Deadline Extension – CFP RO-MAN 2022 Workshop on Machine Learning for HRI: Bridging the Gap between Action and Perception

July 5th, 2022 Daniela Lopez de Luise

CALL FOR PAPERS

The full-day virtual workshop:

Machine Learning for HRI: Bridging the Gap between Action and Perception (ML-HRI)

In conjunction with the 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) – August 22, 2022   

Webpage: https://ml-hri2022.ivai.onl/

I. Aim and Scope

A key factor for the acceptance of robots as partners in complex and dynamic human-centered environments is their ability to continuously adapt their behavior. This includes learning the most appropriate behavior for each encountered situation based on its specific characteristics as perceived through the robots senors. To determine the correct actions the robot has to take into account prior experiences with the same agents, their current emotional and mental states, as well as their specific characteristics, e.g. personalities and preferences. Since every encountered situation is unique, the appropriate behavior cannot be hard-coded in advance but must be learned over time through interactions. Therefore, artificial agents need to be able to learn continuously what behaviors are most appropriate for certain situations and people based on feedback and observations received from the environment to enable more natural, enjoyful, and effective interactions between humans and robots.

This workshop aims to attract the latest research studies and expertise in human-robot interaction and machine learning at the intersection of rapidly growing communities, including social and cognitive robotics, machine learning, and artificial intelligence, to present novel approaches aiming at integrating and evaluating machine learning in HRI. Furthermore, it will provide a venue to discuss the limitations of the current approaches and future directions towards creating robots that utilize machine learning to improve their interaction with humans.

II. Keynote Speakers and Panelists

  1. Dorsa Sadigh – Stanford University – USA
  2. Oya Celiktutan – King's College London – UK
  3. Sean Andrist – Microsoft – USA
  4. Stefan Wermter – University of Hamburg – Germany

III. Submission

  1. For paper submission, use the following EasyChair web link: Paper Submission.
  2. Use the RO-MAN 2022 format: RO-MAN Papers Templates.
  3. Submitted papers should be 4-6 pages for regular papers and 2 pages for position papers.

    The primary list of topics covers the following points (but not limited to):

  • Autonomous robot behavior adaptation
  • Interactive learning approaches for HRI
  • Continual learning
  • Meta-learning
  • Transfer learning
  • Learning for multi-agent systems
  • User adaptation of interactive learning approaches
  • Architectures, frameworks, and tools for learning in HRI
  • Metrics and evaluation criteria for learning systems in HRI
  • Legal and ethical considerations for real-word deployment of learning approaches

IV. Important Dates

  1. Paper submission: June 17, 2022 July 15, 2022 (AoE)
  2. Notification of acceptance: August 1, 2022 August 7, 2022 (AoE)
  3. Camera ready: August 14, 2022 (AoE)
  4. Workshop: August 22, 2022

V. Organizers

  1. Oliver Roesler – IVAI – Germany
  2. Elahe Bagheri – IVAI – Germany
  3. Amir Aly – University of Plymouth – UK
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CFP – IJCB 2022 – Special Session – Recent Advances in Detecting Manipulation Attacks on Biometric Systems (ADMA-2022)

July 5th, 2022 Daniela Lopez de Luise
Recent Advances in Detecting Manipulation Attacks on Biometric Systems (ADMA-2022)

IJCB 2022 – Special Session

 

Website: https://sites.google.com/view/ijcb-ss-adma-2022/home

 

 

Manipulated attacks in biometrics via modified images/videos and other material-based techniques such as presentation attacks and deep fakes have become a tremendous threat to the security world owing to increasingly realistic spoofing methods. Hence, such manipulations have triggered the need for research attention towards robust and reliable methods for detecting biometric manipulation attacks. The recent inclusion of manipulation/generation methods such as auto-encoder and generative adversarial network approaches combined with accurate localisation and perceptual learning objectives added an extra challenge to such manipulation detection tasks. Due to this, the performance of existing state-of-the-art manipulation detection methods significantly degrades in the unknown scenarios. Apart from this, real-time processing, manipulation on low-quality medium, limited availability of data, and inclusion of these manipulation detection techniques for forensic investigation are yet to be widely explored. Hence, this special session aims to profile recent developments and push the border of the digital manipulation detection technique on biometric systems.

 

We invite practitioners, researchers and engineers from biometrics, signal processing, material science, mathematics, computer vision and machine learning to contribute their expertise to underpin the highlighted challenges. Further, this special session promote cross disciplinary research by inviting the partitioner in the field of psychology where one can perform the human observer (or super-recogniser) analysis to detect attacks.

 

Topics of interest include but not limited to:

             Deepfake manipulation and detection technique

             Novel generalised PAD to unknown attacks

             Image manipulation techniques datasets

             Database in image and video manipulation, and attacks

             Privacy preserving techniques in digital manipulation attack detection

             Image and video synthesis in PAD

             Image and video manipulation generation and detection

             Human observer analysis in detecting the manipulated biometric images

             Novel sensors for detecting manipulated attacks

             Bias analyses and mitigation in attack detection algorithms

 

Submission Guidelines:

             Submit your papers at: https://cmt3.research.microsoft.com/IJCB2022 in a special session track.

             Paper presented at ADMA-2022 will be published as part of the IJCB2022 and should, therefore, follow the same guideline as the main conference.

             Page limit: A paper can be up to 8 pages including figures and tables, plus additional pages for references only. If the 7th and 8th pages contain any content other than references, they will incur a cost of USD100 per page.

             Papers will be double-blind peer reviewed by at least three reviewers. Please remove author names, affiliations, email addresses, etc. from the paper. Remove personal acknowledgments.

 

Important Dates:

             Full Paper Submission: July 27, 2022, 23:59:59 PDT

             Acceptance Notice: August 17, 2022, 23:59:59 PDT

             Camera-Ready Paper: August 24, 2022, 23:59:59 PDT

 

Organizing Committee:

Assoc. Prof. Abhijit Das, BITS Pilani, India

Prof. Raghavendra Ramachandra, NTNU, Norway

Meiling Fang, Fraunhofer IGD, Germany

Dr. Naser Damer, Fraunhofer IGD, Germany

Prof. Hu Han, CAS, China

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DeepLearn 2023 Winter: early registration July 4

July 5th, 2022 Daniela Lopez de Luise
******************************************************************
 
 
 
8th INTERNATIONAL SCHOOL ON DEEP LEARNING
 
 
 
DeepLearn 2023 Winter
 
 
 
Bournemouth, UK
 
 
 
January 16-20, 2023
 
 
 
 
 
 
***********
 
 
 
Co-organized by:
 
 
 
Department of Computing and Informatics
 
Bournemouth University
 
 
 
Institute for Research Development, Training and Advice – IRDTA
 
Brussels/London
 
 
 
******************************************************************
 
 
 
Early registration: July 4, 2022
 
 
 
******************************************************************
 
 
 
SCOPE:
 
 
 
DeepLearn 2022 Winter 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, Las Palmas de Gran Canaria and Luleå.
 
 
 
Deep learning is a branch of artificial intelligence covering a spectrum of current exciting 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 24 four-hour and a half courses and 3 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 2023 Winter 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 2023 Winter will take place in Bournemouth, a coastal resort town on the south coast of England. The venue will be:
 
 
 
Talbot Campus
 
Bournemouth University
 
 
 
 
 
 
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:
 
 
 
Yi Ma (University of California, Berkeley), CTRL: Closed-Loop Data Transcription via Rate Reduction
 
 
 
Daphna Weinshall (Hebrew University of Jerusalem), Curriculum Learning in Deep Networks
 
 
 
Eric P. Xing (Carnegie Mellon University), It Is Time for Deep Learning to Understand Its Expense Bills
 
 
 
PROFESSORS AND COURSES: (to be completed)
 
 
 
Mohammed Bennamoun (University of Western Australia), [intermediate/advanced] Deep Learning for 3D Vision
 
 
 
Matias Carrasco Kind (University of Illinois, Urbana-Champaign), [intermediate] Anomaly Detection
 
 
 
Nitesh Chawla (University of Notre Dame), [introductory/intermediate] Graph Representation Learning
 
 
 
Seungjin Choi (Intellicode), [introductory/intermediate] Bayesian Optimization over Continuous, Discrete, or Hybrid Spaces
 
 
 
Sumit Chopra (New York University), [intermediate] Deep Learning in Healthcare
 
 
 
Luc De Raedt (KU Leuven), [introductory/intermediate] Statistical Relational and Neurosymbolic AI
 
 
 
Marco Duarte (University of Massachusetts, Amherst), [introductory/intermediate] Explainable Machine Learning
 
 
 
João Gama (University of Porto), [introductory] Learning from Data Streams: Challenges, Issues, and Opportunities
 
 
 
Claus Horn (Zurich University of Applied Sciences), [intermediate] Deep Learning for Biotechnology
 
 
 
Zhiting Hu (University of California, San Diego) & Eric P. Xing (Carnegie Mellon University), [intermediate/advanced] A “Standard Model” for Machine Learning with All Experiences
 
 
 
Nathalie Japkowicz (American University), [intermediate/advanced] Learning from Class Imbalances
 
 
 
Gregor Kasieczka (University of Hamburg), [introductory/intermediate] Deep Learning Fundamental Physics: Rare Signals, Unsupervised Anomaly Detection, and Generative Models
 
 
 
Karen Livescu (Toyota Technological Institute at Chicago), [intermediate/advanced] Speech Processing: Automatic Speech Recognition and beyond (to be confirmed)
 
 
 
David McAllester (Toyota Technological Institute at Chicago), [intermediate/advanced] Information Theory for Deep Learning
 
 
 
Dhabaleswar K. Panda (Ohio State University), [intermediate] Exploiting High-performance Computing for Deep Learning: Why and How?
 
 
 
Fabio Roli (University of Cagliari), [introductory/intermediate] Adversarial Machine Learning
 
 
 
Richa Singh (Indian Institute of Technology Jodhpur), [introductory/intermediate] Trusted AI
 
 
 
Kunal Talwar (Apple), [introductory/intermediate] Foundations of Differentially Private Learning
 
 
 
Tinne Tuytelaars (KU Leuven), [introductory/intermediate] Continual Learning in Deep Neural Networks
 
 
 
Lyle Ungar (University of Pennsylvania), [intermediate] Natural Language Processing using Deep Learning
 
 
 
Bram van Ginneken (Radboud University Medical Center), [introductory/intermediate] Deep Learning for Medical Image Analysis
 
 
 
Yu-Dong Zhang (University of Leicester), [introductory/intermediate] Convolutional Neural Networks and Their Applications to COVID-19 Diagnosis
 
 
 
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 January 8, 2023.
 
 
 
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 January 8, 2023.
 
 
 
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 company 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 January 8, 2023.
 
 
 
ORGANIZING COMMITTEE:
 
 
 
Rashid Bakirov (Bournemouth, local co-chair)
 
Marcin Budka (Bournemouth)
 
Vegard Engen (Bournemouth)
 
Nan Jiang (Bournemouth, local co-chair)
 
Carlos Martín-Vide (Tarragona, program chair)
 
Sara Morales (Brussels)
 
David Silva (London, organization chair)
 
 
 
REGISTRATION:
 
 
 
It has to be done at
 
 
 
 
 
 
The selection of 8 courses requested in the registration template is only tentative and non-binding. For the sake of organization, 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 participation 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:
 
 
 
Bournemouth University
 
 
 
Rovira i Virgili University
 
 
 
Institute for Research Development, Training and Advice – IRDTA, Brussels/London
      
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deadline for Symposium on Computational Intelligence for Engineering Solutions extended to July 15

July 5th, 2022 Daniela Lopez de Luise

we would like to propose a deadline

extension to 15 July 2022.

This will be the only and final deadline

extension.

************************************************************************

 

IEEE Symposium on Computational Intelligence for Engineering

Solutions (IEEE CIES)

 

https://www.ieeessci2022.org/symposia_cies.html

 

Part of IEEE Series of Symposia on Computational Intelligence,

Singapore, December 4-7, 2022, https://www.ieeessci2022.org/

 

Developments in Engineering are characterized by a growing

complexity, which is balanced by an extensive utilization of

computational resources. This complexity is not only a feature of

engineering systems, processes and products, it is primarily a key

attribute of the respective algorithms for analysis, control and

decision-making to develop those engineering solutions. To cope

with complexity in this broad spectrum of demands, Computational

Intelligence is implemented increasingly in virtually all

engineering disciplines. This emerging approach provides a basis

for developments of a new quality. This Symposium is focused on the

utilization of Computational Intelligence in this context in the

entire field of engineering. Examples concern the control of

processes of various kinds and for various purposes, monitoring

with sensors, smart sensing, system identification,

decision-support and assistance systems, visualization methods,

prediction schemes, the solution of classification problems,

response surface approximations, the formulation of surrogate

models, etc. The engineering application fields may comprise, for

example, bioengineering with prostheses design and control, civil

and mechanical engineering processes, systems and structures

concerned with vehicles, aircraft or bridges, industrial and

systems engineering with design and control of power systems,

electrical and computer engineering with developments in robotics,

etc. All kinds of approaches from the field of Computational

Intelligence are welcome. As a part of the Symposium special

attention is paid to sustainable engineering solutions to address

current and future challenges of environmental changes and

uncertainty. This includes developments dealing with climate

change, environmental processes, disaster warning and management,

infrastructure security, lifecycle analysis and design, etc.

Events, disasters and issues under consideration may be natural

such as earthquakes or tsunamis, man-made such as human failure or

terrorist attacks, or a combination thereof including secondary

effects such as failures in nuclear power plants, which may be

critical for systems, the environment and the society. Developments

which include a comprehensive consideration of uncertainty and

techniques of reliable computing are explicitly invited. These may

involve probabilistic including Bayesian approaches, interval

methods, fuzzy methods, imprecise probabilities and further

concepts. In this context robust design is of particular interest

with all its facets as a basic concept to develop sustainable

engineering solutions.

 

*********************************************************************

 

Topics

  Complex engineering systems, structures and processes

  Intelligent analysis, control and decision-making

  Management and processing of uncertainties

  Problem solution in uncertain and noisy environments

  Reliable computing

  Sustainable solutions

  Infrastructure security

  Climate change

  Environmental processes

  Disaster warning and management

  Lifecycle analysis and design

  Automotive systems

  Monitoring

  Smart sensing

  System identification

  Decision-support and assistance systems

  Visualization methods

  Prediction schemes

  Classification methods, cluster analysis

  Response surface approximations and surrogate models

  Sensitivity analysis

  Robust design, reliability-based design, performance-based design

  Risk analysis, hazard analysis, risk and hazard mitigation

  Optimization methods, evolutionary concepts

  Probabilistic and statistical methods

  Simulation methods, Monte-Carlo and quasi Monte-Carlo

  Bayesian approaches / networks

  Artificial Neural Networks

  Imprecise probabilities

  Evidence theory

  p-box approach

  Fuzzy probability theory

  Interval methods

  Fuzzy methods

  Convex modeling

  Information gap theory

*********************************************************************

Symposium Chairs

 

Michael Beer

Leibniz University Hannover

 

Vladik Kreinovich

University of Texas at El Paso

 

Rudolf Kruse

Otto-von-Guericke University

 

*********************************************************************

 

Important dates:

 

Paper Submission: Friday, 15th July 2022

Paper Acceptance: Thursday, 1st September 2022

Full Manuscript Submission: Monday. 19th September 2022

Early Registration: Monday, 26th September 2022

Conference Dates: 4th – 7th December 2022

 

**********************************************************************

 

Submission logistics: see https://www.ieeessci2022.org/

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IEEE SSCI 2022 Deadline Extension to 15 July 2022

July 5th, 2022 Daniela Lopez de Luise

###########################################################################

 

IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2022)

December 4 – December 7, 2022 | Singapore

http://ieeessci2022.org

 

****Call for Papers****

 

###########################################################################

 

****************

****Synopsis****

****************

 

IEEE SSCI is an established flagship annual international series of

symposia on computational intelligence sponsored bythe IEEE

Computational Intelligence Society to promote and stimulate

discussion on the latest theory, algorithms,applications and

emerging topics on computational intelligence. By co-locating

multiple symposia under one roof, eachdedicated to a specific topic

in the CI domain, IEEE SSCI aims to encourage cross-fertilization

of ideas and provide aunique platform for top researchers,

professionals, and students from all around the world to discuss

and present theirfindings. IEEE SSCI 2022 will feature keynote

addresses, tutorials, panel discussions and special sessions, all

of whichare open to all participants. The conference proceedings of

the IEEE SSCI will be included in the IEEE Xplore andindexed by all

major databases.

 

List of Confirmed Symposia and Special Sessions

 

* Adaptive Dynamic Programming and Reinforcement Learning(IEEE ADPRL)

* Artificial Life (IEEE ALIFE)

* Automated Algorithm Design, Configuration and Selection (IEEE AADCS)

* CI Applications in Smart Grid (IEEE CIASG)

* CI and Ensemble Learning (IEEE CIEL)

* CI for Astroinformatics (IEEE CIAstro)

* CI for Brain Computer Interfaces (IEEE CIBCI)

* CI for Engineering Solutions (IEEE CIES)

* CI for Human-like Intelligence (IEEE CIHLI)

* CI for Multimedia Signal and Vision Processing (IEEE CIMSIVP)

* CI for Security and Defense Applications (IEEE CISDA)

* CI in Agriculture (IEEE CIAg)

* CI in Big Data (IEEE CIBD)

* CI in Biometrics and Identity Management (IEEE CIBIM)

* CI in Control and Automation (IEEE CICA)

* CI in Cyber Security (IEEE CICS)

* CI in Data Mining (IEEE CIDM)

* CI in Dynamic and Uncertain Environment (IEEE CIDUE)

* CI in Feature Analysis, Selection and Learning in Image and Pattern Recognition (IEEE FASLIP)

* CI in Healthcare and E-health (IEEE CICARE)

* CI in IoT and Smart Cities (IEEE CIIoT)

* CI in Remote Sensing (IEEE CIRS)

* CI in Vehicle and Transportation Systems (IEEE CIVTS)

* Cooperative Metaheuristics (IEEE SCM)

* Deep Learning (IEEE DL)

* Differential Evolution (IEEE SDE)

* Ethical, Social and Legal Implications of ArtificialIntelligence (IEEE ETHAI)

* Evolutionary Neural Architecture Search and Applications(IEEE ENASA)

* Evolutionary Scheduling and CombinatorialOptimisation (IEEE ESCO)

* Evolving and Autonomous Learning Systems (IEEE EALS)

* Explainable Data Analytics in Computational Intelligence (IEEE EDACI)

* Foundations of CI (IEEE FOCI)

* Immune Computation (IEEE IComputation)

* Intelligent Agents (IEEE IA)

* Model-Based Evolutionary Algorithms (IEEE MBEA)

* Multi-agent System Coordination and Optimization (IEEE MASCO)

* Multicriteria Decision-Making (IEEE MCDM)

* Nature-Inspired Computation in Engineering (IEEE NICE)

* Neuromorphic Cognitive Computing (IEEE SNCC)

* Robotic Intelligence in Informationally StructuredSpace (IEEE RiiSS)

* Swarm Intelligence Symposium (IEEE SIS)

 

List of Confirmed Special Sessions

* Advancing Capabilities of Simulation Models with Computational Intelligence (ASM)

* Artificial Intelligence-based Uncertainty Quantification (AUQ)

* CI in Soil and Water Management (SWM)

* Conjunection of Quantum Computing and Evolutionary Computation (EVO-QANTUM)

* Evolutionary Transfer Learning and Domain Adaptation (EADLA)

* Evolving Deep and Transfer Learning Models for Computer Vision and Medical Imaging (ECV)

* Games (GAMES)

* Genetic Programming and Machine Learning for Scheduling (GPMLS)

* Human and Machine Intelligence in CollaborativeDecision Making (HMI)

* Physics-Informed Computational Intelligence: Theories, Models and Application (PHYCI)

 

***********************

****Important Dates****

***********************

 

* Symposia/Session/Tutorial Proposals  Sunday, 1st May 2022 (Passed)

* Paper Submission Deadline                    Friday, 15th July 2022

* Notification to Authors                           Thursday, 1st September 2022

* Full Manuscript Submission                   Monday. 19th September 2022

* Early Bird Registration               Monday, 26th September 2022

* IEEE SSCI 2022 Conference                     4th December to 7th December 2022

 

****************************

****Organizing Committee****

****************************

 

* Advisory Chairs

Kay-Chen TAN                  City University of Hong Kong

Yew-Soon ONG                Nanyang Technological University

 

* General Chairs

Ah-Hwee TAN                  Singapore Management University

Dipti SRINIVASAN           National University of Singapore

Chunyan MIAO                Nanyang Technological University

 

* Program Chairs

Hisao ISHIBUCHI                            Southern University of Science andTechnology

Chee-Keong KWOH                       Nanyang Technological University

 

* Finance Chair

Jian-Chao YAO                 DSO National Laboratories

 

* Keynote / Tutorial Chairs

Yaochu JIN                        Bielefeld University

Mahardhika PRATAMA  Nanyang Technological University

 

* Exhibit / Competition Chair

Chi-Keong GOH               AI2Labs

 

* Publication Chairs

Anupam TRIVEDI                           National University of Singapore

Keeley CROCKETT                          Manchester Metropolitan University

 

* Publicity Chairs

Teck-Hou TENG               ST Engineering

Catherine HUANG                         McAfee AI Research

Pauline C. HADDOW      Norwegian University of Science and Technology                            

Jialin LIU                            Southern University of Science and Technology

 

* Local Organizing Chairs

Di WANG                                         Nanyang Technological University

Zhaoxia WANG                Singapore Management University

Hao ZHANG                      Nanyang Technological University

 

* Submission Chair

Hao ZHANG                      Nanyang Technological University

 

* Webmaster

Shanthoshigaa                 Singapore Management University

 

********************************

****Sponsoring Organizations****

********************************

 

IEEE Computational Intelligence Society

IEEE Singapore Section

Singapore Exhibition & Convention Bureau

 

*******************************

****Organizing Institutions****

*******************************

 

Singapore Management University

National University of Singapore

Nanyang Technological University

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