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4. Andrea Visentin

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Biography

Andrea has a BSc and an MSc in Computer Engineering from the University of Padua (Italy) and completed a PhD at the Insight Centre for Data Analytics at UCC. He is currently a permanent lecturer at the School of Computer Science & IT. Moreover, he is a researcher at the Confirm Centre for Smart Manufacturing and the Insight Centre for Data Analytics.‍

Research Interests

My main research focuses on two main branches: algorithms for inventory control and deep learning applied to industrial problems. The first one is a continuation of my PhD work that I am developing in collaboration with colleagues from the Cork University Business School and the University of Edinburgh Business School. I work with bespoke solutions involving different algorithmic techniques (e.g. dynamic programming, branch-and-bound, binary search) and mathematical modelisation that leaves the computation to a solver (e.g. mixed-integer programming or constraint programming). The second is based on collaborations with industrial partners. We researched, designed and developed a Production Scheduler for a surgical blade production plant and deep learning approaches to forecasting a pump's motor failures based on vibrations, magnetic flux and energy consumption.  

I am leading Task 3.6 of TAILOR, a European networking project. The task focuses on the sustainability of AI solutions. I collaborated with the European Commission High-Level Expert Group on Artificial Intelligence (AI HLEG).

I was part of a research team that conducted in-depth interviews with European stakeholders at the end of 2019. These interviews aimed to collect feedback on the Assessment List for Trustworthy Artificial Intelligence (ALTAI) developed by the AI HLEG. In 2020, I developed an online interactive tool for creating and self-assessing ALTAIs submissions (link).‍

Publications

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Peer Reviewed Journals

	Year	Publication
	(2021)	'Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming' Visentin, Andrea; Prestwich, Steven; Rossi, Roberto; Tarim, S. Armagan (2021) 'Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming'. European Journal of Operational Research,   [DOI] [Full Text] [Details]

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Conference Publications

	Year	Publication
	(2021)	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI Dalla M.;Visentin A.;O'Sullivan B. (2021) Automated SAT Problem Feature Extraction using Convolutional Autoencoders Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI , pp.232-239 [DOI] [Details]
	(2019)	2019 IEEE 31ST INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2019) Visentin, A;Nardotto, A;O'Sullivan, B (2019) Predicting Judicial Decisions: A Statistically Rigorous Approach and a New Ensemble Classifier 2019 IEEE 31ST INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2019) , pp.1820-1824 [DOI] [Details]
	(2019)	World Congress on Global Optimization 2019 Visentin, Andrea; Prestwich, Steven D.; Rossi, Roberto; Tarim, Armagan (2019) Modelling Dynamic Programming-based global constraints in Constraint Programming World Congress on Global Optimization 2019 Metz, France, , 08-JUL-19 - 10-JUL-19 , pp.417-427   [DOI] [Full Text] [Details]
	(2018)	4th Global Conference on Artificial Intelligence SD Prestwich, R Rossi, SA Tarim, A Visentin (2018) Towards a Closer Integration of Dynamic Programming and Constraint Programming 4th Global Conference on Artificial Intelligence [Details]
	(2016)	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Visentin A.;Prestwich S.;Armagan Tarim S. (2016) Robust principal component analysis by reverse iterative linear programming Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , pp.593-605 [DOI] [Details]

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Teaching Activities

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Teaching Interests

As a teaching assistant, I covered lectures and labs for Artificial Intelligence II, Optimisation, Foundations of Computer Science II, Web Development I and Relational Databases I. I have been a lecturer in the Munster Programming Training (MPT) organised by the CS Department for two years (2017/18, 2018/19). I lectured Programming for Digital Humanities I (CS1202, AY 19/20) and Web Application Development (IS4439, AY 19/20 and 20/21). Since 2020, I have been lecturing Data Analytics for Digital Humanities I (CS2213) and II (CS2215) and Data Mining (CS6405).  I have teaching experience in: 

• Programming Languages (Python, C++, Java) 
• Algorithms Design and Analysis 
• Competitive Programming 
• Machine Learning
• Data Analysis 
• Data Mining
• Operations Research 
• Web Application Development
• Web Development
• Relational Databases (SQL)