AIML: The 1st IEEE International Workshop on Advances in AI and Machine Learning: Research & Practice

Call for Papers

After decades of generous promises and several frustrating disappointments, artificial intelligence (AI) and machine learning (ML) is finally starting to deliver real benefits, and early adopters in business and industry are embracing its promise reaping benefits. We’re now witnessing rapid advances in AI and ML – in research, development, application and commercialization. To lay better foundation for the future – to make the connected, smartening world more smarter and to embrace AI for good for benefit of society, advances in AI and ML, their new innovative applications, and challenges and lessons learned need to be shared and discussed.

This workshop will facilitate much needed interaction and information exchange among AI researchers, practitioners and business executives. It will provide an interactive forum for discussion on recent and ongoing developments, key issues and challenges, and practices related to AI applications. It will also provide a platform to demonstrate applications and software tools, and present case studies and application experience. Researchers and practitioners from all over the world, from academia, industry, and government are invited to present their work and perspectives and participate in the workshop.

Topics of interest include, but are not limited to:

  • Advances in AI and machine learning, deep learning, cognitive computing, intelligent agent, chatbot
  • AI strategy for business and industry
  • AI applications in industry, business, healthcare, and education and training
  • AI in legal practice
  • Entertainment in the AI age
  • AI for enhancing information security and privacy
  • Work in the age of AI
  • Trust, resilience, privacy and security issues in AI applications
  • Testing and validation of AI and ML applications
  • Risks, limitations, and challenges of AI and ML
  • Legal, regulatory, ethical aspects of AI
  • AI: promise vs practice
  • Societal implication of the rise of AI
  • Human-machine co-existence and collaboration
  • Intelligent, autonomous robots and cars
  • Industry 4.0
  • Smart society
  • AI and IoT
  • Case studies, experience reports, lessons learned
  • Overview of AI activities in a region/country
  • The future of AI

AIML Schedule

Monday July 23, 9:30 – 11:00am
Session 1
Location: Meeting Hall 3
Session Chair: Jun (Luke) Huan, Baidu Research, China

Review of Small Data Learning Methods
Xiali Li, Songting Deng, Song Wang, Zhengyu Lv, Licheng Wu

A Deep Learning Approach for Estimating Inventory Rebalancing Demand in Bicycle Sharing Systems
Petar Mrazovic, Josep Luis Larriba-Pey, Mihhail Matskin

On Learning Fuel Consumption Prediction in Vehicle Clusters
Victor Parque, Tomoyuki Miyashita

An Approach to Proposing Novel Business Models Basing on Association Rules Learning, BP Neural Network and Creative Computing
Qinyun Liu, Lin Zhou, Hua Zhou, Hongji Yang

Monday July 23, 11:30 – 1:00pm
Session 2
Location: Meeting Hall 3
Session Chair: Takahira Yamaguchi, Keio University, Japan

Mining Sequential Patterns to Explore Users’ Learning Behavior in a Visual Programming App
Wen-Chung Shih

Predicting Decisions of the Philippine Supreme Court Using Natural Language Processing and Machine Learning
Michael Benedict Virtucio, Jeffrey Aborot, John Kevin Abonita, Roxanne Aviñante, Rother Jay Copino, Michelle Neverida, Vanesa Osiana, Elmer Peramo, Joanna Syjuco and Glenn Brian Tan

Prediction Method of Blasting Vibration by Optimized GEP Based on Spark
Yunlan Wang, Bin Zhang, Tianhai Zhao, Zhengxiong Hou, Xiangyu Wu, Hussain Khanzada Muzammil

Empirical Evaluation of “Idle-Time Analysis” Driven Improved Decision Making by Always-On Agents
Sravyasri Garapati, Kamalakar Karlapalem

Monday July 23, 2:00 – 3:30pm
Session 3
Location: Meeting Hall 3
Session Chair: Ryohei Orihara, Toshiba, Japan

Practice of Multi-Robot Teahouse based on PRINTEPS and Evaluation of Service Quality
Takeshi Morita, Naho Kashiwagi, Ayanori Yorozu, Michael Walch, Hideo Suzuki, Dimitris Karagiannis, Takahira Yamaguchi

Transfer Learning Method for Very Deep CNN for Text Classification and Methods for its Evaluation
Shun Moriya, Chihiro Shibata

Understanding Mindsets Across Markets, Internationally: A Public-Private Innovation Project for Developing a Tourist Data Analytic Platform
Kristoffer Jon Albers, Mikkel N. Schmidt, Morten Mørup, Marisciel Litong-Palima, Rasmus Bonnevie, Fumiko Kano Glückstad

Modified Memetic Self-Adaptive Firefly Algorithm for 2D Fractal Image Reconstruction
Akemi Galvez, Andres Iglesias

Monday July 23, 4:00 – 5:30pm
Session 4
Location: Meeting Hall 3
Session Chair: San Murugesan, BRITE Professional Services, Australia

Approximation of Time-Consuming Simulation Based on Generative Adversarial Network
Ryohei Orihara, Ryota Narasaki, Yuma Yoshinaga, Yasuhiro Morioka, Yoshiyuki Kokojima

Model-Space Regularization and Fully Interpretable Algorithms for Postural Control Quantification
Alice Nicolaï, Julien Audiffren

Generation of Character Illustrations from Stick Figures using a Modification of Generative Adversarial Network
Yuuya Fukumoto, Daiki Shimizu, Chihiro Shibata

NDFMF: An Author Name Disambiguation Algorithm based on the Fusion of Multiple Features
Xiaolong Xu, Yongping Li, Mark Liptrott, Nik Bessis

AIML Workshop Organizers

San Murugesan, Director BRITE Professional Services; Editor in Chief Emeritus, IEEE CS IT Professional, Australia

Takahira Yamaguchi, Faculty of Science and Technology, Keio University; Past President, Japanese AI Association, Japan

AIML Program Committee

Mohan K. Bavirisetty, CISCO, USA

Seth Earley, Earley Associates, USA

Sunil Mithas, University of Maryland, USA

Takeshi Morita, Keio University, Japan

Kozo Ohara, Aoyama Gakuin University, Japan

Kenichi Yoshida, Tsukuba University, Japan