IEEE Conferences

ICWS 2022 Symposium

2022 IEEE ICWS Symposium on Services for Machine Learning

Jump to: ICWS Symposium on Services for Machine Learning Program | ICWS Full Technical Program

Research in machine learning is active as probably never before. Rarely has a field seen such growth in interest in a fairly short time. Most of the research focus on learning algorithms and data. However, once trained, ML models not only need to be managed, but they need to be deployed - typically as services - in the context of workflows that deliver value to users.

The integration of ML services into workflows or composite services and the relationship between ML quality and workflow quality and fairness is a much less explored topic, and is the focus of this symposium.

Specifically, the ICWS Symposium on Services for Machine Learning aims at bringing together experts from ML, process management, and service integration to create a community focused on understanding and proposing methods for leveraging and measuring ML services when integrated into processes to deliver customer value. We believe this is the missing link in ML research that connects the recent amazing progress to positive user impact.

---

ICWS Symposium on Services for Machine Learning - Session 1 (CWS-SYM1)
Monday July 11, 14:00-15:15
Room: Theater Room
Session Chair: Fabio Casati, Servicenow

CWS_SYM_140
Temporal Match Analysis and Recommending Substitutions in Live Soccer Games
Yuval Berman, Sajib Mistry, Joby Mathew and Aneesh Krishna

CWS_SYM_189
Enabling Multi-Provider Cloud Network Service Bundling
Imen Jerbi, Nour Assy, Mohamed Sellami, Hayet Brabra, Walid Gaaloul, Sami Bhiri, Olivier Tirat and Djamal Zeghlache

CWS_SYM_191
How Composable is the Web? An Empirical Study on OpenAPI Data model Compatibility
Souhaila Serbout, Cesare Pautasso and Uwe Zdun

CWS_SYM_192
Knowledge Base 4.0: Using Crowdsourcing Services for Mimicking the Knowledge of Domain Experts (short paper)
Amin Beheshti

---

ICWS Symposium on Services for Machine Learning - Session (CWS-SYM2)
Monday July 11, 15:15-16:30
Room: Theater Room
Session Chair: Boualem Benatallah, Dublin City University

CWS_SYM_194
A Blockchain-based Framework in Support of Privacy Preferences Enforcement for Scientific Workflow
Federico Daidone, Barbara Carminati and Elena Ferrari

Panel: Bias in ML - From Bias in ML Service to Bias in ML-Powered Processes

Panelists:

Boualem Benatallah (in-person) is a full professor of computing at Dublin City University (DCU, Ireland) since Jan 2022. Professor Benatallah has had over 21 years as a research leader and academic (senior lecturer, associate professor, professor and then scientia professor), at UNSW Sydney (Australia). His main research interests are developing fundamental concepts and techniques in Web service composition, services engineering, crowd sourcing services, data curation, cognitive services, and business processes management. He has published more than 300 refereed papers including more than 90 journal papers. Most of his papers appeared in very selective and reputable conferences and journals. Boualem has been general and PC chair of a number of international conferences. He has been guest editor of several special issues for reputable international journals. He is a member of the steering committee of BPM and ICSOC conferences. He is member of the editorial board of numerous international journals including ACM Transactions on Web and IEEE transactions on services computing. He held visiting professor positions at several prestigious research institutes and universities. He was a member of the team (comprising multiple university, government, and industry partners) that constructed the successful bid for the Smart Services CRC (cooperative Research Centre). He was research leader of the data curation foundry research stream at the Data to Decisions CRC. He is fellow of the IEEE. He is member of Executive Committee of IEEE Computer Society's Technical Committee on Business Informatics and Systems. He is member of ACM.

Fabio Casati (in-person) is a Principal Machine Learning Architect and Engineer at Servicenow. Fabio focuses on designing, architecting and deploying AI-powered workflows for enterprise customers. On the research side, he is working on AI applied to workflows and on quality in AI. Previously he was Professor at the University of Trento. In that role, he started research lines on crowdsourcing and hybrid human-machine computations, focusing on applications that have direct positive impact on society through tangible artefacts adopted by the community. Prior to that, he was technical lead for the research program on business process intelligence in Hewlett-Packard USA, where he contributed to several HP commercial products in the area of web services and business process management. He co-authored a best-selling book on Web services and is author of over 250 peer-reviewed papers.

Cesare Pautasso (in-person) is full professor at the Software Institute at USI Lugano, Switzerland. He leads the Architecture, Design and Web Information Systems Engineering research group, which focuses on building experimental systems to explore the intersection of Text-to-Visual modeling languages, Web API analytics and liquid software architectures. He is the general chair for EuroPLoP 2022 and SOSE 2022. He is the co-editor of the IEEE Software Insights department. His e-books on Email Anti-Patterns, Software Architecture, Business Process Management, and API visualization are available on LeanPub.

Marcos Baez (virtual) is a Senior Research Fellow at Bielefeld University of Applied Sciences, Germany, where he is carrying out research on AI-enabled services, taking a pragmatic and human-centred approach to design and engineering. In the past, Marcos participated in the research and development of successful tech-supported wellbeing initiatives, working towards bringing societal innovations to vulnerable populations. His main research interests include Web engineering, Crowdsourcing, Human-AI interaction, and in general how design and engineering can be combined in an ethically-sound framework to make people’s life better.

Yacine Gaci (virtual) is a Ph.D. student at the University of Lyon, France. His research focuses on studying the effect and harms that social biases may inflict on NLP technologies. He proposes and develops methods to quantify and measure the amount of gender, racial and religious biases and stereotypes encoded in static word embeddings and in large-scale text encoders, as well as reducing social stereotypes from these models. In the past, Yacine conducted research on enabling conversational systems to cater for the users' subjective queries. He also worked on designing similarity measures that take subjectivity into consideration. Yacine's main research interests include Deep Learning, Optimization, and socially-fair Natural Language Processing.

Symposium Chairs

Boualem Benatallah is a full professor of computing at Dublin City University (DCU, Ireland) since Jan 2022. Professor Benatallah has had over 21 years as a research leader and academic (senior lecturer, associate professor, professor and then scientia professor), at UNSW Sydney (Australia). His main research interests are developing fundamental concepts and techniques in Web service composition, services engineering, crowd sourcing services, data curation, cognitive services, and business processes management. He has published more than 300 refereed papers including more than 90 journal papers. Most of his papers appeared in very selective and reputable conferences and journals. Boualem has been general and PC chair of a number of international conferences. He has been guest editor of several special issues for reputable international journals. He is a member of the steering committee of BPM and ICSOC conferences. He is member of the editorial board of numerous international journals including ACM Transactions on Web and IEEE transactions on services computing. He held visiting professor positions at several prestigious research institutes and universities. He was a member of the team (comprising multiple university, government, and industry partners) that constructed the successful bid for the Smart Services CRC (cooperative Research Centre). He was research leader of the data curation foundry research stream at the Data to Decisions CRC. He is fellow of the IEEE. He is member of Executive Committee of IEEE Computer Society's Technical Committee on Business Informatics and Systems. He is member of ACM.

Fabio Casati is a Principal Machine Learning Architect and Engineer at Servicenow. Fabio focuses on designing, architecting and deploying AI-powered workflows for enterprise customers. On the research side, he is working on AI applied to workflows and on quality in AI. Previously he was Professor at the University of Trento. In that role, he started research lines on crowdsourcing and hybrid human-machine computations, focusing on applications that have direct positive impact on society through tangible artefacts adopted by the community. Prior to that, he was technical lead for the research program on business process intelligence in Hewlett-Packard USA, where he contributed to several HP commercial products in the area of web services and business process management. He co-authored a best-selling book on Web services and is author of over 250 peer-reviewed papers.