Sun 14 AprDisplayed time zone: Lisbon change
11:00 - 12:30 | Architecting, Designing, Managing, and Modeling AI-Enabled SystemsIndustry Talks / Research and Experience Papers at Pequeno Auditório Chair(s): Nicolás Cardozo Universidad de los Andes | ||
11:25 10mIndustry talk | KnowING Intelligent Document Classification: A Deep Dive into Microservices and Efficient Models at ING Industry Talks A: Andrew Rutherfoord CWI; University of Groningen, A: Gert Vermeer , Andrea Capiluppi Brunel University | ||
11:50 10mIndustry talk | Engineering Challenges in Industrial AI Industry Talks |
14:00 - 15:30 | Data Engineering and Management for AI-Enabled SystemsResearch and Experience Papers / Industry Talks at Pequeno Auditório Chair(s): Marc Zeller Siemens AG | ||
14:55 10mIndustry talk | Structuring the world of unstructured text data – Balancing business requirements, training data availability, and model performance. Industry Talks | ||
15:05 10mIndustry talk | Invited: Artificial Intelligence Projects, a quest between meaningful use cases, data, and unfulfilled desires. Industry Talks |
16:00 - 18:00 | Generative AI EngineeringIndustry Talks / Research and Experience Papers at Pequeno Auditório Chair(s): Ipek Ozkaya Carnegie Mellon University | ||
16:25 10mIndustry talk | Innovating Translation: Lessons Learned from BWX Generative Language Engine Industry Talks | ||
17:00 60mPanel | Industry Panel Industry Talks |
Mon 15 AprDisplayed time zone: Lisbon change
16:00 - 18:00 | System QualitiesResearch and Experience Papers / Industry Talks at Pequeno Auditório Chair(s): Andrei Paleyes Department of Computer Science and Technology, Univesity of Cambridge | ||
17:20 10mIndustry talk | Trustworthy AI: Industry-Guided Tooling of the Methods Industry Talks Zakaria Chihani CEA, LIST, France |
Accepted Papers
Call for Contributions
The goal of Industry Talks is to share experiences related to the industrial applications of soft-ware engineering in AI-enabled systems and to convey lessons learned from applying various techniques and practices in the field. This submission category is exclusively open to individuals who are willing to share practical insights gained directly from their professional experiences.
We are inviting practitioner-oriented talks on topics that are expected to be relevant to both in-dustry professionals and academic attendees. Talk proposals must include a brief abstract (up to 150 words), a list of keywords (up to 8), and a “talk description” that elaborates on the content of the talk, emphasizes its key points, and explains why it is relevant and significant to the soft-ware engineering community (up to 500 words).
Optionally, this description can be submitted as a two-page long extended abstract which will be included in the CAIN’24 proceedings, following the official “ACM Primary Article Template” avail-able at the ACM Proceedings Template page. LaTeX users should employ the “sigconf” option and include the “review” option to generate line numbers for easy reference by reviewers. You can place the following LaTeX code at the beginning of your document:
\documentclass[sigconf,review]{acmart}
\acmConference[CAIN 2024]{3rd International Conference on AI Engineering — Software Engineering for AI}{April 2024}{Lisbon, Portugal}
In addition, please include up to 10 slides that represent the content of your talk. Submissions should also include title, name, affiliation, and a short bio of the speaker. Talk proposals can also include supporting supplemental materials such as white papers or videos. Please indicate a desired length of either 15 minutes or 30 minutes for your talk.
The submitted proposals will be reviewed by the Industry Track Committee.
Please submit your Industry Talk proposals through the designated web page: https://icse2024-cain-industry.hotcrp.com/
List of Accepted Talks
Engineering Challenges in Industrial AI
Author: Martin Hollender, Chaojun Xu, and Ruomu Tan
Innovating Translation: Lessons Learned from BWX Generative Language Engine
Author: Vanilson Burégio
Trustworthy AI: Industry-Guided Tooling of the Methods
Author: Zakaria Chihani
KnowING Intelligent Document Classification: A Deep Dive into Microservices and Efficient Models at ING
Authors: A Rutherfoord, G Vermeer, A Capiluppi
Artificial Intelligence Projects, a quest between meaningful use cases, data, and unfulfilled desires.
Author: Andreas Jedlitschka
Structuring the world of unstructured text data – Balancing business requirements, training data availability, and model performance.
Authors: Sooji Han and Berinike Tech