April 27th, 2023 
Daniela Lopez de Luise —————————————————
Department of Engineering and Architecture
University of Parma
Parco Area delle Scienze 181/A
I-43124 Parma, Italy
April 27th, 2023 Daniela Lopez de Luise 10th IEEE International Conference on Data Science and Advanced Analytics (DSAA) (https://conferences.sigappfr.org/dsaa2023/)
Location: Thessaloniki, Greece
Date: October 9-13, 2023
Website: https://gradsci.github.io/
About the Special Session
GraDSci: Graph Data Science and Applications is a Special Session of the 10th IEEE International Conference on Data Science and Advanced Analytics (DSAA). The special session aims to bring together researchers from academia and industry who are interested in state-of-the-art algorithmic techniques and methodologies in graph data science, ranging from graph mining to graph representation learning, along with their applications.
We live in an interconnected world where entities interact with each other creating complex systems that can be modeled by graphs. Social networks, for example, are used to model interactions among individuals in collaboration networks and online social media applications. Information networks, such as the Web or knowledge graphs, provide an effective way to model and navigate relational content. In the biomedical domain, complex heterogeneous graphs are used to describe the interactions between patients, diseases, and drugs, toward detecting polypharmacy side effects or addressing drug repurposing problems. Finally, molecular graphs, which capture the interactions between atoms or molecules, have recently been used to discover new materials, accelerating scientific discovery.
Topics of Interest
The topics of interest of the GraDSci special session include, but are not limited to:
Graph data science algorithms and methods
– Representation learning on graphs
– Deep learning and graph neural networks
– Scalable graph learning models and methods
– Bias and fairness in graph machine learning
– Probabilistic graphical models
– Statistical models of graphs
– Graph kernels and graph similarity
– Semi-supervised, self-supervised, and unsupervised graph learning
– Graph sampling and inference
– Graph clustering and community detection
– Graph summarization
– Graph anomaly detection
– Learning on spatial, temporal, and dynamic networks
– Learning on heterogeneous and multi-relational graphs
– Graph data processing and management
– Graph visualization
Application domains
– Social media and social network analysis
– Influence propagation and misinformation detection
– Knowledge graphs and semantic networks
– Recommender systems
– Natural language processing
– Multimedia signal processing and computer vision
– Computational health, biomedicine, and epidemiology
– Computational biology and bioinformatics
– Neuroscience and brain network analysis
– Drug design and pharmaceutical sciences
– Materials science
– Urban network analysis
– Environment
– Communication networks and cybersecurity
Important Dates
– Special Session Paper Submission Deadline: May 2, 2023 May 22, 2023
– Special Session Paper Notification: July 10, 2023 July 17, 2023
– Camera Ready Submission: August 7, 2023
Submission Instructions
Please look at: https://gradsci.github.io/submission/
Organizers
– Fragkiskos D. Malliaros, Paris-Saclay University, CentraleSupelec, Inria, France
– Jhony H. Giraldo, Telecom Paris, Institut Polytechnique de Paris, France
April 27th, 2023 Daniela Lopez de Luise The Unconstrained Ear Recognition Challenge 2023 (UERC)
Held in conjunction with IEEE IJCB 2023
https://ijcb2023.ieee-biometrics.org/
Important dates: Registration is open now
UERC 2023 Website: http://awe.fri.uni-lj.si/uerc.html
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Ear recognition is an active area of research within the biometric
community. However, the work in this field has long focused on maximizing
raw recognition performance, while other aspects critical for the
deployment of biometrics recognition techniques in practice have largely
been ignored. One such example is demographic bias. Modern ear
recognition approaches are not only expected to be highly efficient when
recognizing individuals, but also to be equally fair in their decisions,
regardless of the demographic characteristics of the subjects, e.g.,
gender or ethnicity. The 2023 Unconstrained Ear Recognition Challenge
will, therefore, investigate the performance as well as demographic bias
of existing ear recognition solutions and promote research into
bias-mitigation mechanisms that have minimal impact on the recognition
performance.
Understanding demographic bias is important because it can help to
identify and mitigate inaccuracies and errors in biometric systems,
prevent the development of discriminatory systems, and even inform the
public policies and regulations related to biometric systems. Research
related to demographic bias in ear recognition techniques can help
promote the development of more accurate, fair, and just ear recognition
systems that are less likely to produce errors or false positives for
certain groups of people and protect individual's rights and interests.
To promote research in the bias-aware ear recognition, the Unconstrained
Ear Recognition Challenge (UERC) 2023 will bring together researchers
working in the field of ear recognition and benchmark existing and new
algorithms on a common dataset and under a predefined experimental protocol.
*** How to Participate? ***
To participate in UERC 2023 fill out the following registration form:
https://docs.google.com/forms/d/e/1FAIpQLSdrXKDcor2MRsvOsdAkjptcCJSZ40NbLHo4Tc5GjP7-pzRGMQ/viewform
*** Execution ***
UERC 2023 will be organized as a two-track competition, where each track
will be focused on one specific goal. Participants will be free to enter
only a single track or compete in both. For each track, a dataset,
evaluation tool written in Python, and baseline models in Python will be
made available. A detailed description of the two tracks is given below:
Track 1: Fair Ear Recognition. The first UERC 2023 evaluation track will
collect ear recognition models and score their performance on ear images
captured in unconstrained environments. Here, the performance indicators
will include both, a measure of recognition performance as well as an
estimate of the exhibited demographic bias. Both recognition and bias
scores will contribute to the overall ranking. Participants will be free
to develop any type of model to maximize performance, while minimizing
bias. The final submission for this track will include a working
solution (source code or compiled binary), which the organizers will run
to evaluate the performance on a sequestered test data.
Track 2: Bias Mitigation. The second UERC 2023 track will address bias
mitigation strategies explicitly. Here, a baseline ResNet model (written
in Python) will be made available to the participants and the goal will
be to design bias mitigation schemes that reduce the initial bias of the
models without adversely affecting performance. Such schemes may include
additional model blocks and network components, normalization layers,
knowledge infusion mechanisms, score normalization procedures, image
preprocessing approaches and any other solution capable of reducing bias
of the predefined base model. Similarly to the first track, participants
will have to submit a working solution that the organizers will evaluate
on the sequestered test data.
*** Summary paper and co-authorship ***
The results of UERC 2023 will be published in the IJCB conference paper
authored jointly by all participants of the challenge.
*** Organizers ***
+ Asst. Prof. Žiga Emeršič, University of Ljubljana, Faculty of Computer
and Information Science, Slovenia
+ Prof. Hazım Kemal Ekenel, Istanbul Technical University, Department of
Computer Engineering, Turkey
+ Prof. Guillermo Camara-Chavez, Federal University of Ouro Preto, Brazil
+ Prof. Peter Peer, University of Ljubljana, Faculty of Computer and
Information Science, Slovenia
+ Prof. Vitomir Štruc, University of Ljubljana, Faculty of Electrical
Engineering, Slovenia, EU
*** Timeline ***
+ February 14th: Promotion of the competition, website draft,
registration opens.
+ February 15th: Kick-off of the competition: data, toolkit and
instructions made available on UERC website.
+ April 15th: Possible interim ranking.
+ May 1st: Registration closes, end of the competition.
+ May 15th: Summary paper submission.
April 27th, 2023 Daniela Lopez de Luise 
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April 27th, 2023 Daniela Lopez de Luise
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International Journal on Natural Language…
