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¡En instantes! Revisa nuestro programa de hoy y sigue capacitándote
August 31st, 2022 
Daniela Lopez de Luise DeepLearn 2022 Autumn: early registration September 14
August 30th, 2022 Daniela Lopez de Luise ******************************************************************
7th INTERNATIONAL SCHOOL ON DEEP LEARNING
DeepLearn 2022 Autumn
Luleå, Sweden
October 17-21, 2022
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Co-organized by:
Luleå University of Technology
EISLAB Machine Learning
Institute for Research Development, Training and Advice – IRDTA
Brussels/London
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Early registration: September 14, 2022
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SCOPE:
DeepLearn 2022 Autumn will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães and Las Palmas de Gran Canaria.
Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, finance, biotechnology, physics experiments, biometrics, communications, climate sciences, bioinformatics, etc. etc. Renowned academics and industry pioneers will lecture and share their views with the audience.
Most deep learning subareas will be displayed, and main challenges identified through 21 four-hour and a half courses and 2 keynote lectures, which will tackle the most active and promising topics. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely.
An open session will give participants the opportunity to present their own work in progress in 5 minutes. Moreover, there will be two special sessions with industrial and recruitment profiles.
ADDRESSED TO:
Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well. Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses. Overall, DeepLearn 2022 Autumn is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators.
VENUE:
DeepLearn 2022 Autumn will take place in Luleå, on the coast of northern Sweden, hosting a large steel industry and the northernmost university in the country. The venue will be:
Luleå University of Technology
STRUCTURE:
3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.
Full live online participation will be possible. However, the organizers highlight the importance of face to face interaction and networking in this kind of research training event.
KEYNOTE SPEAKERS:
Tommaso Dorigo (Italian National Institute for Nuclear Physics), Deep-Learning-Optimized Design of Experiments: Challenges and Opportunities
Elaine O. Nsoesie (Boston University), AI and Health Equity
PROFESSORS AND COURSES:
Sean Benson (Netherlands Cancer Institute), [intermediate] Deep Learning for a Better Understanding of Cancer
Thomas Breuel (Nvidia), [intermediate/advanced] Large Scale Deep Learning and Self-Supervision in Vision and NLP
Hao Chen (Hong Kong University of Science and Technology), [introductory/intermediate] Label-Efficient Deep Learning for Medical Image Analysis [virtual]
Jianlin Cheng (University of Missouri), [introductory/intermediate] Deep Learning for Bioinformatics
Nadya Chernyavskaya (European Organization for Nuclear Research), [intermediate] Graph Networks for Scientific Applications with Examples from Particle Physics
Sébastien Fabbro (University of Victoria), [introductory/intermediate] Learning with Astronomical Data
Efstratios Gavves (University of Amsterdam), [advanced] Advanced Deep Learning
Quanquan Gu (University of California Los Angeles), [intermediate/advanced] Benign Overfitting in Machine Learning: From Linear Models to Neural Networks
Jiawei Han (University of Illinois Urbana-Champaign), [advanced] Text Mining and Deep Learning: Exploring the Power of Pretrained Language Models
Awni Hannun (Zoom), [intermediate] An Introduction to Weighted Finite-State Automata in Machine Learning [virtual]
Tin Kam Ho (IBM Thomas J. Watson Research Center), [introductory/intermediate] Deep Learning Applications in Natural Language Understanding
Timothy Hospedales (University of Edinburgh), [intermediate/advanced] Deep Meta-Learning
Shih-Chieh Hsu (University of Washington), [intermediate/advanced] Real-Time Artificial Intelligence for Science and Engineering
Andrew Laine (Columbia University), [introductory/intermediate] Applications of AI in Medical Imaging
Tatiana Likhomanenko (Apple), [intermediate/advanced] Self-, Weakly-, Semi-Supervised Learning in Speech Recognition
Peter Richtárik (King Abdullah University of Science and Technology), [intermediate/advanced] Introduction to Federated Learning
Othmane Rifki (Spectrum Labs), [introductory/advanced] Speech and Language Processing in Modern Applications
Mayank Vatsa (Indian Institute of Technology Jodhpur), [introductory/intermediate] Small Sample Size Deep Learning
Yao Wang (New York University), [introductory/intermediate] Deep Learning for Computer Vision
Zichen Wang (Amazon Web Services), [introductory/intermediate] Graph Machine Learning for Healthcare and Life Sciences
Alper Yilmaz (Ohio State University), [introductory/intermediate] Deep Learning and Deep Reinforcement Learning for Geospatial Localization
OPEN SESSION:
An open session will collect 5-minute voluntary presentations of work in progress by participants. They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by October 9, 2022.
INDUSTRIAL SESSION:
A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry. Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event. Expressions of interest have to be submitted to david@irdta.eu by October 9, 2022.
EMPLOYER SESSION:
Organizations searching for personnel well skilled in deep learning will have a space reserved for one-to-one contacts. It is recommended to produce a 1-page .pdf leaflet with a brief description of the organization and the profiles looked for to be circulated among the participants prior to the event. People in charge of the search must register for the event. Expressions of interest have to be submitted to david@irdta.eu by October 9, 2022.
ORGANIZING COMMITTEE:
Nosheen Abid (Luleå)
Sana Sabah Al-Azzawi (Luleå)
Lama Alkhaled (Luleå)
Prakash Chandra Chhipa (Luleå)
Saleha Javed (Luleå)
Marcus Liwicki (Luleå, local chair)
Carlos Martín-Vide (Tarragona, program chair)
Hamam Mokayed (Luleå)
Sara Morales (Brussels)
Mia Oldenburg (Luleå)
Maryam Pahlavan (Luleå)
David Silva (London, organization chair)
Richa Upadhyay (Luleå)
REGISTRATION:
It has to be done at
The selection of 8 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course. During the event, participants will be free to attend the courses they wish.
Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event.
FEES:
Fees comprise access to all courses and lunches. There are several early registration deadlines. Fees depend on the registration deadline. The fees for on site and for online participants are the same.
ACCOMMODATION:
Accommodation suggestions are available at
CERTIFICATE:
A certificate of successful participation in the event will be delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
ACKNOWLEDGMENTS:
Luleå University of Technology, EISLAB Machine Learning
Rovira i Virgili University
Institute for Research Development, Training and Advice – IRDTA, Brussels/London
IEEE BigData 2022 Call for Paper deadline: Sept 3, 2022
August 30th, 2022 Daniela Lopez de Luise
Call for Papers
2022 IEEE International Conference on Big Data (IEEE BigData 2022)
http://bigdataieee.org/BigData2022/
December 17-20, 2022 – Osaka, Japan
(may move to hybrid or online depending on the pandemic situation by then)
In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data.
· The first conference IEEE Big Data 2013 had more than 400 registered participants from 40 countries ( http://bigdataieee.org/BigData2013/) and the regular paper acceptance rate is 17.0%.
· The IEEE Big Data 2019 (http://bigdataieee.org/BigData2019/ , regular paper acceptance rate: 18.7%) was held in Los Angeles, CA, Dec 9-12, 2019 with close to 1200 registered participants from 54 countries.
· The IEEE Big Data 2020 (http://bigdataieee.org/BigData2020/ , regular paper acceptance rate: 15.7%) was held online, Dec 10-13, 2020 with close to 1100 registered participants from 50 countries
· The IEEE Big Data 2021 (http://bigdataieee.org/BigData2021/ , regular paper acceptance rate: 19.9%) was held online, Dec 15-18, 2021 with close to 1089 registered participants from 52 countries
The 2022 IEEE International Conference on Big Data (IEEE BigData 2022) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications.
We solicit high-quality original research papers (and significant work-in-progress papers) in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value and Veracity), including the Big Data challenges in scientific and engineering, social, sensor/IoT/IoE, and multimedia (audio, video, image, etc.) big data systems and applications. The conference adopts single-blind review policy. We expect to have a very high quality and exciting technical program at Osaka, Japan this year. Example topics of interest includes but is not limited to the following:
1. Big Data Science and Foundations
a. Novel Theoretical Models for Big Data
b. New Computational Models for Big Data
c. Data and Information Quality for Big Data
d. New Data Standards
2. Big Data Infrastructure
a. Cloud/Grid/Stream Computing for Big Data
b. High Performance/Parallel Computing Platforms for Big Data
c. Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
d. Energy-efficient Computing for Big Data
e. Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
f. Software Techniques and Architectures in Cloud/Grid/Stream Computing
g. Big Data Open Platforms
h. New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
i. Software Systems to Support Big Data Computing
3. Big Data Management
a. Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
b. Algorithms and Systems for Big DataSearch
c. Distributed, and Peer-to-peer Search
d. Big Data Search Architectures, Scalability and Efficiency
e. Data Acquisition, Integration, Cleaning, and Best Practices
f. Visualization Analytics for Big Data
g. Computational Modeling and Data Integration
h. Large-scale Recommendation Systems and Social Media Systems
i. Cloud/Grid/Stream Data Mining- Big Velocity Data
j. Link and Graph Mining
k. Semantic-based Data Mining and Data Pre-processing
l. Mobility and Big Data
m. Multimedia and Multi-structured Data- Big Variety Data
4. Big Data Search and Mining
a. Social Web Search and Mining
b. Web Search
c. Algorithms and Systems for Big Data Search
d. Distributed, and Peer-to-peer Search
e. Big Data Search Architectures, Scalability and Efficiency
f. Data Acquisition, Integration, Cleaning, and Best Practices
g. Visualization Analytics for Big Data
h. Computational Modeling and Data Integration
i. Large-scale Recommendation Systems and Social Media Systems
j. Cloud/Grid/StreamData Mining- Big Velocity Data
k. Link and Graph Mining
l. Semantic-based Data Mining and Data Pre-processing
m. Mobility and Big Data
n. Multimedia and Multi-structured Data- Big Variety Data
5. Big Data Learning and Analytics
a. Predictive analytics on Big Data
b. Machine learning algorithms for Big Data
c. Deep learning for Big Data
d. Feature representation learning for Big Data
e. Dimension reduction for Big Data
f. Physics informed Big Data learning
6. Data Ecosystem
a. Data ecosystem concepts, theory, structure, and process
b. Ecosystem services and management
c. Methods for data exchange, monetization, and pricing
d. Trust, resilience, privacy, and security issues
e. Privacy preserving Big Data collection/analytics
f. Trust management in Big Data systems
g. Ecosystem assessment, valuation, and sustainability
h. Experimental studies of fairness, diversity, accountability, and transparency
7. Big Data Applications
a. Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
b. Big Data Analytics in Small Business Enterprises (SMEs),
c. Big Data Analytics in Government, Public Sector and Society in General
d. Real-life Case Studies of Value Creation through Big Data Analytics
e. Big Data as a Service
f. Big Data Industry Standards
g. Experiences with Big Data Project Deployments
INDUSTRIAL & Government Track
The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages).
The Government Track welcomes papers discussing the usefulness and need for publicly-contribution big data and open data and their use. Specifically, data utilization scenarios, needs analysis, data utilization obstacle analysis and solutions, data integration processes, interfaces as data utilization solutions, visualization, use cases, evidence-based policy making, building an ecosystem for solving social issues, analyzing their cases, comparing international and regional differences, and conducting comparative surveys before and after specific events (like Covid-19). We are also looking for other big data solutions related to national and local governments, and public services.
Please submit an extended abstract (2-4 pages) OR a full-length paper (up to 10 pages) through the online submission page (Industrial & Government Track dedicated page)
Paper Submission:
Please submit a full-length paper (up to 10 page IEEE 2-column format, reference pages counted in the 10 pages ) through the online submission system.
https://wi-lab.com/cyberchair/2022/bigdata22/index.php
Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to “formatting instructions” below).
https://www.ieee.org/conferences/publishing/templates.html
Visa Application:
Japan has opened its border to allow foreigners to visit Japan, IEEE BigData 2022 has hired a Japanese company to assist all participants from over the world to get a visa to enter Japan for the conference. The visa application process is very smooth and detailed information is already posted in the conference website.
Important Dates:
Electronic submission of full papers: Sept 3, 2022
Notification of paper acceptance: Oct 25, 2022
Camera-ready of accepted papers: Nov 15, 2022
Conference: Dec 17-20, 2022
LowCost3D – call for papers
August 30th, 2022 Daniela Lopez de Luise ***** 15-16 December 2022
***** Wuerzburg, Germany
***** https://lc3d.fbk.eu/
***** Wuerzburg, Germany
***** https://lc3d.fbk.eu/
LowCost 3D is a series of international workshops on low-cost
three-dimensional sensor systems and tools. Ranging from low-cost
acquisition devices like handheld scanning systems over inexpensive
photogrammetric algorithms to processing software and applications.
Started by Prof. Frank Neitzel from Technical University Berlin and
Prof. Ralf Reulke from Humboldt-University in Berlin, the workshops were
organized and hosted alternating between these two universities. Since
2011 four workshops took place in Berlin, in 2017 the 5th workshop was
hosted by the HafenCity University Hamburg and in 2019 the 6th edition
of the workshop took place at INSA Strasbourg, France.
The 7th edition of the ISPRS LowCost3D workshop will be organized in
Würzburg (Germany) during 15-16 December 2022 at the Graduate School,
University of Würzburg.
Abstract Submission: 16 September 2022
The main focus of the workshop is to discuss new developments in
low-cost 3D sensor technology, algorithms, and applications. Topics include:
Image- and range-based low-cost sensor systems including low-cost
scanning systems
– Low-cost sensor calibration and system integration
– Accuracy investigations in low-cost sensor systems
– Low-cost sensors for automatic data acquisition
– Automation in data registration
– Point cloud analysis
– Image matching and 3D reconstruction
– Low-cost sensors including open-source and free algorithms for
terrestrial and UAV 3D modeling
– Web-based tools for terrestrial 3D modeling
– 4D modelling
– Low-cost systems for Virtual and Augmented Reality applied to the
visualization of 3D models
– Low-cost solutions for 3D printing
(2nd Cfp) 4th Springer icSoftComp2022: [SI: SNCS journal] [Deadline: 31-Aug] [Hybrid mode](Proceedings by Springer CCIS)
August 30th, 2022 Daniela Lopez de Luise |
*** Call for Paper ***
Springer 2022 4th International Conference on Soft Computing and its Engineering Applications (icSoftComp2022)
https://www.charusat.ac.in/icSoftComp2022/index.php
Charotar University of Science and Technology (CHARUSAT), Changa, India December 09-10, 2022
[Hybrid mode]
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Conference proceedings by Springer CCIS Series (Scopus indexed) Conference series link: https://link.springer.com/conference/icsoftcomp
Paper submission link: https://equinocs.springernature.com/service/icSoftComp2022
============== Important Notes: ============== – Conference is in Hybrid mode (onsite and online) – icSoftComp2022 follows a double-blind peer review system. – Please follow the Springer CCIS format for paper submission. – Authors of selected papers will be invited to submit extended article versions for a post-conference special issue of peer reviewed Scopus indexed journal (Springer Nature Computer Science)
2022 4th International Conference on Soft Computing and its Engineering Applications (icSoftComp2022) aims to provide an excellent international forum to the researchers, academicians, students, and professionals in the areas of computer science and engineering to present their research, knowledge, new ideas and innovations. It will exhibit an exciting technical program. It will also feature high-quality Tutorials and Workshops, Industry Panels and Exhibitions, as well as Keynotes from prominent research and industry leaders.
================ Keynote Speakers: ================ – Dr. Dilip Kumar Pratihar, Indian Institute of Technology Kharagpur, Kharagpur, India – Dr. Witold Pedrycz, University of Alberta, Alberta, Canada – Dr. Dimitrios A. Karras, National and Kapodistrian University of Athens, Greece – Dr. Massimiliano Cannata, SUPSI, Canobbio, Switzerland
================ Paper Publication: ================ The accepted and presented papers will be published as proceedings with Springer in their prestigious Communications in Computer and Information Science (CCIS) series. Indexed by Scopus, DBLP, Ei Compendex, Google Scholar, and Springerlink
================ Journal Publication: ================ Authors of selected papers will be invited to submit extended article versions for post-conference special issue of peer-reviewed journal. · Springer Nature Computer Science Journal (Scopus)
================ Paper Submission: ================ We are now open for technical paper submission. icSoftComp2022 solicits papers on all aspects of Soft computing and its engineering applications for a smart and better world. The topics of the conference include, but are not limited to the following:
============== Important Dates: ==============
============================ Previous conference proceedings: ============================ – icSoftComp2021 https://link.springer.com/book/10.1007/978-3-031-05767-0 – icSoftComp2020 https://www.springer.com/gp/book/9789811607073 – icSoftComp2017 https://ieeexplore.ieee.org/xpl/conhome/8269416/proceeding
Please join icSoftComp WhatsApp group to get updates: https://chat.whatsapp.com/CnkrBjvMcuu1ksjQGi67Ak
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