Agenda PhD Day (July 6th, 2023)
| 10:00-10:45 T024 room (ground floor) | Talk “Mental health and stress among phd students“ prof. Massimo Miglioretti slides |
| 10:45-11:15 | coffee break |
| 11:15-12:45 Sala Seminari (first floor) | Poster Session 1 |
| 12:45-14:30 | Lunch break |
| 14:30-15:30 T024 room (ground floor) | Talk “Health Big Data: a step forward for data management in the Italian medical landscape” prof. Letizia Tanca |
| 15:30-16:00 | coffee break |
| 16:00-17:30 Sala Seminari (first floor) | Poster Session 2 |
Talk Abstracts
Mental health and stress among phd students
Prof. Massimo Miglioretti (Univ. Milano-Bicocca)
Stress during the doctoral study is common; however, its presence is of concern to students as it has a deleterious impact on well-being and performance, and to the university, which has a duty of care to students and the desire to promote a supportive research environment. In fact, while some stress is beneficial for personal and professional growth, prolonged exposure to stress may lead to mental health problems such as burnout or other mental disorders.
My speech, considering the more accredited theory of stress and well-being, will present the more relevant stress factors in the phd students’ work and in academia and will discuss them from the perspective of work-life balance and sustainable employability. Finally, I will give some indication about more effective techniques in stress management.
Massimo Miglioretti is a full professor of Work and Organizational Psychology at the University of Milano-Bicocca and scientific director of the Bicocca Center of Applied Psychology (BiCApP). His main research topics regard the relationship between work and health, workers’ wellbeing, the use of technology at work, and their consequences for workers’ health and wellbeing. He is a member of QoL@work, the Italian group of academic researchers who develop research activities on stress and well-being in Academia.
Health Big Data: a step forward for data management in the Italian medical landscape
Prof. Letizia Tanca (Politecnico di Milano)
Understanding the molecular mechanisms underlying diseases is radically changing the landscape of medicine (e.g., Precision, or Custom Medicine). This revolution was initiated by Genomics, which was later joined by other Omics approaches (transcriptomics, metabolomics, radiomics, etc.) that have increased the granularity of the investigations in healthy and diseased cells. The systematic collection and sharing of omics and clinical data from individuals, and in perspective of real-world data, health and environmental data, will generate a universal resource of knowledge for health and care management.
The Health Big Data project aims at the creation of a technological platform that allows the generation, extraction, collection, sharing and analysis of scientific and clinical data related to the patients of each of the 50 Italian institutes (IRCCS) belonging to the project. The type of data that will be processed includes imaging and omic data, clinical data (electronic medical record, patient follow-up data, real world data) and further data provided by patients. The platform must also guarantee connectivity of the project institutes with other Research Institutes, database of the National Health Service and international public ones. After a general presentation of the project, I will concentrate on the main issues related to the integration platform. Data Lake technologies are promising solutions for enhancing data management and analysis capabilities in the healthcare domain; we can rely on them to manage the complexity of big data volume and variety, providing data analysts with a self-service environment in which advanced analytics can be applied. In this talk I will discuss the adoption of a data lake federation through which organizations could achieve further benefits by sharing data.
These requirements imply new research challenges: the collected data should be accurately described in order to document their quality, facilitate their discovery, define security and privacy policies.
Letizia Tanca is a full professor at Politecnico di Milano (Department of Electronics, Information and Bio-Engineering – DEIB), where she served as Chairman of the Board of Studies in Computer Engineering (Milan) from 2000 to 2006, while from 2011 in the end of 2015 served as Director of the Computer Science Area of DEIB. During her career, she taught courses on the Foundations of Computer Science, Databases and Methodologies and Technologies for Information Systems. Her research interests have included databases for mobile devices, customizing and integrating data in context-driven, peer-to-peer distributed databases, design of quality- and context-aware databases and applications, the data curation pipeline before data analysis.
Poster Session 1
Jorge Avila (cycle XXXVII), PangeBlocks Customized construction of Pangenome Graphs
Gianmaria Balducci (cycle XXXVIII), Jointly Fine-Grained Named Entity-Relation extraction in news articles
Jessica Amianto Barbato (cycle XXXVII), Bridging the gap between human-gaze studies and table summarization
Mirko Barbato (cycle XXXVI), Ticino: A Multi-modal Remote Sensing Dataset for Semantic Segmentation
Alessandro Bregoli (cycle XXXVI), Analyzing complex systems with cascades using continuous time Bayesian networks
Davide Cozzi (cycle XXXVIII), μ-PBWT: a lightweight r-indexing of the PBWT for storing and querying UK Biobank Data
Simone Deola (cycle XXXVII), Using Attention to summarize texts Solving the task of abstractive text summarization using Attention based solutions
Ilaria Erba (cycle XXXVI), Color Constancy Beyond RGB Images multispectral and video extensions
Matteo Gabardi (cycle XXXVII), Convolutional neural networks for signal denoising on X-ray detectors
Marco Gigli (cycle XXXVI), Multi-armed Bandits for Performance Marketing
Pranav Kasela (cycle XXXVII), Personalized approaches to Information Retrieval
Chiara Natali (cycle XXXVIII), Frictional Decision Support Systems Stimulating Cognitive Engagement By Design
Ivan Orlov (cycle XXXVI), Assessment of Car Damage from Photographs
Riccardo Pozzi (cycle XXXVIII), Human-in-the-loop Adaptation for Domain Specific Entity Extraction
Renzo Alva Principe (cycle XXXVII), Addressing the Problem of Long Document Classification
Lorenzo Rovida (cycle XXXVIII), Securing MLaaS with Homomorphic Encryption Finding an intersection between Machine Learning and Cryptography
Sahar Shah (cycle XXXVIII), Continual Learning: LIME-based Surrogate Model for Interpretable Predictive Modeling of Black Box Systems
Rishabh Upadhyaym (cycle XXXVI), Improve the Effectiveness of Health Information Retrieval by considering Information Genuineness based on Scientific Evidence
Poster Session 2
Hamza Amrani (cycle XXXVIII), Decoding Speech from Non-Invasive Brain Recordings
Alice Bernasconi (cycle XXXVII), Bayesian causal networks for cardiovascular risk management in breast cancer patients
Michele Carbonera (cycle XXXVIII), Deep Learning models for scenario generation considering spatial-temporal correlations
Matteo Garavaglia (cycle XXXVIII), Conversational Recommender Systems Open Challenges and a first proposal
Greta Greco (cycle XXXVI), A neurosymbolic approach to Fairness Declarative encoding of Fairness in Logic Tensor Networks
Giorgio Lazzarinetti (cycle XXXVII), Solving optimization problems on Complex Network with Deep Learning The role of memory and attention
Atieh Mahroo (cycle XXXVIII), Integration of the Artificial Intelligence Models with Mixed Reality Application
Ricardo Matamoros (cycle XXXVI), When Attention Turn To Be Explanation A Case Study in Recommender Systems
Oscar Javier Espitia Mendoza (cycle XXXVI), Curriculum learning for Clinical Trials Retrieval
Gian Carlo Milanese (cycle XXXVI), Approximate Reasoning with Order-Sorted Feature Logic
Alberto Minora (cycle XXXVIII), Distributed Learning in Safe Human-Robot Cooperation
Federico Moiraghi (cycle XXXVII), Hierarchical Text Classification using Natural Language Label Descriptions a case study on CPV taxonomy
Ali Qurban (cycle XXXVIII), Testing the evolution: addressing bugs in ML and DL systems
Giulia Rizzi (cycle XXXVII), The many faces of Hateful Content Detection: from Bias to Perspectivism
Jacopo Talpini (cycle XXXVII), Federated Learning and Uncertainty-Aware ML Models for Enhanced Network Intrusion Detection
Matteo Vaghi (cycle XXXVI), Uncertainty Quantification of DNN-based Localization Systems
Alessio Zanga (cycle XXXVII), Causal Discovery with Missing Data in a Multicentric Clinical Study
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