2nd International Workshop on Industrial Machine Learning

ICPR 2022

August 21st, 2022 | Montreal, Canada

With the advent of Industry 4.0 and Smart Manufacturing paradigms, data has become a valuable resource, and very often an asset, for every manufacturing company. Data from the market, from machines, from warehouses and many other sources are now cheaper than ever to be collected and stored. A study from Juniper Research has identified industrial internet of things (IIoT) as a key growth market over the next five years, accounting for an increase in the global number of IIoT connections from 17.7 billion in 2020 to 36.8 billion in 2025, representing an overall growth rate of 107%. With such an amount of data produced every second, classical data analysis approaches are not useful and only automated learning methods can be applied to produce value, a market estimated in more than 200B$ worldwide. Using machine learning techniques manufacturers can exploit data to significantly impact their bottom line by greatly improving production efficiency, product quality, and employee safety.

The introduction of ML to industry has many benefits that can result in advantages well beyond efficiency improvements, opening doors to new opportunities for both practitioners and researchers. Some direct applications of ML in manufacturing include predictive maintenance, supply chain management, logistics, quality control, human-robot interaction, process monitoring, anomaly detection and root cause analysis to name a few.

This workshop will ground on the successful story of the first edition, with 19 oral presentations and 3 invited talks, to draw attention to the importance of integrating ML technologies and ML-based solutions into the manufacturing domain, while addressing the challenges and barriers to meet the specific needs of this sector. Workshop participants will have the chance to discuss:

● needs and barriers for ML in manufacturing

● state-of-the-art in ML applications to manufacturing

● future research opportunities in this domain

Call for Papers

This is an open call for papers, soliciting original contributions considering recent findings in theory, methodologies, and applications in the field of industrial machine learning. Position papers presenting industrial use cases and discussing potential solutions are welcome. Potential topics include, but are not limited to:

  • Robustness-oriented learning algorithms

  • Machine learning for robotics (e.g. learning from demonstration)

  • Continuous and life-long learning for industrial applications

  • Transfer learning and domain adaptation

  • Anomaly detection and process monitoring

  • ML applications to Predictive Maintenance

  • ML applications to Supply Chain and Logistics

  • ML applications to Quality Control

  • ML for flexible manufacturing

  • Deep Learning for industrial applications

  • Learning from Big-Data

  • Inference in real-time applications

  • Machine Learning on Embedded and Edge computing hardware

All the contributions are expected to expose applications to the industrial sector, possibly with real world case studies. Position papers presenting new industrial systems and case studies, possibly reporting preliminary validation studies, are also encouraged.

A Best Paper Award will be assigned to the most relevant contribution. The decision will be taken by the Organizing Committee according to the reviewers’ feedback.


Papers must be prepared according to the ICPR guidelines (see here). All papers will be reviewed by at least two reviewers with single-blind peer review policy. Papers will be selected based on relevance, significance and novelty of results, technical merit, and clarity of presentation. Papers will be published in ICPR proceedings.

Templates in Word or Latex can be downloaded here: word | latex

All the papers must be submitted using CMT submission server.

Important dates

  • Full Paper Submission: May 7, 2022 EXTENDED to June 10, 2022

  • Notification of Acceptance: June 20, 2022

  • Camera-Ready Paper Due: September 1, 2022

In case of rejection from ICPR main conference, authors can submit their work to the IML workshop. Authors should address all ICPR reviewers' comments in the submitted paper and submit the ICPR reviews as supplementary material.

Program (Tentative)

9.00 AM - Welcome & Opening

9.10 AM - Invited talk: Martin Atzmüller (Osnabrück University and German Research Center for AI, Germany) - Explainable & Interpretable Machine Learning: Methods and Applications in Complex Industrial Contexts

10.00 AM - Coffee break

10.30 AM - Geri Skenderi: "On the use of learning-based forecasting methods for ameliorating fashion business processes: A position paper"

10.45 AM - Buddhika Laknath Semage: "Intuitive Physics Guided Exploration for Sample Efficient Sim2real Transfer"

11.00 AM - Invited talk: Marco Rudolph (Leibniz University Hannover, Germany) - Industrial Anomaly Detection with Normalizing Flows

11.30 AM - Invited talk: Danijel Skočaj (University of Ljubljana, Slovenia) - Data-driven learning-based surface defect detection

12.10 PM - Saeid Rezaei: "Gym-DC: Reinforcement Learning Environment in Distribution Centre"

12.25 PM - Marco Cristani: "Toward Smart Doors: A Position Paper"

12.40 PM - Francesco Setti: "IndRAD: A Benchmark for Anomaly Detection on Industrial Robots"


Francesco Setti

University of Verona

Luigi Di Stefano

University of Bologna

Paolo Rota

University of Trento

Vittorio Murino

University of Verona

Massimiliano Mancini

University of Tübingen