The 4th International Conference on Activity and Behavior Computing October 27th - 29th, 2022, London, United Kingdom (Hybrid)
Paper deadline: July 31st, 2022 (Extended)

Welcome to ABC2022!


Human Activity Recognition has been researched in thousands of papers so far, with mobile / environmental sensors in ubiquitous / pervasive domains, and with cameras in vision domains. As well, Human Behavior Analysis is also explored for long-term health care, rehabilitation, emotion recognition, human interaction, and so on. However, many research challenges remain for realistic settings, such as complex and ambiguous activities / behavior, optimal sensor combinations, (deep) machine learning, data collection, platform systems, and killer applications.

In this conference, we comprehend such research domains as ABC: Activity and Behavior Computing, and provide an open and a confluent place for discussing various aspects and the future of the ABC.

Keynotes


Björn W. Schuller, Fellow IEEE

Imperial College London/UK and University of Augsburg/Germany

Automatic Anthropologic Activity and Affect Assessment: About Advancing an Art

Machines recognising our activity and affect bear great potential from improved human-computer interaction to multimedia retrieval, health monitoring, and many more. Here, starting with the history of Affective Computing in particular, we shall move to the state-of-the-art in technical modelling. This will be supported by results and findings from recent competitive research challenges in the field. From this, current challenges such as dealing with less visited affective states, affect regulation, cultural and interpersonal differences, among others, will be distilled. Finally, we shall elaborate on future scenarios of Affective Computing considering going Big Data, ground truth modelling, and prognosis. Will computers soon know our activity and affect better than we do?

Björn W. Schuller

Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany. He is Full Professor of Artificial Intelligence and the Head of GLAM - the Group on Language, Audio, & Music - at Imperial College London/UK, Full Professor and Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg/Germany, co-founding CEO and current CSO of audEERING – an Audio Intelligence company based near Munich and in Berlin/Germany, and permanent Visiting Professor at HIT/China amongst other Professorships and Affiliations. Previous stays include Full Professor at the University of Passau/Germany, Key Researcher at Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. He is a Fellow of the IEEE and Golden Core Awardee of the IEEE Computer Society, Fellow of the BCS, Fellow of the ISCA, Fellow and President-Emeritus of the AAAC, and Senior Member of the ACM. He (co-)authored 1,000+ publications (40k+ citations, h-index=100+), is Field Chief Editor of Frontiers in Digital Health and was Editor in Chief of the IEEE Transactions on Affective Computing amongst manifold further commitments and service to the community. His 40+ awards include having been honoured as one of 40 extraordinary scientists under the age of 40 by the WEF in 2015. First-in-the-field of Affective Computing and Sentiment analysis challenges such as AVEC, ComParE, or MuSe have been initiated and by now organised overall more than 30 times by him. He is an ERC Starting and DFG Reinhart-Koselleck Grantee, and consultant of companies such as Barclays, GN, Huawei, Informetis, or Samsung.


Nicholas Lane

University of Cambridge / Samsung AI


Cecilia Mascolo

University of Cambridge / United Kingdom

Wear-to-compute? Challenges of Wearable Computing for Health

Wearable devices are becoming pervasive in our lives, from smart watches measuring our heart rate to wearables for the ear accompanying us in every virtual meeting. These devices are becoming, in theory, very good proxies for human behaviour. Yet, making the inference from the raw sensor data to individuals’ behaviour remains difficult. In this talk I will discuss where commercial systems have gotten to today and highlight the open challenges that these technologies still face before they can be trusted health measurement proxies. Namely, the ability to work in the wild, the sensitivity of the data versus centralisation of computation, the uncertainty of the prediction over the data. I will use examples from my group's ongoing research on on-device machine learning, “earable” sensing and uncertainty estimation for health application in collaboration with epidemiologists and clinicians.

Cecilia Mascolo

Cecilia Mascolo is the mother of a teenage daughter but also a Full Professor of Mobile Systems in the Department of Computer Science and Technology, University of Cambridge, UK. She is director of the Centre for Mobile, Wearable System and Augmented Intelligence. She is also a Fellow of Jesus College Cambridge and the recipient of an ERC Advanced Research Grant. Prior joining Cambridge in 2008, she was a faculty member in the Department of Computer Science at University College London. She holds a PhD from the University of Bologna. Her research interests are in mobile systems and machine learning for mobile health. She has published in a number of top tier conferences and journals in the area and her investigator experience spans projects funded by Research Councils and industry. She has served as steering, organizing and programme committee member of mobile and sensor systems, data science and machine learning conferences. More details at www.cl.cam.ac.uk/users/cm542

Program


Schedule

You can import to your calendar in your timezone from the [+] below.

Program

Tentative, Times are in GMT


Oct. 27th (Thursday), 2022

Registration, 8:30-9:00

Breakfast, 9:00-9:30

Welcome, 9:30-9:50

Session 1: Security / Comfort, 9:50-11:10

      Function Estimation of Multiple IoT Devices by Communication Traffic Analysis, Yuichi Hattori (Kyushu Institute of Technology)*; Yutaka Arakawa (Kyushu University); Sozo Inoue (Kyushu Institute of Technology)
      (k,n)-Threshold Encoding Scheme for RFID-based Real-Time Event Extraction and Its Application to ADL Recognition, Masayuki Numao (The University of Electro Communications)*; Ryota Fukumoto (The University of Electro Communications)
      Toward Human Thermal Comfort Sensing: New Dataset and Analysis of Heart Rate Variability (HRV) Under Different Activities, Tahera Hossain (Aoyama Gakuin University)*; Yusuke Kawasaki (Aoyama Gakuin University); Kazuki Honda (Aoyama Gakuin University); Kizito Nkurikiyeyezu (Aoyama Gakuin University); Guillaume Lopez (Aoyama Gakuin University)
      Touching with eye contact and vocal greetings increases the sense of security, Miyuki Iwamoto (Kyoto University)*; Atsushi Nakazawa (Kyoto University)

Keynote 1, 11:30-12:30

      Nicholas D. Lane (University of Cambridge / Samsung AI),

Lunch Break, 12:30-13:30

Session 2: Emotion, 13:30-14:50

      Optimal EEG Electrode Set for Emotion Recognition From Brain Signals: An Empirical Quest, Rumman Ahmed Prodhan (University of Asia Pacific); Sumya Akter (University of Asia Pacific ); Tanmoy Sarkar Pias (Virginia Tech)*; Akhtaruzzaman Adnan (UAP)
      Translation-Delay-Aware Emotional Avatar System for Online Communication Support, Tomoya Suzuki (Aoyama Gakuin University)*; Akihito Taya (Aoyama Gakuin University); Yoshito Tobe (Aoyama Gakuin University); Guillaume Lopez (Aoyama Gakuin University)
      Psychological Analysis in Human-Robot Collaboration from Workplace Stress Factors: A Review, Nazmun Nahid (Kyushu Institute of Technology)*; XINYI MIN (kyushu institute of technology); Md Atiqur Rahman Ahad (University of East London); Sozo Inoue (Kyushu Institute of Technology)
      Understanding Mental Health Using Ubiquitous Sensors and Machine Learning: Challenges Ahead, Tahia Tazin (Kyushu Institute of Technology)*; Tahera Hossain (Kyushu Institute of Technology); Shahera Hossain (Kyushu Institute of Technology); Sozo Inoue (Kyushu Institute of Technology)

Keynote 2, 15:10-16:10

      Björn W. Schuller, Fellow IEEE (Imperial College London / UK and University of Augsburg / Germany),

Workshop - Mental Health, 16:10-17:10

      Detection and Classification of Acute Psychological Stress in Free-Living: Challenges and Achievements, Mert Sevil (Illinois Institute of Technology); Mudassir Rashid (Illinois Institute of Technology); Mohammad Reza Askari (Illinois Institute of Technology); Lisa Sharp (UIC); Laurie Quinn (UIC); ALI CINAR (Illinois Institute of Technology)*
      Classification of Stress via Ambulatory ECG and GSR Data, Zac Dair (Munster Technological University)*; Muhammad Muneeb Saad (Cork Institute of Technology, Ireland); Urja Pawar (CIT); Samantha Dockray (University College Cork); Ruairí D O'Reilly (Cork Institute of Technology)
      A Multi-Sensor Fusion Method For Stress Recognition, Leonardo Alchieri (Università della Svizzera Italiana (USI))*; Nouran Abdalazim (Università della Svizzera Italiana (USI); Lidia Alecci (Università della Svizzera Italiana (USI); Silvia Santini (Università della Svizzera italiana (USI)); Shkurta Gashi (Università della Svizzera italiana)
      Anxolotl, an Anxiety Companion App - Stress Detection, Matilde Pato (Instituto Superior de Engenharia de Lisboa)*; Nuno Gomes ( Instituto Superior de Engenharia de Lisboa); Pedro Santos (Instituto Superior de Engenharia de Lisboa); André Lourenço (Instituto Superior de Engenharia de Lisboa); Lourenço Rodrigues (Instituto Superior de Engenharia de Lisboa)
      Detection of self-reported stress level from wearable sensor data using machine learning and deep learning-based classifiers: Is it feasible?, Michele Atzeni (Department of Information Engineering - University of Padova)*; Luca Cossu (Department of Information Engineering - University of Padova); Giacomo Cappon (Department of Information Engineering - University of Padova ); Martina Vettoti (University of Padova)
      IEEE EMBC 2022 Workshop and Challenge on Detection of Stress and Mental Health Using Wearable Sensors, Huiyuan Yang (Rice University)*; Han Yu (Rice University); Alicia M Choto (Rice University); Maryam Khalid (Rice University); Thomas Vaessen (University of Twente); Akane Sano (Rice University)

Oct. 28th (Friday), 2022

Breakfast, 9:00-9:30

Session 3: Movement, 9:30-10:50

      A Method for Estimating the Number of Steps Taken Using a BLE Beacon Attached to the Soles of Footwear, Yuki Ogane (Aichi Institute of Technology)*; Yu Enokibori (Nagoya University); Katsuhiko Kaji (Aichi Institute of Technology)
      Real-Time Feedback System for Efficient Core Training, Keisuke Sato (Aoyama Gakuin University)*; Ami Jinno (Aoyama Gakuin University); Nishiki Motokawa (Aoyama Gakuin University); Tahera Hossain (Aoyama Gakuin University); Anna Yokokubo (Aoyama Gakuin University); Guillaume Lopez (Aoyama Gakuin University)
      Development of Automatic Posture and Stumbling Judgement System using Deep Learning, Jetson Nano and Drone with Information-Sharing Function, Shinji KAWAKURA (Osaka City Univ.)*; Masayuki Hirafuji (The University of Tokyo); Ryosuke Shibasaki (University of Tokyo)
      Testing the Applicability of Virtual Stochastic Sensors in Human Activity Recognition, Claudia Krull (Otto-von-Guericke-University Magdeburg)*; Pascal Krenckel (Otto-von-Guericke-University Magdeburg); Lauro Fialho Müller (Otto-von-Guericke-University Magdeburg)

Keynote 3, 11:10-12:10

      Cecilia Mascolo (University of Cambridge / United Kingdom), Wear-to-compute? Challenges of Wearable Computing for Health

Luncheon Event, 12:10-14:00

      Session Chair: Seyed Ali, Jaswinder Lota,
      Prospects of Activity Understanding for Smart Cities, Organized by Smart City Res. Gr., UEL- Ali, Jaswinder, Atiq & others

Session 4: Healthcare / Nursery, 14:00-15:20

      Reducing the Number of Wearable Sensors and Placement Optimization by Missing Data Imputation on Nursery Teacher Activity Recognition, Akira Omi (Toyohashi University of Technology)*; Kenshi Fujiwara (Toyohashi University of Technology); Naoko Ishibashi (Sugiyama Jogakuen University); Ren Ohmura ()
      Forecasting Parkinson's Disease Patients' Wearing-Off using Wrist-Worn Fitness Tracker and Smartphone Dataset, John Noel C Victorino (Kyushu Institute of Technology)*; Yuko Shibata (Kyushu Institute of Technology); Sozo Inoue (Kyushu Institute of Technology); Tomohiro Shibata (Kyushu Institute of Technology)
      Analysis of Care Records for Predicting Urination Times, Masato Uchimura (Kyushu Institute of Technology)*; Haru Kaneko (Kyushu Institute of Technology); Sozo Inoue (Kyushu Institute of Technology)
      Challenges and Opportunities of Activity Recognition in Clinical Pathways, Chrisitina A Garcia (Kyushu Institute of Technology)*; Sozo Inoue (Kyushu Institute of Technology)

Panel: Now and the Future of Activity and Behavior Computing, 15:40-17:40


Oct. 29th (Saturday), 2022

Breakfast, 9:00-9:30

Session 5: Recogntion, 9:30-10:50

      Static Sign Language Recognition Using Segmented Images and HOG on Cluttered Backgrounds, Arezoo Sadeghzadeh (Bahcesehir University)*; MD BAHARUL ISLAM (Bahcesehir University); Md Atiqur Rahman Ahad (University of East London)
      Improving Complex Nurse Care Activity Recognition Using Barometric Pressure Sensors, Muhammad Fikry (Kyushu Institute of Technology)*; Chrisitina A Garcia (Kyushu Institute of Technology); Quynh N Phuong Vu (Kyushu Institute of Technology); Shintaro Oyama (Nagoya University); Keiko Yamashita (Nagoya University); Yuji Sakamoto (Global business division, CARECOM CO.,LTD); Yoshinori Ideno (Global business division, CARECOM CO.,LTD ); Sozo Inoue (Kyushu Institute of Technology)
      A CSI-based Human Activity Recognition using Canny Edge Detector, Hossein Shahverdi (Shahid Beheshti University); Parisa Fard Moshiri (Shahid Beheshti University); Mohammad Nabati (Shahid Beheshti University); Seyed Ali Ghorashi (University of East London)*
      A Method for Estimating Upper-Arm Muscle Activities and sEMG with PPG Sensor, Masahiro Okamoto (Ritsumeikan University); Kazuya Murao ()*

4th Nurse Challenge, 11:10-12:40

      Nurse Activity Recognition based on Temporal Frequency Features, Md. Sohanur Rahman (University of Dhaka); Hasib Ryan Rahman (University of Dhaka); Abrar Zarif (University of Dhaka); Yeasin Arafat Pritom (University of Dhaka); Md Atiqur Rahman Ahad (University of East London)*
      Ensemble Classifier for Nurse Care Activity Prediction Based on Care Records, Björn Friedrich (Carl von Ossietzky Universität)*; Andreas Hein (Carl von Ossietzky Universität)
      Predicting User-specific Future Activities using LSTM-based Multi-label Classification, Mohammad Sabik Irbaz (Islamic University of Technology)*; Fardin Ahsan Sakib (George Mason University); Lutfun Nahar Lota (Islamic University of Technology)
      Addressing the inconsistent and missing time stamps in Nurse Care Activity Recognition Care Record Dataset, Rashid Kamal (Ulster University)*
      A Sequential-based Analytical Approach for Nurse Care Activity Forecasting, Md. Mamun Sheikh (University of Dhaka); Shahera Hossain (University of Asia Pacific, Bangladesh); Md Atiqur Rahman Ahad (University of East London)*
      Activity Recognition of Nursing Care Data, Gulustan Dogan (University of North Carolina Wilmington)*; Jonathan Sturdivant (University of North Carolina Wilmington); John Hendricks (University of North Carolina at Chapel Hill)
      Future Prediction for Nurse Care Activities Using Deep Learning based Multi-Label Classification, Wasim Akram (EWU)*; Md. Golam Rasul (Potsdam); Sayeda Fatema Tuj Zohura (EWU); Tanjila Alam Sathi (Islamic University of Technology ); Lutfun Nahar LOTA (IUT)
      A Classification Technique based on Exploratory Data Analysis for Activity Recognition,
      Time Series Analysis of Care Records Data for Nurse Activity Recognition in the Wild,

Lunch Break, 12:40-13:40

Position Papers, 13:40-15:10

      Technology for Recognizing Complex Human Behavior from Video and its Recognition Rule, Takahiro Saito (Fujitsu)*; Satoru Takahashi (Fujitsu)
      Power-Law Distribution of the Visibility Graphs from Acceleration Time Series Generated by Calf Activities, Shuichiro Ito (The University of Shiga Prefecture)*; Osamu Sakai (The University of Shiga Prefecture); Shigeyuki Miyagi (The University of Shiga Prefecture)
      Comparison between Machine Learning and Objective Evaluation in Estimating Emotions of Participants in Video Conferencing, Nozomi Toba (Nara Institution of Science and Technology)*; Manato Fujimoto (Osaka Metropolitan University); Hirohiko Suwa (Nara Institute of Science and Technology); Motoki SAKAI (Nihon University); Masaki Shuzo (Tokyo Denki University); Keiichi Yasumoto (Nara Institute of Science and Technology, Japan)
      Leveraging key-points Motion History Maps for Human Activity Recognition, Rosa Altilio (Elettronica Group)*; Luca Minutillo (Elettronica Group); Francesco Chirico (Elettronica Group); Foglia Goffredo (Elettronica Group)
      How Perfect Joint Combinations from Human-body Data Can Aid in the Development of Intimate Distance Supportive Human Robot Collaboration Systems, Nazmun Nahid (Kyushu Institute of Technology)*; Sozo Inoue (Kyushu Institute of Technology)
      Feasibility Study of Predicting MBTI Personality Types with Group Discussion Dataset, Motoki SAKAI (Nihon University)*; Masaki Shuzo (Tokyo Denki University); Kai imasato (Nihon University)
      A Framework for Estimating Autism Spectrum Disorder Severity by Incorporating Physiological Markers to Aid in Robot Enhanced Intervention Therapy, Iqbal Hassan (Ahsanullah University of Science and Technology)*; Minhajul Islam (Ahsanullah University of Science and Technology); Nazmun Nahid (Kyushu Institute of Technology); Shahera Hossain (University of Asia Pacific, Bangladesh); Md Atiqur Rahman Ahad (University of East London)
      Exploring Deep Learning Models and Training Data Amount for Nursery Activity Recognition, Kenshi Fujiwara (Toyohashi University of Technology)*; Akira Omi (Toyohashi University of Technology); Naoko Ishibashi (Sugiyama Jogakuen University); Ren Ohmura ()
      Preliminary Study for Classifying Baby Stroller-related Parenting using Smartphones, Zengyi Han (The University of Tokyo); Xuefu Dong (The University of Tokyo)*; Yuuki Nishiyama (The University of Tokyo); Kaoru Sezaki (The University of Tokyo)
      Technology for Recognizing Complex Human Behavior from Video and its Recognition Rule, Takahiro Saito (Fujitsu)*; Satoru Takahashi (Fujitsu)
      Learning from data: Self-Supervised Feature Learning for Human Activity Recognition, Federico Cruciani (Ulster University)*; Chris Nugent (Ulster University); Ian Cleland (Ulster University); Paul McCullagh (Ulster University)
      Using Digital Twins for the generation of data for activity recognition models, Chris Nugent (Ulster University); Federico Cruciani (Ulster University)*; Liming Chen (Ulster University); Ian Cleland (Ulster University); Kåre Synnes (Luleå University of Technology); Miguel Ortiz Barrios (Universidad de la costa)

Session 6: Sports, 15:30-16:50

      Gait condition assessment methods for visualizing interventional expertise by means of posture detection, Akinori Kunishima (Shizuoka University)*; Koki Suzuki (Shizuoka University); Atsushi Omata (Shizuoka University); Shogo Ishikawa (Shizuoka University); Shinya Kiriyama (Shizuoka University)
      FootbSense: Soccer Moves In Practice Environment Identification Using a Single IMU, Hikari Aoyagi (Aoyama Gakuin University)*; Tahera Hossain (Aoyama Gakuin University); Anna Yokokubo (Aoyama Gakuin University); Guillaume Lopez (Aoyama Gakuin University)
      BoxerSense: Boxing movements recognition using IMUs during shadow boxing exercise, Yoshinori Hanada (Aoyama Gakuin University)*; Tahera Hossain (Aoyama Gakuin University); Anna Yokokubo (Aoyama Gakuin University); Guillaume Lopez (Aoyama Gakuin University)
      Keeping athletes motivated by realtime co-running application, Shun Ishii (Aoyama Gakuin University); Kazuki Imura (Aoyamagakuinn)*; Guillaume Lopez (Aoyama Gakuin University); Tahera Hosain (Aoyama Gakuin University); Anna Yokokubo (Aoyama Gakuin University)

Awards + Closing, 16:50-17:30

Banquet,


Registration


Please do registration from below.

  • Non-Student Author/Participant: USD240
  • Student Author: USD120
The payment will be managed by AUTOCARE LLC with the name of mo***@eng.u-hyogo.ac.jp.
Registration

Call for Papers


We welcome 4 categories of papers: regular papers, position papers, survey papers, and challenge papers. The submitted papers are peer reviewed by expert researchers, and accepted based on the research quality.

Accepted papers will be included in the Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors by CRC Press.

Scope

  • Mobile sensor-based ABC
  • Environmental sensor-based ABC
  • Vision-based ABC
  • Multimodal ABC
  • Physical / semantic analysis of ABC
  • Gait analysis
  • Sleep analysis
  • Emotion recognition / analysis
  • ABC with deep learning
  • ABC data mining
  • Data collection
  • ABC systems
  • Interactive ABC
  • Healthcare applications
  • Sports applications
  • Business applications
  • Tools for industry
  • ABC in the wild

Categories

  • Regular papers: full technical contents which describe the accuracy and performance of ABC Systems, real deployment cases or application of new paradigms such as deep learning to ABC.
  • Survey papers: new perspective or new challenges in ABC based on literature survey. We do not welcome just compilations of existing research, but do if it provides new research horizons.
  • Challenge papers: we will provide a dataset and accept results for activity recognition and papers describing the methods and the results. Please see the Challenge Site for details.
  • Position papers: describe the challenges and future directions of ABC based on problems that arise when systems are deployed in real settings.

Format

  • Regular papers: 8-20 pages in single column
  • Survey papers: 10-20 pages in single column
  • Challenge papers: 4-10 pages in single column
  • Position papers: 4-10 pages in single column
  • Please use the LaTeX template (button below for the LaTeX template).
  • Submit from Microsoft CMT service (button below) and select the ABC.
  • Note that the author information should be removed from the paper, for double blind reviews.

Important dates

[Regular/Survey/Position] Paper submission

  :  

June 30th July 31st, 2022 (Extended) (Anywhere on Earth)!

Review result

  :  

August 1st August 25th, 2022

Resubmission for conditionally accepted paper

  :  

August 15th September 5th, 2022

[Challenge] Application Close

  :  

July 15th, 2022

[Challenge] Result submission

  :  

August 1st August 7th, 2022 (Extended) (Anywhere on Earth)!

[Challenge] Paper submission

  :  

August 10th August 15th, 2022 (Extended) (Anywhere on Earth)!

[Challenge] Review result

  :  

August 25th, 2022

[Regular/Survey/Position/Challenge] Camera ready and Registration

  :  

September 10th September 23rd, 2022 (Extended) (Anywhere on Earth)!

Conference

  :  

October 27th - 29th, 2022

Venue


ABC2022 will be held at (London, United Kingdom (Hybrid)).

ABC2022 will be held at Dept. of Computer Science and Digital Technologies, Docklands Campus, University of East London (UEL), UK, very nearby the London City Airport.

For more information, please see the campus web.

Committee


General Chairs

Sozo Inoue, Kyushu Institute of Technology / AUTOCARE LLC, Japan
Atiqur Rahman Ahad, University of East London, UK

Program Chairs

Stephan Sigg, Aalto University, Finland
Guillaume Lopez, Aoyama Gakuin University, Japan

Publicity Chairs (TBA)

Paula Lago, Concordia University, Canada
Anja Exler, Adastra, Germany

Publication Chairs

Tahera Hossain, Aoyama Gakuin University, Japan
Shahera Hossain, American University of Malta, Malta

Local Arrangement Committee

Abdulrazaq Abba, University of East London, UK
Bilyaminu Auwal Romo, University of East London, UK
Fahimeh Jafari, University of East London, UK
Seyed Ali Ghorashi, University of East London, UK
Shahera Hossain, American University of Malta, Malta
Sujit Biswas, University of East London, UK

Advisory Board

Paul Lukowicz, DFKI, Germany
Kristof Van Laerhoven, University of Siegen, Germany
Michael Beigl, Karlsruhe Institute of Technology, Germany
Jeffry Cohn, University of Pittsburgh, USA
Anind Dey, University of Washinton, USA
Nobuo Kawaguchi, Nagoya University, Japan

Secretaries (TBA)

Muhammad Fikry, Kyushu Institute of Technology, Japan
Haru Kaneko, Kyushu Institute of Technology, Japan

Program Committee (TBA)

Ren Ohmura, Toyohashi University of Technology, Japan
Kazuya Murao, Ritsumeikan University, Japan
Kaori Fujinami, Tokyo University of Agriculture and Technology, Japan
Kristof Van Laerhoven, University of Siegen, Germany
Philipp M. Scholl, University of Freiburg, Germany
Hristijan Gjoreski, Ss. Cyril and Methodius University, Macedonia
Katsuhiko Kaji, Aichi Institute of Technology, Japan
Tsuyoshi Okita, Kyushu Institute of Technology / Riken, Japan
Paula Lago, Concordia University, Canada
Hiroki Watanabe, Hokkaido University, Japan
Pascal Hirmer, University of Stuttgart, Germany
Shigeyuki Miyagi, The University of Shiga Prefecture, Japan
Yu Enokibori, Nagoya University, Japan
Anja Exler, Adastra, Germany
Trung Thanh NGO, Osaka University, Japan
Upal Mahbub, University of Meryland, College Park, USA
Atsushi Shimada, Kyushu University, Japan
Atsushi Nakazawa, Kyoto University, Japan
Liming Chen, Ulster University, UK
Christopher Nugent, Ulster University, UK
François Charpillet, INRIA, France
Maria Del Pilar Villamil Giraldo, University of Los Andes, Colombia
Takuro Yonezawa, Nagoya University, Japan
Yuuki Nishimura, University of Tokyo, Japan
Tahera Hossain, Aoyama Gakuin University, Japan
Moe Matsuki, Kyushu Institute of Technology, Japan
Nattaya Mairittha, Kyushu Institute of Technology, Japan
Tittaya Mairittha, Kyushu Institute of Technology, Japan
John Noel Victorino, Kyushu Institute of Technology, Japan
Takuya Maekawa, Osaka University, Japan

Series