Location: 📍 Trento - Verona | LinkedIn

Innovative, challenge-loving, and professional. Currently pursuing a National PhD. in Artificial Itellicenge at the University of Verona in collaboration with the University La Sapienza, Rome and Giordano Controls. We tackling the predictive maintance problem in HVAC systems with Giordano Controls. Ambitious, cheerful, and reliable. Passionate about startups and enjoy achieving goals as part of a team. CV

Artificial Intelligence | Explainability | Time Series Anomaly detection | BPMN | Healthcare Informatics | Time Series Classification | Strategy Synthesis |

Team working | Time management | Autonomy | Flexibility | Adaptability | Attention to detail | Excellent interpersonal skills| Problem solving | Initiative

• Institution: University of Verona, University La Sapienza - Rome
• Period: 2023 - Present

• Institution: Starting Finance
• Period: 09/2024 - 11/2024
• Location: Milan, Italy
• Link: certificate

• Institution: Bocconi University
• Link: certificate

• Institution: European Patent Academy
• Period: 06/2026
• Duration: 75 hours
• Grade: 80.00
• Certificate ID: mmEIjsXF5Z
• Link: certificate

• Institution: University of Verona
• Period: 2021 - 2023

• Institution: University of Trento
• Period: 2018 - 2021

• Institution: Liceo Scientifico G. Galilei
• Period: 2013 - 2018

• Abstract: "As business processes become increasingly complex, effectively modeling decision points, their likelihood,and resource consumption is crucial for optimizing operations. To address this challenge, this paper introduces a formal extension of the Business Process Model and Notation (BPMN) that incorporates choices, probabilities, and impacts, referred to as CPI. This extension is motivated by the growing emphasis on precise control within business process management, where carefully selecting decision pathways in repeated instances is crucial for conforming to certain standards of multiple resource consumption and environmental impacts. In this context we deal with the problem of synthesizing a strategy (if any) that guarantees that the expected impacts on repeated execution of the input process are below a given threshold. We show that this problem belongs to PSPACE complexity class; moreover we provide an effective procedure for computing a strategy (if present)."
• Authors: Emanuele Chini, Pietro Sala, Andrea Simonetti and Omid Zare
• Year: 2024
• Conference: Fifteenth International Symposium on Games, Automata, Logics, and Formal Verification
• Keywords: Business Process Management | Expected Impacts | Reactive Synthesis
• Link Code: [https://github.com/ansimonetti/PACO]
• Link publication: https://arxiv.org/abs/2410.22760

• Abstract: "The Business Process Modeling Notation (BPMN) is a diagrammatical notation to describe complex process models, and it can be used as a common language among stakeholders. These stakeholders could intervene in the development of the processes, also in an agile environment. Thus, the same process could evolve through different versions over time. BPMN has been already adopted in the healthcare domain, where designing healthcare processes is fundamental for delivering optimal and efficient services to patients without overburdening healthcare professionals. Adapting and updating BPMN processes within an agile development is paramount in the rapidly evolving healthcare domain. The challenges of migrating a process to its revised versions have been discussed since the introduction of BPMN. However, there is a lack of migration policies that consider compensation strategies when migrating to a revised version at runtime, combined with healthcare-related migration risk classes. In this paper, we propose a methodological framework that includes migration strategies to adopt when the user is already running the process in a previous version. We propose compensatory strategies to integrate the novelties of the revised process based on the actual users’ completion status, with a specific focus on the addition, modification, and removal of tasks. Moreover, the proposed framework includes a color-coded risk classification system encapsulating migration risks and potential impact on patients. This system provides a visual and intuitive way to understand potential risks, enabling clinicians to make informed decisions about the migration strategy. Finally, we showed an application of the proposed framework in a real-world scenario, that is, through an ERAS-inspired prehabilitation program for pancreatic surgery currently developed at the Verona Pancreas Institute."
• Authors: Matteo Mantovani, Emanuele Chini and Carlo Combi
• Year: 2024
• Conference: The 12th IEEE International Conference on Healthcare Informatics (IEEE ICHI 2024)
• Keywords: BPMN | BPMN framework | agile methodology | migration | BPMN migration | versioning
• DOI: https://ieeexplore.ieee.org/abstract/document/10628905

Research Collaboration – Explainable Knowledge Distillation in Time Series
2025

Collaboration with Prof. Germain Forestier on interpretable knowledge distillation methods for time series classification.

Predictive Maintenance for HVAC Systems
2023 – 2025

Development of AI pipelines and anomaly detection systems using TensorFlow and PyTorch.

• Institution: Fondazione Bruno Kessler (FBK)
• Period: 04/2023 - 06/2023
• Type: Internship
• Responsibilities: Optimizing the definition of the breast cancer care process modeled with BPMN 2.0 and integrating it between the TreC platform and the Camunda engine.

• Period: 2022 - 2023
• Type: Master Thesis
• Responsibilities: Developing frontend (Angular) and backend (using Camunda BPM engine) for an application that supports patients comprehensively in the month before pancreatic surgery.

• Period: 2021
• Type: Bachelor Thesis
• Responsibilities: Collaborated with Dr. Alessandra Tobaldi from the Neurocognitive Rehabilitation Center CERIN in Rovereto to develop an application aiding verbal apraxia rehabilitation. Developed the Android application and served as the liaison between the University and CERIN.

• Period: 06/2023 - 10/2023
• Type: Research grant
• Responsibilities: Collaborating with Prof. Pietro Sala to develop an interface that connects OCR-processed data with an NLP pipeline, allowing users to modify and/or add information.

• Program: Lifelong Learning Programme
• Institution: Visser't Hooft Lyceum, Leiden (Netherlands)
• Language: English
• Duration: 10/2017
• Description: Linguistic, scientific, and social sciences research project.

• Italian: Native
• English: FIRST Certificate, Cambridge English, Level B2, 2018
• German: CLA Certification, University of Verona, Level A2, 2023

• Name: Emanuele Chini
• Date of Birth: 11/06/1999
• Email: emanuele.chini@univr.it, emanuele.chini@uniroma1.it