THE WORKSHOP WILL TAKE PLACE ON NOVEMBER 9, 2023. FOR INFO ON REGISTRATION PLEASE VISIT THE AI*IA 2023 REGISTRATION PAGE.


3rd Italian Workshop on Artificial Intelligence and Applications for Business and Industries - AIABI | co-located with AI*IA 2023

AI is strongly emerging as transversal and powerful technological paradigm: it can transform business models in all industries, in a disruptive and pervasive way. This workshop will be focused on the current scenario of AI for business in heterogenous fields and industries.

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The proceedings are now ONLINE!

The proceedings are published online at CEUR-WS.org. Thanks to all of those who took part into the workshop. Check the proceedings on the CEUR website down here.

Abstract Submission

15th September 202320th September 2023

Paper Submission

25th September 2023 28th September 2023

Notification to authors

4th October 2023

Registration

see main conference website

Camera ready for CEUR Proceedings

18th October 2023 20th November 2023

Workshop Program

Thursday November 9th 2023 from 3 to 6 p.m.

Submit Your Paper
Aixia Series
Call For Papers

Papers

Submission Guidelines

We encourage the submission of original contributions, investigating novel methodologies or presenting business cases of AI systems and algorithms for industries. In particular, authors can submit:

Regular papers: max. 12 + references – Springer LLNCS format. Original and unpublished research works. The aim of this kind of paper is to disseminate to the community a complete research work.

Short/Position papers: max 6 pages + references – Springer LLNCS format. Shorter papers with preliminary results or in-progress works. The authors are encouraged to present the main open problems and novel ideas to allow a fruitful discussion that can help in improving the work. Exploratory papers are also a useful tool for students to start presenting their current research.

Workshop submissions must be in PDF format, do not exceed 12 (for full papers) or 6 (for short papers) pages, and should be written in LaTeX, using https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines.

Submit to: https://easychair.org/conferences/?conf=aiabi2023

Submission Guidelines
Proceedings and post-proceedings

Papers

Proceedings and post-proceedings

All accepted papers will be published in the AIxIA series of CEUR-WS. Workshop proceedings should preferably be published in CEUR Workshop Proceedings AIxIA Series http://ceur-ws.org/aixia.html selecting Workshop as the submission topic. A selection of the best papers, accepted for the presentation at the workshops, will be invited to submit an extended version for publication on “Intelligenza Artificiale”, the International Journal of the Italian Association for Artificial Intelligence, edited by IOS Press and indexed by Thomson Reuters’ “Emerging Sources Citation Index” and Scopus by Elsevier.

Proceedings will be submitted for indexation by:

Scopus
Semantic Scholar
Google Scholar
dblp computer science bibliography
Motivation

Motivation

AI is a crucial technology

Artificial Intelligence (AI) is becoming crucial in every business field. AI is currently reshaping organizations and how technologies affects management and business (Haefner et al., 2021). AI has the power to transform business and society, in a transversal and pervasive way, due to its ability to extract and manage knowledge potentially in every industry. Researchers and scientists are aware that AI is transforming business models of all industries, by reshaping existing organizational processes (Brynjolfsson and McAfee, 2017; von Krogh, 2018). Moreover, AI has the potential to provide higher quality, greater efficiency, and better outcomes than human experts (Agrawal et al., 2018a). AI is actually able to foster evolution in society, emerging as transversal and powerful technological paradigm and giving rise to the so-called fourth industrial revolution. Andrew Ng, former chief scientist at Badu and Cofounder at Coursera, said in a keynote speech at the AI Frontiers conference in 2017 that AI is really the new electricity: a disruptive, pervasive and enabling technology, empowering technologies and processes in potentially any field or domain.

AI is a crucial technology
The pervasivity of AI in organizations

Motivation

The pervasivity of AI in organizations

In the organizational and business framework, AI can provide assistance to decision-makers and technicians beyond the scope of humans (Groves et al., 2013; Wamba et al., 2017). Indeed, both academics and practitioners agree that AI may substantially impact firms’ innovation processes (Bughin et al., 2018; von Krogh, 2018). Organizations have long exploited AI-based solutions to automate routine tasks in operations and logistics. Recent advances in computational power and resources, the exponential increase in data availability, and new machine-learning techniques now allow organizations to also exploit AI-based solutions for managerial tasks (Brynjolfsson & McAfee, 2017). For example, AI-based solutions play important roles in Unilever’s talent acquisition process (Marr, 2018), in Netflix’s decision-making processes regarding movie plots, directors, and actors (Westcott Grant, 2018), and in Pfizer’s drug discovery and scientific development activities (Fleming, 2018).

Motivation

AI for quality control and Industry 4.0

In the industrial field, there is a wide use of vision tools for the automation of quality control procedures by the means of AI tools that focus on the quantitative and deterministic analysis of a product, in order to ensure that it complies with the requirements expressed by the customer. Moreover, there is also the need for software tools which could allow the modeling and generalization of quantitative analyses that aim to determine the value of a product or material according to aesthetic standards. These operations are still carried out by specialized technicians, thereby the traditional process is slowed down by the huge waste of time and human resources required, as well as by a performance limit mainly due to the high intrinsic variability among the different annotators. For these reasons, it is not surprising that the quality control task has rapidly established itself as a relevant use case for AI in the field of Industry 4.0.

AI for quality control and Industry 4.0
Why AIABI?

Motivation

Why AIABI?

Therefore, this workshop will be focused on the current technological scenario of AI for business in heterogenous fields and industries. The workshop mainly aims at allowing organizations, academics, researchers and specifically firms, decision-makers and practitioners to share and analyze heterogenous research works and business case studies dealing with AI in business fields. The idea behind this workshop is the opportunity to share knowledge and experience in how AI is actually and currently affecting business cases and intelligence. Companies will share specific case studies as well as their current issues AI is solving in their organizations. Researchers will provide scientific works and studies to contribute in the advancement of the many synergies between AI and business models and organizations. The final aim of the workshop is contributing in depicting the overall scenario and framework of the exploitation, advantages and current issues of AI in business.

Topics of Interest
  • Affective computing
  • Artificial intelligence
  • Brain computer interface
  • Control devices
  • Ergonomics
  • Ethics in artificial intelligence
  • Human-centered computing
  • Human-centered sensing
  • Human-machine interaction
  • Interfaces
  • Multimodal machine learning (sensors, information, environment)
  • Neuropsychology and neuroscience in the HMI field
  • Regulations and juridical aspects in the HMI field
  • Sensors
  • User experience
  • Virtual and augmented reality
  • Wearable sensing
Workshop Program
(Thursday November 9th 2023 3 to 6 p.m.)

THE WORKSHOP WILL TAKE PLACE ON NOVEMBER 9, 2023. FOR INFO ON REGISTRATION PLEASE VISIT THE AI*IA 2023 REGISTRATION PAGE.

  • Welcome

    15.00-15.05

  • The use of impressions inRecommender Systems: improving complete and semi cold-start

    15.05-15.17

    Authors: Matteo Garavaglia, Alessandro Solinas, Ricardo Anibal Matamoros Aragon,Stefania Bandini and Francesco Epifania.

    Affiliations: Aitech4t, Social Things, Unimib

  • Enhancing Classification in UTD-MHAD Dataset: Utilizing Recurrent Neural Networks in Ensemble-Based Approach for Human Action Recognition

    15.17-15.29

    Authors: Saketh Kilaru, Anushka Shah and Swoichha Adhikari.

    Affiliations: BITS Pilani, Mumbai University, Gandaki College of Engineering 

  • NLP for market and competitive intelligence

    15.29-15.41

    Authors: Igor Menghini.

    Affiliations: Roche Diagnostics

  • Drug Inventory Control: Human Decisions versus DeepReinforcement Learning

    15.41-15.53

    Authors: Francesco Stranieri, Alberto Archetti, Enrico Robbiano, Chaaben Kouki andFabio Stella.

    Affiliations: PoliTO, Unimib, Bristol Myers Squibb, ESSCA School of Management

  • Prompt-Based Fashion Outfits Retrieval and Recommender System Using Binary Hashing

    15.53-16.05

    Authors: Quocdung Nguyen, Hoangnam Pham, Duyhung Dao, Quangmanh Do andVanha Tran.

    Affiliations: FPT University in Vietnam

  • Coffee Break

    16.05-16.30

  • DeepLearning MRI Analysis for Automated Knee Injury Diagnosis

    16.30-16.42

    Authors: Snehal Patil, Supriya Alavala, Ambar Gharat and Akshath Kamath.

    Affiliations: Savitribai Phule Pune University, Bangalore RNS Institute of Technology, Vellore Institute of Technology

  • Enhancing Online Educational ResourceSecurity with BiGRU Attention Models

    16.42-16.54

    Authors: Ricardo Anibal Matamoros Aragon, Alessandro Solinas, Simone Re, Matteo Oliveri and Francesco Epifania.

    Affiliations: Informattiva, Social Things, Unimib

  • An empirical analysis of attention based solution applied to text summarization tasks

    16.54-17.06

    Authors: Simone Deola, Luca Leo Del Vescovo and Ricardo Anibal Matamoros Aragon.

    Affiliations: Unimib, Social Things

  • Marrying LLMs with Domain ExpertValidation for Causal Graph Generation

    17.06-17.18

    Authors: Alessandro Castelnovo, Riccardo Crupi, Fabio Mercorio, Mario Mezzanzanica, Daniele Potertì and Daniele Regoli.

    Affiliations: Intesa Sanpaolo S.p.A, Unimib

  • Detecting Zero-Day Vulnerabilities in CMS Platforms: An In-depth Analysis Using DeepLog

    17.18-17.30

    Authors: Alberto Schiaffino, Matteo Reina, Ricardo Matamoros, Alessandro Solinas and Francesco Epifania.

    Affiliations: Engitel, Social Things, Unimib

  • Boosting Power Grid Efficiency: Meta-RLApproaches

    17.30-17.42

    Authors: Cherindranath Reddy, Satyesh Das, Surya Narayana Murthy Babu Batchu and Gurram Venkata Yaswanth.

    Affiliations: Bangalore RNS Institute of Technology, Rajiv Gandhi Institute of Petroleum Technology, National institute of technology Durgapur, Indian institute of technology Dhanbad

  • Utilizing LSTM Neural Networks for Sentiment Analysis ofTweets

    17.42-17.54

    Authors: Manan Gangwani.

    Affiliations: Podar International School - High School student

  • Quantifying CreditPortfolio sensitivity to asset correlations with interpretable generative neural networks

    17.54-18.06

    Authors: Sergio Caprioli, Emanuele Cagliero and Riccardo Crupi.

    Affiliations: Intesa Sanpaolo S.p.A

  • Concluding Remarks

    18.06-18.15

Info

Accepted Papers

Authors Title
Aketh Kilaru, Anushka Shah and Swoichha Adhikari Enhancing Classification in UTD-MHAD Dataset: Utilizing Recurrent Neural Networks in Ensemble-Based Approach for Human Action Recognition
Cherindranath Reddy, Satyesh Das, Surya Narayana Murthy Babu Batchu and Gurram Venkata Yaswanth Boosting Power Grid Efficiency: Meta-RL Approaches
Manan Gangwani Utilizing LSTM Neural Networks for Sentiment Analysis of Tweets
Francesco Stranieri, Alberto Archetti, Enrico Robbiano, Chaaben Kouki and Fabio Stella Drug Inventory Control: Human Decisions versus Deep Reinforcement Learning
Alessandro Castelnovo, Riccardo Crupi, Fabio Mercorio, Mario Mezzanzanica, Daniele Potertì and Daniele Regoli Marrying LLMs with Domain Expert Validation for Causal Graph Generation
Sergio Caprioli, Emanuele Cagliero and Riccardo Crupi Quantifying Credit Portfolio sensitivity to asset correlations with interpretable generative neural networks
Snehal Patil, Supriya Alavala, Ambar Gharat and Akshath Kamath Deep Learning MRI Analysis for Automated Knee Injury Diagnosis
Alberto Schiaffino, Matteo Reina, Ricardo Matamoros, Alessandro Solinas and Francesco Epifania Detecting Zero-Day Vulnerabilities in CMS Platforms: An In-depth Analysis Using DeepLog
Giulia Cisotto, Dagmawi Delelegn Tegegn, Alberto Zancanaro, Ivan Reguzzoni, Edoardo Lotti, Sara L. Manzoni and Italo F. Zoppis An AI-empowered energy-efficient portable NIRS solution for precision agriculture: A pilot study on a citrus fruit
Matteo Garavaglia, Alessandro Solinas, Ricardo Anibal Matamoros Aragon, Stefania Bandini and Francesco Epifania The use of impressions in Recommender Systems: improving complete and semi cold-start
Ricardo Anibal Matamoros Aragon, Alessandro Solinas, Simone Re, Matteo Oliveri and Francesco Epifania Enhancing Online Educational Resource Security with BiGRU Attention Models
Simone Deola, Luca Leo Del Vescovo and Francesco Epifania An empirical analysis of attention based solution applied to text summarization task
Igor Menghini NLP for market and competitive intelligence
Quocdung Nguyen, Hoangnam Pham, Duyhung Dao, Quangmanh Do andVanha Tran Prompt-Based Fashion Outfits Retrieval and Recommender System Using Binary Hashing

Committee

Organizers

Francesco Epifania

CEO & Co-founder Social Thingum

Francesco Epifania is CEO & founder of Social Things srl, he was a research assistant in Computer Science at the University of Milan and Ph.D candidate at the University of Milano Bicocca. He has received 3 degrees and Ph.D in Computer Science.

Matteo Garavaglia

Data Engineering & PhD Student

I am a PhD Candidate in Computer Science at the University of Milano Bicocca, where my research focuses on advanced topics in the field of Data Engineering and Artificial Intelligence. Simultaneously, I hold the position of Data Engineer and AI Researcher at AITECH4T, where I am actively involved in developing and implementing cutting-edge AI solutions. As a PhD Candidate, my primary objective is to conduct original research, contribute to the existing body of knowledge in the domain of Computer Science...

Emanuele Frontoni

Full Professor of Computer Science UNIMC

Emanuele Frontoni joined the Dept. of Information Engineering (DII) at the Università Politecnica delle Marche, as a Ph.D. student in "Intelligent Artificial Systems".

Simone Deola

Machine Learning Engineer & PhD Student

Developing ML solutions for third-party companies using custom technologies and ready-to-use solutions. I am currently collaborating with the Bicocca University of Milan as part of a PhD Executive project. My research area is mainly focused on NLP technologies, mainly in the area of conversational algorithms.

Ricardo Matamoros

Project Manager Computer Science & PhD candidate

Master's degree at the Department of Computer Science, University of Milan Bicocca. In his career, he has focused on topics related to the domains of Artificial Intelligence and Bioinformatics. His main activities are Agile management of the development of various projects throughout their lifecycle, experimental analysis and comparison of different solution methodologies for various AI problems, implementation and development of different types of recommendation systems, and use of techniques belonging to deep learning to improve the state of the art.

Committee

Members

Ernesto Damiani

Full Professor, Department of Computer Science, University of Milan Senior Director at Robotics and Intelligent Systems Institute, Khalifa University Director, Center for Cyber Physical Systems, Khalifa University President, Consortium of Italian Computer Science Universities (CINI)

Donato De Ieso

Co-Founder & CEO, dilium srl Board Member and AI Group Coordinator, Assintel

Guido Di Fraia

Associate Professor, Vice Rector for Innovation and Artificial Intelligence Department of Communication, Arts and Media “Giampaolo Fabris”, IULM University in Milan Vice Rector for Innovation and Artificial Intelligence Founder and CEO, IULM AI LAB

Alberto Fioravanti

Chairman, Digital Magics

Iuri Frosio

Principal Research Scientist, NVIDIA

Althin Kadareja

CEO, Cardo AI

Eugenia Kovatcheva

Associate Professor, Department of Information Technology, University of Library Studies and Information Technologies (ULSIT), Sofia Scientific Secretary, Department of Information Science UNESCO Chair ICT in Library Studies, Education and Cultural Heritage, ULSIT

Giulio Massucci

CEO & Co-Founder, Wavenure

Marco Leonardi

Machine Learning Scientist at lastminute.com

Luca Nardone

Head of Artificial Intelligence & Automation at Unipol Group

Filippo Neri

Explicable Artificial Intelligence Department of Electrical and Computer Engineering University of Naples "Federico II"

Roumen Nikolov

Department of Information Technologies, University of Sofia Chair holder of the UNESCO chair in ICT at Sofia

Alessandro Rozza

Chief Research Officer and Chief Machine Learning Scientist lastminute.com

Info

Questions

While the event is indeed officially in presence, we will offer the possibility of connecting and presenting remotely. Streaming will also be useful for visually impaired participants, participating in presence with their laptop/tablet. Remote participation requires the payment of the same fee as the participation in presence.

Each workshop will be granted a free registration to the event. Organizers may use it as they wish, for instance, offering it to an invited speaker. As for the actual registration costs, they are expected to be as follows: student early € 300, regular early € 350, student late € 380, regular late € 430, with the early cut-off date set on 16th of October

The social event participation fee is + € 80, irrespective of the registration date