you only. Instead use the forward page<http://cossan.irz.uni-hannover.de/lists/lt.php?tid=KkoHAlBWUAIFWR8AWFUISQwE…> in our newsletter system. powered by phpList<http://cossan.irz.uni-hannover.de/lists/lt.php?tid=KkpWCAUBBAVSDR8BXQAFSQwP…>

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Next SIPTA Seminar: 31st January at 3pm Paris Time
by sdesterc Jan. 29, 2024

Jan. 29, 2024

Dear colleagues, We are delighted to announce our upcoming SIPTA online seminar on imprecise probabilities (IP). These monthly events are open to anyone interested in IP, and will be followed by a Q&A and open discussion. They also provide an occasion for the community to meet, keep in touch and exchange between in-person events. The next seminar will take place on the 31st of January (Wednesday). The zoom link for this seminar is https://utc-fr.zoom.us/j/86165930800 For this new seminar, we are very happy to have Matthias Troffaes as our speaker. Matthias Troffaes is Professor in the Department of Mathematical Sciences, and is a past SIPTA president, as well as the co-author of the book Lower previsions. Matthias Troffaes is both interested in the theory and practice of imprecise probabilities, having made fundamental core contributions to the theories of imprecise probabilities, as well as having applied them to environmental or engineering issues such as land crop management or the wind industry. On the 31st of January, at 15:00 CEST:paris time (up to 17:00 CEST, with a talk duration of 45min/1h), he will talk about "Fundamentally finitary foundations for probability and bounded probability”. Curious? Then check out the abstract on the webpage of the SIPTA seminars: sipta.org/events/sipta-seminars. The zoom link for attending the seminar can be found on that same page. So please mark your calendars on the 31st of January, and join us for the occasion. And for those who missed the previous seminar and want to catch up, or simply want to see it again and again, it is online at https://www.youtube.com/watch?v=rBgehsbawVY See you at the seminar! Sébastien, Enrique and Jasper

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Re: Final Reminder: Upcoming Deadlines for REC2024 Conference
by Kreinovich, Vladik Jan. 28, 2024

Jan. 28, 2024

FYI, papers using imprecise probabilities are very welcome at this series of conferences From: j-shi20(a)mails.tsinghua.edu.cn<mailto:j-shi20@mails.tsinghua.edu.cn> <j-shi20(a)mails.tsinghua.edu.cn<mailto:j-shi20@mails.tsinghua.edu.cn>> Sent: Wednesday, January 24, 2024 10:07 PM [cid:image002.png@01DA51F8.36111780] Dear Professor Kreinovich:, We trust this message finds you in good health and high spirits. As the deadline for key milestones approaches, we would like to remind you of the upcoming dates for the INTERNATIONAL WORKSHOP ON RELIABLE ENGINEERING COMPUTING 2024 (REC2024). (http://rec2024.com/) Revised Important Dates: One page abstract submission: January 31, 2024 Abstract notification of acceptance: February 15, 2024 Paper submission: May 31, 2024 Paper notification of acceptance: June 30, 2024 Final paper submission: July 31, 2024 Your contributions play a vital role in the success of REC2024, and we sincerely appreciate your commitment to the workshop. This extension was granted to ensure that all participants have ample time to refine their work and engage in meaningful discussions during the event. We kindly invite you to submit your abstract via email to submissionrec2024(a)gmail.com<mailto:submissionrec2024@gmail.com> with the subject line “REC2024 abstract submission”. Abstracts are strictly limited to ONE page. The abstract templates can be downloaded on the website (http://rec2024.com/) We understand the importance of your time and effort, and we thank you for your dedication to the REC2024 conference. Should you have any questions or concerns, do not hesitate to reach out to us. We look forward to your active participation in REC2024 and appreciate your continued support. Sincerely, REC2024 Chairs Yi Zhang Zhaohui Lu [cid:image003.jpg@01DA51F8.36111780]

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20-month research position in Human - AI interaction and medical decision support
by Davide Elio Ciucci Dec. 28, 2023

Dec. 28, 2023

We are seeking a motivated researcher for a fully funded research fellowship position (Italian Assegno di Ricerca – Post-Doc Equivalent) on topics related to Decision Support, Human-AI Interaction and eXplainable Artificial Intelligence, with a special focus on biomedical informatics and medical decision making. The position regards a recently funded Italian PRIN PNRR project “InXAId - Ricerca Nel Campo dell'interazione con l'intelligenza Artificiale Spiegabile nel Processo Decisionale Medico” (Research In The Field Of Interaction With Explainable Artificial Intelligence In Medical Decision Making"), under the scientific supervision of Prof. Federico Cabitza (PI) and Prof. Silvana Quaglini. The candidate will join the MUDILAB research group (https://mudilab.disco.unimib.it/) at the University of Milano-Bicocca, in Milan, Italy and work in close collaboration with the BMI laboratory (www.labmedinfo.org <http://www.labmedinfo.org/>) of the University of Pavia, in Pavia, Italy. More details Position: Research Fellow / Assegnista di Ricerca (post-doc equivalent) Location: Department of Informatics, Systems and Communication of the University of Milano-Bicocca, Viale Sarca 336, 20126, Milan, Italy Application Deadline: 15th January 2024, 12.00 (Italian Time) Link to the Call (with instructions on how to apply): https://www.unimib.it/ateneo/gare-e-concorsi/cod-23a413 Duration: 20 Months, tentatively starting in March 2024. Gross Salary: 2,848.00 Euros per month (According to Italian Law, that amount is not subject to income tax, but only to retirement funds; thus, the net salary should be slightly higher than 2,000 Euros.) The selected researcher will advance Human-AI collaboration in medical decision-making. Key tasks include: Developing Explainable AI (XAI): Innovate in XAI and Uncertainty Quantification for clinical decision support systems (CDSS). Designing Human-AI Protocols: Implement and test protocols that enhance decision-making and trust in AI processes. Empirical Analysis: Conduct experiments and data analysis to evaluate AI system effectiveness and decision-making impact. Academic Outreach: Publish findings in scientific venues, attend conferences, and engage in interdisciplinary collaboration. Teamwork: Work with a diverse team, integrating insights from clinicians, computer scientists, biomedical engineers and psychologists. The postdoc will also supervise PhD students, master degree students, and work in collaboration with them. This role demands strong AI and HCI expertise, ideally with a focus on healthcare applications. The project offers an opportunity to significantly contribute to both academic research and practical healthcare advancements. Admission Criteria To participate in the call, a master degree in Computer Science (LM-18 ), or Computer Engineering (LM-32 ), or Statistical Science (LM-82 ), or Techniques and methods for the information society (LM-91), or Biomedical engineering (LM-21 ), or Cognitive science (LM-55), or equivalent foreign degree, is required. A PhD is not required, but recommended. Previous background in AI and HCI is also highly recommended. About the Laboratory The MUDILAB at UNIMIB mainly focuses on the development and evaluation of decision support systems and eXplainable AI - human interaction protocols. Currently, the lab has two faculty members, three funded PhD students and two post-doc. The founders, the head Prof. Federico Cabitza and Prof. Davide Ciucci, have both been counted among the world's top 2% of researchers in AI and medical informatics for years, according to the list curated by Stanford researchers. The MUDI group has a recent track record of previous publications in prestigious venues (CHI, Interact, AAAI, ECAI, …) and research projects on both fundamental and application-oriented research, in collaborations with several hospitals and academic partners. The BMI lab at UNIPV has a long tradition (dating back to the mid 80s, with its founder Prof. Mario Stefanelli) of research in biomedical informatics and AI in medicine. Led by prof. Silvana Quaglini, the lab is the biggest in Italy in its field and counts 7 faculty, 2 post-docs, and 5 PhD students (enrolled either in the Biomedical Informatics PhD @UNIPV or in the National PhD in AI - health&life sciences pillar). Both groups aim to provide its members a friendly environment with strong supervision, in which individuals can grow and let their full potential flourish. We regularly organize group meetings and gatherings outside the lab to keep the team motivated and encourage a good work culture. For more information, do not hesitate to contact Prof. Federico Cabitza, at federico.cabitza [at] unimib.it <http://unimib.it/>

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CFP IPMU 2024 Special session: Dynamic decision models under uncertainty and imprecision
by Davide Petturiti Dec. 27, 2023

Dec. 27, 2023

Dear Colleague, We would like advertise the following special session: “Dynamic decision models under uncertainty and imprecision” we are organizing in the conference: 20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2024), 22-26 July 2024, Lisbon, Portugal (https://ipmu2024.inesc-id.pt/) We would be very grateful if Colleagues interested in sending a paper would communicate it to us, sending an email to: davide.petturiti(a)unipg.it<mailto:davide.petturiti@unipg.it> barbara.vantaggi(a)uniroma1.it<mailto:barbara.vantaggi@uniroma1.it> Below you can find all the information related to the special session. Best regards, Davide Petturiti and Barbara Vantaggi TITLE OF THE SPECIAL SESSION: Dynamic decision models under uncertainty and imprecision TOPICS: Topics of interest of the special session include, but are not limited to: * Decision making under uncertainty; * Games under ambiguous information; * Dynamic non-linear functionals and applications; * Portfolio selection under ambiguity; * Uncertainty and risk models under imprecise information. REVIEW PROCESS: Papers submitted to the special session will be treated as regular papers from both the perspective of the review process and of the proceedings. KEY DATES: Paper submission: February 23rd, 2024 Notification of acceptance: March 29th, 2024 Camera-ready paper submission: April 30th, 2024 Early/author registration: April 26th, 2024 Conference: July 22nd-26th, 2024 ORGANIZERS: Davide Petturiti, University of Perugia, Italy (davide.petturiti(a)unipg.it<mailto:davide.petturiti@unipg.it>) Barbara Vantaggi, Sapienza University of Rome, Italy (barbara.vantaggi(a)uniroma1.it<mailto:barbara.vantaggi@uniroma1.it>) [signature_4033098136] Davide Petturiti, Ph.D. Associate Professor Department of Economics University of Perugia Address: Via Pascoli 20, 06123 Perugia, Italy Phone: +39-075-585-5218 Fax: +39-075-585-5950 Email: davide.petturiti(a)unipg.it<mailto:davide.petturiti@dmi.unipg.it> Website: https://sites.google.com/site/davidepetturiti

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