[UAI] First International Conference on ICT for Health, Accessibility and Wellbeing (IHAW 2021): First Call for Papers

[George A. Papadopoulos]

*** First Call for Papers ***

First International Conference on ICT for Health, Accessibility and
Wellbeing (IHAW 2021)

November 8-10, 2021, Golden Bay Hotel 5*, Larnaca, Cyprus

http://www.cs.ucy.ac.cy/~george/lm/lm.php?tk=CQlBSQl1YWlAZW5nci5vcnN0LmVkdQlGaXJzdCBJbnRlcm5hdGlvbmFsIENvbmZlcmVuY2Ugb24gSUNUIGZvciBIZWFsdGgsIEFjY2Vzc2liaWxpdHkgYW5kIFdlbGxiZWluZyAoSUhBVyAyMDIxKTogRmlyc3QgQ2FsbCBmb3IgUGFwZXJzCTUxNwlHZW9yZ2UJMTgJY2xpY2sJeWVzCW5v&url=http%3A%2F%2Fcyprusconferences.org%2Fihaw2021%2F

(Proceedings to be published by Springer)


ICT for Health, Accessibility and Wellbeing (IHAW 2021) is the first of the
series of International Conferences on "ICT for Societal Challenges". It is a
showcase for high quality oral and poster presentations and demonstrations
sessions. This conference aims to be a platform for multi and interdisciplinary
research at the interplay between Information and Communication
Technologies, Biomedical, Neuro-cognitive, and Experimental research.

This research includes the design, experimental evaluation and
standardization of new ICT scalable systems and in-silico systems for new
and future inclusive and sustainable technologies that benefit all: healthy
people, people with disabilities or other impairments, people having chronic
diseases, etc. User-centered design and innovation, new intuitive ways of
human -computer interaction, and user acceptance are the topics of
particular interest.


Conference Topics

Relevant topics include (but are not limited to) the following:

· AI and Cognition, Cognitive Mechatronics, Human-Machine Interaction,
Cobotics, Model-based design and configuration tools for healthcare and
well-being, AI methods for medical device testing

· Systems for management of health and care (mental health, pain,
neurological disorders, sight, hearing, balance, space awareness; sensory
based physiological and psychological non-invasive measurements,
preventive healthcare, m-healthcare, e-healthcare, integrated care, serious
games, electronic health record, self-management, patient-centered systems
for survivorship, palliation and/or end-of-life care)

· Precision medicine

· ICT for in-silico trials

· Implantable medical devices

· Computational methods for medical device

· Models for human-device interaction for medicine

· Systems promoting access to the socio-economical and cultural
environment

· Age-friendly systems for active and healthy aging (telepresence, robotics
solutions, innovative solutions for independent living, innovative elderly care,
integrated care, age-related risks prevention/detection)

· Multimodal assistive ICT devices to empower people with sensory,
cognitive, motor, balance and spatial impairments

· ICT systems to improve the quality of life and for daily life activities
assistance (education, recreation, and nutrition)

· Smart living homes and wearables (Intelligent and personalized digital
solutions for sustaining and extending healthy and independent living;
personalized early risk detection and intervention)

· New experimental validation methods with end-users

· Standardization, certification, labeling, privacy, security and communication
issues (related to aging well, to sensory impairment)

High-quality original submissions that address such future issues, show the
design and evaluation in (near-) real scenarios, explain how to benchmark
systems, and outline the education and training procedures for acquiring new
perceptual skills while using such systems are welcome.

Research and technical papers are expected to present significant and original
contributions validated with the targeted end-users. Early works and works-
in-progress are invited to submit a short or demo paper.

Submissions should clearly state the progress beyond the existing state-of-
the-art and the expected societal benefits of the developed technology. When
possible, validate scenarios with the target user groups and well-identified
technology readiness levels
(https://en.wikipedia.org/wiki/Technology_readiness_level)
should be at least outlined.


Submissions

We invite three types of paper submissions:
1. Research and Technical papers, up to 15 pages, describing original
unpublished research, making a substantial contribution to the research field
2. Short papers, up to 6 pages, describing original unpublished research,
making a small but solid contribution to the field
3. Demos, up to 4 pages, describing innovative tools that address topics
relevant to the conference

All submissions will be reviewed by the Program Committee. Accepted
contributions will appear in the archival proceedings of IHAW 2021,
published by Springer in the Communications in Computer and Information
Science (CCIS) series (https://www.springer.com/series/7899),
and will be presented in plenary sessions of the conference.

The authors of the best papers accepted for IHAW2021 will be invited to
submit extended versions for a journal special issue (currently under
negotiation).

Submis

[UAI] CS professorships at Aalto University (Helsinki, Finland)

[Jussi Rintanen]

The CS Department of Aalto University calls for applications for 
tenure-track Assistant Professorship in all areas of Computer Science. 
The CS department is very well funded, availability of research funding 
in Finland in general is very good, and the positions come with a 
generous start-up package that funds a new research group for a number 
of years. Quality of life in Helsinki is internationally very 
competitive on multiple scales, and Finland is globally known as one of 
the progressive and technologically advanced Nordic societies.


See the position announcement at:

https://www.aalto.fi/en/open-positions/tenure-track-assistant-professors-in-computer-science 



Please seriously consider applying! We consider applicants for Assistant 
Professorships from 0 and 6 years from the granting of the Ph.D., so no 
need to do one or more post-docs before applying (you could even apply 
right after submitting your thesis.).


Although the now announced positions are at the Assistant Professor 
level, we are continuously looking for excellent candidates also at the 
Associate and Full Professor levels. Please contact me at 
jussi.rinta...@aalto.fi if you are interested in advancing your career 
this way.


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[UAI] AAAI Symposium on Machine Learning for Mobile Robot Navigation in the Wild: Call for Participation

[Xuesu Xiao]

*Due to AAAI SS21 conversion to virtual format, paper submission 
deadline is extended to January 15, 2021*



Dear Roboticists,

we would like to invite you to participate in our AAAI Spring Symposium 
*/Machine Learning for Mobile Robot Navigation in the Wild/* 
(https://sites.google.com/utexas.edu/ml4nav/), which will take place 
March 22-24 at Stanford University in Palo Alto, California, USA. We are 
also seeking related contributions in the form of *six-page* full paper 
and *two-page* abstract, and industrial participants. The submission 
deadline is November 8th. AAAI EasyChair site submission link can be 
found at https://easychair.org/conferences/?conf=sss21. For details, 
please see the following Call for Participation 
(https://docs.google.com/document/d/1WHmfNDilpvVieK1JbaTDy6SCNbmuREdQN7YEZu3OU64/edit?usp=sharing): 




**

Call for Participation


The Machine Learning for Mobile Robot Navigation in the Wild Symposium 
in AAAI 2021 SSS will take place March 22-24 at Stanford University in 
Palo Alto, California, USA. The 2.5-day symposium will consist of 
invited talks, technical presentations, spotlight posters, robot 
demonstrations, industry spotlights, breakout sessions, and interactive 
panel discussions.



Decades of research efforts have enabled classical navigation systems to 
move robots from one point to another, observing system and 
environmental constraints. However, navigation outside a controlled test 
environment, i.e., navigation in the wild, remains a challenging 
problem: an extensive amount of engineering is necessary to enable 
robust navigation in a wide variety of environments, e.g., to calibrate 
perception or to fine-tune navigational parameters; classical map-based 
navigation is usually treated as a pure geometric problem, without 
considering other sources of information, e.g., terrain, risk, social 
norms, etc.



On the other hand, advancements in machine learning provide an 
alternative avenue to develop navigation systems, and arguably an 
“easier” way to achieve navigation in the wild. Vision input, semantic 
information, terrain stability, social compliance, etc. have become new 
modalities of world representations to be learned for navigation beyond 
pure geometry. Learned navigation systems can also largely reduce 
engineering effort in developing and tuning classical techniques. 
However, despite the extensive application of machine learning 
techniques on navigation problems, it still remains a challenge to 
deploy mobile robots in the wild in a safe, reliable, and trustworthy 
manner.



In this symposium, we focus on navigation in the wild as opposed to 
navigation in a controlled, well-engineered, sterile environment like 
labs or factories. In the wild, mobile robots may face a variety of 
real-world scenarios, other robot or human companions, challenging 
terrain types, unstructured or confined environments, etc. This 
symposium aims at bringing together researchers who are interested in 
using machine learning to enable mobile robot navigation in the wild and 
to provide a shared platform to discuss learning fundamental navigation 
(sub)problems, despite different application scenarios. Through this 
symposium, we want to answer questions aboutwhy, where, and how to apply 
machine learning for navigation in the wild, summarize lessons learned, 
identify open questions, and point out future research directions.



Symposium URL: https://sites.google.com/utexas.edu/ml4nav/


Organizing Committee:

Xuesu Xiao (Symposium Chair), The University of Texas at Austin, Email: 
x...@cs.utexas.edu 


Harel Yedidsion, The University of Texas at Austin, Email: 
ha...@cs.utexas.edu 


Reuth Mirsky, The University of Texas at Austin, Email: 
re...@cs.utexas.edu 


Justin Hart, The University of Texas at Austin, Email: 
h...@cs.utexas.edu 


Peter Stone, The University of Texas at Austin, Sony AI, Email: 
pst...@cs.utexas.edu 


Ross Knepper, Cornell University, Email: ross.knep...@gmail.com 



Hao Zhang, Colorado School of Mines, Email: hzh...@mines.edu 



Jean Oh, Carnegie Mellon University, Email: jea...@cmu.edu 



Davide Scaramuzza, University of Zurich, ETH Zurich, Email: 
sdav...@ifi.uzh.ch 


Vaibhav Unhelkar, Rice University, Email: vaibhav.unhel...@rice.edu 




Submission Instructions:


Full papers of up to sixpages and abstract papers of up to twopages are 
sought in the following topic areas:


 *

   Learning for social navigation

 *

   Learning for terrain-based navigation

 *

   Learning for vision-based navigation

 *

   Learning for interactive navigation

 *

   Representation learning for navigation

 *

   Sim2real for navigation

 *

   Zero-shot path pla

[UAI] DIMACS Postdoctoral positions

[Isha Deen-Cole]

DIMACS, the Center for Discrete Mathematics and Theoretical Computer Science, 
based at Rutgers University, invites applications for postdoctoral positions 
associated with the Center.

DIMACS solicits applications of two types:

a) DIMACS - Institute for Advanced Study (IAS) Postdoc. This is a two-year 
postdoctoral associateship with the first year (2021-2022) spent at DIMACS, and 
the second year (2022-2023) spent at IAS in Princeton. There is a requirement 
to teach one course during the first year. Applicants should be recent PhDs 
with interest in theoretical computer science and/or discrete mathematics. 
Research areas include but are not limited to: computational complexity, 
algorithms, optimization, cryptography, combinatorics, graph theory, and 
discrete probability. For this postdoc, applicants must apply both to DIMACS 
and IAS.

b) DIMACS Postdoc. This is a one-year position. Topics include theoretical 
computer science (TCS), the foundations of data science (DS), and artificial 
intelligence (AI). The postdoc will be based at DIMACS at Rutgers University, 
mentored by a faculty member at Rutgers or a DIMACS partner institution, and 
able to participate in the breadth of activities at DIMACS, while working on a 
research program of his or her own design. The postdoc will have unique 
opportunities to help plan workshops to complement their research and visit one 
of four domestic and four international partners. Applicants should be recent 
PhD graduates in computer science, economics, information science, operations 
research, or a related field, preferably with a focus in TCS or AI.

Positions provide salary, health benefits, and an allowance for domestic travel.

Applicants should provide a cover letter specifying which postdoctoral 
position(s) they are applying for, a curriculum vitae, a research statement 
highlighting their past and planned future research, a teaching statement if 
applying for the DIMACS-IAS position or intending to teach, and the names & 
email addresses of three references.

DIMACS fosters research and education programs on topics that lie at the 
interface of discrete mathematics and theoretical computer science and their 
wide-ranging applications. It was founded as an NSF Science and Technology 
Center in 1989. DIMACS’s partners include Rutgers University, AT&T Labs - 
Research, Columbia University, Georgia Tech, IBM Research, Microsoft Research, 
NEC Laboratories America, New Jersey Institute of Technology, Nokia Bell Labs, 
Perspecta Labs, Princeton University, Rensselaer Polytechnic Institute, and 
Stevens Institute of Technology.

Research and education areas at DIMACS include algorithms, combinatorics, 
complexity, privacy and security, discrete and computational geometry, 
optimization, graph theory, data science, artificial intelligence, and machine 
learning, with applications in sustainability, epidemiology, genetics, 
networks, transportation, security, and economics. Many DIMACS activities 
relate to specific topics of current interest represented by the DIMACS Special 
Focus programs. Postdoctoral Associates at DIMACS are encouraged to collaborate 
with DIMACS members and visitors and to participate in all of the research and 
educational activities of DIMACS.

We believe that research and society benefit from a diverse workplace and 
strongly encourage applications from women, minorities, individuals with 
disabilities, veterans, and students with non-traditional backgrounds.

For more information: https://jobs.rutgers.edu/postings/122935

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[UAI] ACM UMAP 2021: Second call-for-papers

[Oana Inel]

--- Apologies for cross-posting ---



Call for Papers - ACM UMAP 2021
29th ACM International Conference on User Modeling, Adaptation and 
Personalization
Theme: "Re-Evaluating Evaluation in Personalization Research"

Hybrid: Utrecht (The Netherlands) and Online
June 21-25th (tentative), 2021

Website: https://www.um.org/umap2021/


Abstracts due: January 17, 2021 (mandatory)
Full paper due: January 24, 2021



BACKGROUND AND SCOPE:

ACM UMAP – User Modeling, Adaptation and Personalization – is the premier 
international conference for researchers and practitioners working on systems 
that adapt to individual users or to groups of users, and that collect, 
represent, and model user information. ACM UMAP is sponsored by ACM SIGCHI and 
SIGWEB, and organized with User Modeling Inc. as the core Steering Committee, 
extended with past years’ chairs. The proceedings are published by ACM and will 
be part of the ACM Digital Library.

ACM UMAP covers a wide variety of research areas where personalization and 
adaptation may be applied. This includes a number of domains in which 
researchers are engendering significant innovations based on advances in user 
modeling and adaptation, recommender systems, adaptive educational systems, 
intelligent user interfaces, e-commerce, advertising, digital humanities, 
social networks, personalized health, entertainment, and many more.

We welcome submissions related to user modeling, personalization and 
adaptation; the conference web site provides a detailed list. Below we present 
a short (but not proscriptive) list of topics of importance to the conference. 
As the theme for UMAP 2021 is “Re-Evaluating Evaluation” we encourage 
submissions in all areas that offer a critical analysis of evaluations of 
personalized systems. We particularly want to acknowledge that some of the 
research might be influenced by Covid-19 related constraints (e.g., difficulty 
of running lab studies), and welcome submissions which introduce novel 
methodologies arising from a need to conduct research in new ways.


CONFERENCE TOPICS:

We welcome submissions related to user modeling, personalization and adaptation 
in any area. The topics listed below are not intended to limit possible 
contributions.
Final decisions will be made on the basis of suitability for, and fit to, the 
overall conference (not for specific tracks). Additionally, there is no quota 
for the maximal number of accepted papers per track. Topics include (but are 
not limited to):
• Personalized Recommender Systems
• Track chairs: Alejandro Bellogin, Sole Pera, Ludovico Boratto
• Adaptive Hypermedia and the Semantic Web
• Track chairs: Maria Bielikova, Panagiotis Germanakos, Ben Steichen
• Intelligent User Interfaces
• Track chairs: Katrien Verbert, Denis Parra
• Personalized Social Web
• Track chairs: Julita Vassileva, Jie Zhang
• Technology-Enhanced Adaptive Learning
• Track chairs: Ella Haig, Manolis Mavrikis
• Fairness, Transparency, Accountability, and Privacy
• Track chairs: Christine Bauer, Michael Ekstrand
• Personalization for Persuasive and Behavior Change Systems
• Track chairs: Jaap Ham, Rita Orji


SUBMISSION AND REVIEW PROCESS

Papers will be submitted through EasyChair:
https://easychair.org/conferences/?conf=acmumap2021


Long (8 pages + references) and Short (4 pages + references) papers in ACM 
style. Original research papers addressing the theory and/or practice of UMAP, 
and papers showcasing innovative use of UMAP and exploring the benefits and 
challenges of applying UMAP technology in real-life applications and contexts 
are welcome.


  *   Long papers should present original reports of substantive new research 
techniques, findings, and applications of UMAP. They should place the work 
within the field and clearly indicate its innovative aspects. Research 
procedures and technical methods should be presented in sufficient detail to 
ensure scrutiny and reproducibility. Results should be clearly communicated and 
implications of the contributions/findings for UMAP and beyond should be 
explicitly discussed.

  *   Short papers should present original and highly promising research or 
applications. Merit will be assessed in terms of originality and importance 
rather than maturity, extensive technical validation, and user studies. 
Separation of long and short papers will be strictly enforced so papers will 
not compete across categories, but only within each category.

Papers must be formatted using the ACM SIG Standard (SIGCONF) proceedings 
template: https://www.acm.org/publications/proceedings-template.

UMAP uses a double blind review process. Authors must omit their names and 
affiliations from submissions, and avoid obvious identifying statements. For 
instance, citations to the authors' own prior work should be made in the 
third-pe

[UAI] Call for Book Chapters (Extended Deadline): Artificial intelligence and Blockchain for Future Cybersecurity Applications by Springer

[Yassine MALEH]

*Call for Book Chapters: **Artificial intelligence and Blockchain for
Future Cybersecurity Applications by Springer **"Studies in Big Data"
 *

Call for chapters website: https://sites.google.com/view/aiblockchain
Submission Deadline: *December 30, 2020 (Extended Deadline)*
Submission Link: https://easychair.org/conferences/?conf=aiblockcyber2020


*Scope:*

AI and Blockchain technologies have infiltrated all areas of our lives,
from manufacturing to healthcare and beyond. Cybersecurity is an industry
that has been significantly affected by this technology and maybe more so
in the future. The upcoming book will go in-depth showing how Blockchain
and Artificial Intelligence can be used for cybersecurity applications.
Merging AI and Blockchain can be used to prevent any data breach, identity
theft, cyber-attacks, or criminal acts in transactions.
Submission Guidelines:

Authors are invited to submit their full chapter by* December 30, 2020*.
Manuscripts submitted for the book must be original, must not be previously
published or currently under review anywhere. Submitted manuscripts should
respect the standard guidelines of the *Springer book chapter format*.
Manuscripts must be prepared using Latex, or Word, and according to the
Springer requirements that can be downloaded from the (*link*
)
and the Chapter should contain in between 20-30 pages. *Manuscripts that do
not follow the formatting rules will be rejected without review.* Prospective
authors should send their manuscripts electronically through the easychair
submission system as mentioned below:

https://easychair.org/conferences/?conf=aiblockcyber2020

*NB:* There are *no submission or acceptance fees* for manuscripts
submitted to this book publication. All manuscripts are accepted based
on a *double-blind
peer review* editorial process.
List of Topics:

   - Artificial intelligence models and blockchain cybersecurity
   - Blockchain-based AI for future cybersecurity applications
   - AI and Blockchain in Cybersecurity threat detection
   - Blockchain in intelligent networks
   - Blockchain and AI for cybersecurity in E-Health
   - Blockchain and AI for cybersecurity in cyber-physical systems
   - Blockchain and AI for cybersecurity in Smart cities
   - Blockchain and AI for cybersecurity in IoT
   - Clustering and classification algorithms for blockchain for sensor
   networks
   - Crypto chips and artificial intelligence
   - Reinforcement learning and blockchain for Cybersecurity
   - Intelligent systems for fraud detection and forensics in blockchain
   environments
   - Intelligent applications of blockchain and cybersecurity
   - Multi-agent systems and blockchain for cybersecurity
   - AI and Blockchain for cybersecurity in cyber-physical systems
   - Malware detection and Prevention using AI
   - Deep Learning for Security Operation Centers
   - Blockchain and AI for detecting threats and attacks
   - Cybersecurity Using Blockchain Technology
   - Intrusion and cybersecurity threat detection and analysis
   - Deep Learning techniques for Cybersecurity and Privacy
   - Machine Learning techniques for Cybersecurity and Privacy
   - Big Data Analytics for cybersecurity

Editors:

   - Yassine Maleh, Sultan Moulay Slimane University, Morocco
   - Youssef Baddi, Chouaib Doukkali University
   - Mamoun Alazab, Charles Darwin University, Australia
   - Loai Tawalbeh, Texas A&M University-San Antonio, USA
   - Imed Romdhani,  Edinburgh Napier, UK

Important Dates:

Chapters Submission: December 30, 2020

Authors notification: January 10, 2021

Camera-ready submission: January 30, 2021

Publication date: 1st quarter of 2021

*Contact:*

For questions regarding the book, please contact Professor Yassine Maleh:

   - *Yassine Maleh, *Sultan Moulay Slimane University:
   yassine.ma...@ieee.org


-- 

Y. Maleh, Ph.D.

*Senior Member IEEE*

*Professor of Cybersecurity, ENSAK*

*Editor in Chief IJSST
*

*Associate Editor,* IEEE
*Access
,
IJISP
,
IJDCF
*



Phone +212 608 867 568

Webiste: Personal Website 

*yassine.ma...@ieee.org * ORC*ID*
 ; *Pub*
lons ; *R*

[UAI] Computer Vision and Machine Learning (CVML) and Autonomous Systems Web Lecture Series

[Ioanna Koroni]

Dear Computer Vision, Machine Learning and Autonomous Systems  engineers,
scientists and enthusiasts,


you are welcomed to register in the  'Computer Vision, Machine Learning and
Autonomous Systems Web Lecture Series'.


After the very successful completion of a) the Spring2020 edition of the
CVML Web Lecture Series and b) the 'Summer School on Autonomous Systems
2020' 17-21/8/2020, attracting more than 100 registrants, AIIA Lab
(AIIA.CVML research group) offers an asynchronous mode to study Computer
Vision, Machine Learning and Autonomous Systems topics. CVML Web Lecture
list is found below. Sample material of this course is available and lecture
topics are provided as well.


This asynchronous e-course provides an overview and in-depth presentation of
the various computer vision and deep learning problems encountered in
autonomous systems perception, e.g. in drone imaging or autonomous car
vision. It consists of 21 one-hour lectures and related material (ppt/pdf,
self-assessment exercises, videos, 5 programming exercises), covering the
following topics:


a. Computer vision. After reviewing image acquisition, camera geometry
(mapping the 3D world on a 2D image plane) and camera calibration, stereo
and multi-view imaging systems are presented for recovering 3D world
geometry from 2D images. This is complemented by Structure from Motion (SfM)
towards Simultaneous Localization and Mapping (SLAM) for vehicle and/or
target localization and visual object tracking and 3D localization. Motion
estimation algorithms are also overviewed.
b. Neural Networks and Deep Learning. As there is much hype and often little
accuracy, when treating these topics, first the principles of Machine
Learning are presented, focusing on classification and egression. Then, an
introduction to neural networks, provides rigorous formulation of the
optimization problems for their training, starting with Perceptron. It
continues with Multilayer perceptron training through Backpropagation,
presenting many related problems, such as over-/under-fitting and
generalization. Deep neural networks, notably Convolutional NNs are the core
of this domain nowadays and they are overviewed in great detail. Their
application on deep learning for object detection is a very important issue
as well, complemented with a presentation of deep semantic image
segmentation.
c. Autonomous Systems. First of all, an introduction to Autonomous Systems
(AS) provides an overview of various issues related to AS perception and
control. Then topics related to autonomous drones are detailed, notably
drone mission planning and control and multiple drone imaging. Then
Autonomous cars and autonomous marine vehicles are overviewed.
d. CVML algorithms and programming. Various such tools, libraries and
frameworks are overviewed: Robotic Operating System (ROS), linear algebra
libraries (BLAS), DNN libraries (e.g., cuBLAS, cuDNN) and frameworks (e.g.,
Pytorch, Tensorflow, Keras etc). Distributed computing frameworks (Apache
Spark) and collaborative SW development tools are overviewed as well (e.g.,
GitHub).
e. Signals and Systems. Much confusion exists nowadays in ML literature, as
even mature ML scientists have no background on Signals and Systems (SS) and
confuse even basic notions, e.g., convolutions and correlations. SS
principles are overviewed, while focusing on fast convolution algorithms,
particularly on 2D convolution algorithms that are an absolute must for CNN
libraries/frameworks and many computer vision tasks.

You can use the following link for course registration:

http://icarus.csd.auth.gr/cvml-web-lecture-series/



Lecture topics, sample lecture ppts and videos, self-assessment
questionnaires and programming exercises can be found therein.

For questions, please contact: Ioanna Koroni mailto:koroniioa...@csd.auth.gr> >



The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow,
Chair of the IEEE SPS Autonomous Systems Initiative, Director of the

Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle
University of Thessaloniki, Greece, Coordinator of the European Horizon2020

R&D project Multidrone. He is ranked 249-top Computer Science and
Electronics scientist internationally by Guide2research (2018). He is head

of the EC funded AI doctoral school of Horizon2020 EU funded R&D project
AI4Media (1 of the 4 in Europe). He has 31600+ citations to his work

and h-index 85+.



AUTH is ranked 153/182 internationally in Computer Science/Engineering,
respectively, in USNews ranking.



Relevant links:

1) Prof. I. Pitas:

https://scholar.google.gr/citations?user=lWmGADwJ
 &hl=el

2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/

3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/

4) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/

5) AIIA Lab: https://aiia.csd.auth.gr/



LECTURES
Computer vision

1.  

[UAI] Call for Paper: LAMAS&SR 2021, London, 3 or 4 May (TBA) 2021

[Bastien]

FIRST CALL FOR PAPERS

International Workshop on Logical Aspects of Multi-Agent Systems and 
Strategic Reasoning (LAMAS&SR)
Satellite workshop of AAMAS 2021, London, United Kingdom, May 3 or 4 
(TBA), 2021


    https://lamassr.github.io/

Logics and strategic reasoning play a central role in multi-agent systems.
Logics can be used, for instance, to express the agents' abilities, 
knowledge, and objectives.
Strategic reasoning refers to algorithmic methods that allow for 
developing good behavior
for the agents of the system. At the intersection, we find logics that 
can express existence

of strategies or equilibria, and can be used to reason about them.

The LAMAS&SR workshop merges two international workshops:
LAMAS, which focuses on all kinds of logical aspects of multi-agent 
systems from the perspectives of artificial intelligence, computer
science, and game theory, and SR, devoted to all aspects of strategic 
reasoning in formal methods and artificial intelligence.


Over the years the communities and research themes of both workshops got 
closer and closer.
LAMAS&SR unifies LAMAS and SR under the same flag, formally joining the 
two communities in
order to expose each of them to a wider range of work relevant to their 
research.


LAMAS&SR is thus interested in all topics related to logics and 
strategic reasoning in multi-agent systems,

from theoretical foundations to algorithmic methods and implemented tools.

The topics of the workshop include, but are not limited to:

    Logical systems for specification, analysis, and reasoning about 
multi-agent systems;

    Logic-based modeling of multi-agent systems;
    Dynamical multi-agent systems;
    Deductive systems and decision procedures for logics for 
multi-agent systems;
    Development and implementation of methods for formal verification 
in multi-agent systems;

    Logic-based tools for multi-agent systems;
    Logics for reasoning about strategic abilities;
    Logics for multi-agent mechanism design, verification, and synthesis;
    Logical foundations of decision theory for multi-agent systems;
    Strategic reasoning in formal verification;
    Automata theory for strategy synthesis;
    Applications and tools for cooperative and adversarial reasoning;
    Robust planning and optimization in multi-agent systems;
    Risk and uncertainty in multi-agent systems;
    Quantitative aspects in strategic reasoning.


LAMAS&SR 2021 will be held with AAMAS 2021 in London, England.


SUBMISSIONS:

Authors are invited to submit extended abstracts of 2 pages plus 1 page 
for references in the AAMAS format.

Both published and unpublished works are welcome.
Submissions are subject to a single-blind review process (submissions 
should not be anonymous).


There will be no formal proceedings, but accepted extended abstracts 
will be made available on the workshop's website.

We envisage that extensions of selected papers will be invited to a journal.

Authors are invited to submit their manuscript via EasyChair.
Submission webpage: https://easychair.org/my/conference?conf=lamassr21#

IMPORTANT DATES:

Paper submission: 10 Feb, 2021 (AoE)
Author Notification: 10 March, 2021
Camera Ready: 24 March, 2021
Workshop: May 3 or 4, 2021 (TBA)

ORGANIZERS:

Bastien Maubert, University of Naples "Federico II"
(bastien.maub...@gmail.com)

Giuseppe Perelli, Sapienza University of Rome
(pere...@diag.uniroma1.it)

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[UAI] 2nd CFP: IUI Workshop on Exploratory Search and Interactive Data Analytics (ESIDA)

[Axel Soto]

Fourth IUI Workshop on Exploratory Search and Interactive Data Analytics  
(ESIDA)

https://sites.google.com/view/esida2021/home
13 April 2021, Virtual

Important Dates:
Submission deadline: December 23, 2020 (midnight Hawaii time)
Acceptance notification: January 31, 2021
Final manuscript due: February 15, 2021
Workshop:  April 13, 2021

Workshop Description:
This workshop will be part of the ACM Intelligent User Interfaces 2021  
Conference (http://iui.acm.org/2021/). The workshop focuses on systems  
that personalize, summarize and visualize the data for supporting  
interactive information seeking and information discovery, along with  
tools that enable user modeling and methods for incorporating the user  
needs and preferences into both analytics and visualization. Our aim is to  
bring together researchers and practitioners working on different  
personalization aspects and applications of exploratory search and  
interactive data analytics. This will allow us to achieve four goals: (1)  
propose new strategies for systems that need to convey the rationale  
behind their decisions or inference, and the sequence of steps that lead  
to specific (search) results; (2) develop new user modeling and  
personalization techniques for exploratory search and interactive data  
analytics; (3) develop a common set of design principles for this type of  
systems across platforms, contexts, users and applications; (4) develop a  
set of evaluation metrics for personalization in exploratory search. The  
workshop aims to solicit submissions in the following areas of  
personalized interactive data analytics and exploratory search:


Personalized interactive exploration via interactive data analytics:
– personalization aspects in systems for exploratory search.
– cross-domain/ context-aware/ cross-platform exploratory search systems.
– interactively modelling the user’s information needs for high-recall  
information retrieval.

– new applications of exploratory search and interactive data analytics.
Data analytics:
– interactive interfaces for data-intensive platforms.
– interaction degrees of freedom.
– preprocessing vs. online processing.
– interactive data visualization evaluation of interactive systems for  
exploratory search and data analytics.

Metrics for explainable intelligent systems:
– metrics for explainable exploratory search.
– explainability and transparency in expert vs. non-expert systems.
– human-in-the-loop analytics systems.
– efficient vs. explainable analytics.
– user perception of explainability and transparency in interactive  
intelligent systems.


Organisers:
Dorota Glowacka,
Department of Computer Science, University of Helsinki (Finland),  
glowacka[at]cs.heelsinki.fi

Evangelos Milios,
Faculty of Computer Science, Dalhousie University (Canada),  
eem[at]cs.dal.ca

Axel J. Soto,
Institute for Computer Science and Engineering, UNS - CONICET (Argentina),  
axel.soto[at]cs.uns.edu.ar

Fernando V. Paulovich,
Faculty of Computer Science, Dalhousie University (Canada),  
paulovich[at]dal.ca

Denis Parra,
Department of Computer Science, Pontificia Universidad Católica (Chile) ,  
dparra[at]ing.puc.cl

Osnat (Ossi) Mokryn,
Department of  Information and Knowledge Management, University of Haifa   
(Israel), omokryn[at]univ.haifa.ac.il


Submission Information:
We encourage submissions of work in progress, concept papers, case  
studies, ongoing research projects, reports on recently completed PhD  
dissertations or recently accepted journal papers, and generally material  
that will stimulate discussion, generate useful feedback to the authors,  
encourage research collaborations and vigorous exchange of ideas on  
promising research directions, in one of the following formats:
-full papers (up to 8 pages in ACM sigconf format), which will presented  
either as contributed talks or posters
-extended abstracts (up to 4 pages in ACM sigconf format), which will be  
presented as posters with a possibility to be accompanied by a demo.

Papers can be submitted through EasyChair:
https://easychair.org/conferences/?conf=esida21

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[UAI] Australian Robotic Vision Summer School (RVSS), Australia, 1-5 February 2021

[RVSS]

~~

Australian Robotic Vision Summer School (RVSS), Australia, 1-5 February 2021

~~



The Australian Centre for Robotic Vision (ACRV) is 
pleased to announce the 7th annual Robotic Vision Summer School (RVSS).

The summer school provides a premium venue for graduate students to:

·  learn about fundamental and advanced topics in computer vision and robotics.

·  know the latest developments in robotic vision as presented by world's 
leading experts

·  Introduction to robotic vision application domains

·  A unique opportunity to experiment with computer vision algorithms on actual 
robotic hardware

·  Chance to meet and network with peers and experts in the field.



Due to COVID this will be run in a mixture of online and local node formats.  
Groups of 4 or more students from the same city or institution can form nodes 
to provide communal learning support and run the workshops in person.  
Tutorials and Deep Dives will be online.  Individual students can participate 
in a fully online mode although the workshop activities will be simulations 
only.  Further information on speakers and the program is available at the 
summer school website.  Have a look at the YouTube promotional videos from 
previous years RVSS 2019 and last 
year RVSS 2018.



To apply see our website: RVSS 2021

Summer School: 1 - 5 February 2021

Location: hybrid online and local nodes.  Contact organisers for details.



Application deadline:  18 December 2020

Registration deadline: 4 January 2021

Registration Fee: $300

Late Registration Fee: $350



RVSS 2021 Organizers:

 Prof. Robert Mahony, ANU

 Dr Pamela Carreno, Monash University
 Dr Yizhak Ben Shabat, ANU

 Ms Katrina Tune, QUT
Mrs Carol Taylor, ANU


For more information regarding the program/logistics, please visit the website 
(above) or contact Carol Taylor 
rvss.c...@anu.edu.au.




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[UAI] Postdoc Position in Face Processing and Social Cognition

[Angela Yu]

Applications are invited from highly motivated researchers for a postdoctoral 
position immediately available in the Computational & Cognitive Neuroscience 
Lab, led by Prof. Angela Yu, at University of California, San Diego.  One 
current project of particular interest is using machine learning, computer 
vision, and statistical techniques to model human face processing and 
representation, as well as face-based social cognition. 

More broadly, Dr. Yu’s lab applies modern machine learning and statistical 
tools to extract computational principles that underlie cognitive processes 
that enable intelligent behavior, in particular how humans and other 
intelligent agents perform inference, learning, decision-making, and social 
interactions under conditions of uncertainty and non-stationarity. Current 
interests include face processing, attention, active sensing, judgement and 
decision making, and social cognition.

Applicants should be committed to applying rigorous computational and 
mathematical tools to understand natural intelligence. Experience or interest 
in carrying out human behavioral experiments (either in person or on-line) 
and/or collaborating with neuroimaging/neurophysiology laboratories is 
desirable. Initial appointment is for one year, renewable for up to 2-3 years.

Dr. Yu's lab is situated within the Cognitive Science department, and also 
affiliated with the Halıcıoğlu Data Science Institute, the Computer Science 
Department, the Neurosciences Graduate Program, and the Institute of Neural 
Computation. There are ample opportunities for collaborations with related 
groups across the UCSD main campus, the medical school, and the Salk Institute.

Interested candidates should send a research statement, along with a CV 
including publications, to Dr. Angela Yu (a...@ucsd.edu ) 
with the subject “Postdoc Application”. Two or more letters of references 
should be sent directly by the recommenders to a...@ucsd.edu 
. More information about Dr. Yu’s group can be found at 
https://www.cogsci.ucsd.edu/~ajyu .


--
Angela Yu
Associate Professor
Dept. of Cognitive Science
Halıcıoğlu Data Science Institute
UC San Diego
858-822-3317
http://www.cogsci.ucsd.edu/~ajyu 
--

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[UAI] Remainder: Special Issue of the journal Entropy on "Bayesian Inference in Probabilistic Graphical Models"

[ANTONIO SALMERON CERDAN]

Dear Colleagues,

Probabilistic graphical models (PGMs) have become a popular statistical 
modelling tool with remarkable impact on disciplines like data mining and 
machine learning, because their most outstanding features are their clear 
semantics and interpretability. Bayesian inference methods naturally embed into 
PGMs, providing them with efficient and sound techniques for estimating both 
structure and parameters. Bayesian inference has been the key to the 
application of PGMs in specially demanding domains like streaming data 
analysis, where the models need to be frequently updated when new data arrives.

There are, however, a number of open issues concerning scalability, which is 
especially relevant in big data domains. In general, approximate techniques are 
employed, including variational inference and Markov Chain Monte Carlo. This 
Special Issue seeks original contributions covering aspects of Bayesian methods 
for learning PGMs from data and efficient algorithms for probabilistic 
inference in PGMs. Papers covering relevant modelling issues are also welcome, 
including papers dealing with data stream modelling, Bayesian change point 
detection, feature selection and automatic relevance determination. Even though 
entirely theoretical papers are within the scope of this Special Issue, 
contributions including a thorough experimental analysis of the methodological 
advances are particularly welcome, so that the impact of the proposed methods 
can be appropriately determined in terms of performance over benchmark datasets.

Keywords
Bayesian networks
Probabilistic Graphical Models
Bayesian methods
Cross Entropy Methods
Variational Inference
Bayesian Data Stream Modelling
Monte Carlo methods for PGMs

Link: https://www.mdpi.com/journal/entropy/special_issues/graphical_models 


Deadline for paper submission: 1 March 2021

Prof. Rafael Rumí
Prof. Antonio Salmerón
Guest Editors


—
Antonio Salmerón Cerdán
Department of Mathematics
University of Almería
http://www.ual.es/personal/asalmero




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