Journal of Computing and Information Science in Engineering

Rizzi, Ph.D.

Areas of Interest

University of Bergamo, Italy
She is Full Professor of Technical Drawing and PLM at University of Bergamo, where she is also Head of the Department of Management, Information and Production Engineering since 1 September 2014. Member of the Academic Senate of the University of Bergamo since October 2015. Member of Technology Transfer Board at University of Bergamo since September 2016. Member of the Management Board of the International Medical School, University of Bergamo, Università di Milano Bicocca and University of Surrey, UK, since February 2017. She is one of the founders of the academic BiGFLO spin-off ( whose aim is to develop software solutions to support companies during product and process innovation. At present, she coordinates a research group composed by 8 people and a number of graduate students. She is working in the area of product development process tools and techniques (CAD, CAM, PDM, PLM, etc.) since 1985. Current Research topics are: Virtual prototyping, Ergonomics and Virtual humans modelling, Virtual and Augmented Reality, Additive Manufacturing, Physics based modelling and simulation, Knowledge-based systems, Eco-design, Methodologies and tools for systematic innovation and Intellectual Property Management. She participated to several European projects funded by UE and National research projects also as project co-ordinator. She is reviewer for the European Commission within the framework of V, VI and VII Framework Programme and Horizon2020. She is author and co-author of more than 200 scientific publications in international journals and conference proceedings as well as member and chair of international conference scientific committees.

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Special Issue on Geometric Data Processing and Analysis for Advanced Manufacturing

Geometric information, such as three-dimensional (3D) shapes and network topologies, has been increasingly explored in manufacturing research. For example, characterizing geometric information in 3D-printed parts, in-situ or ex-situ, opens opportunities for defect detection, quality improvement, and product customization. However, geometric data mining remains critically challenging. Geometric information is embedded in complex data structures, such as 3D point clouds, graphs, meshes, voxels, high-dimensional images, and tensors, which possess challenges for analysis due to their high-dimensionality, high-volume, unstructured, multimodality characteristics. Additional challenges stem from compromised data quality (e.g., noisy and incomplete data), the need for registration, etc.


2023 Reviewer’s Recognition

The Editor and Editorial Board of the Journal of Computing and Information Science in Engineering would like to thank all of the reviewers for volunteering their expertise and time reviewing manuscripts in 2023. Serving as reviewers for the journal is a critical service necessary to maintain the quality of our publication and to provide the authors with a valuable peer review of their work.


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