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19 - 21 February, 2027 - Valletta, Malta

Within the 20th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSTEC 2027

CO-CHAIRS

	Roberta Bardini Politecnico di Torino Italy
Short Bio Roberta Bardini leads the intelligent biofabrication research line at the SMILIES research group, Department of Control and Computer Engineering, Politecnico di Torino, where she is Assistant Professor (RTD-A). She holds an M.Sc. in Molecular Biotechnology from the University of Turin (2014) and a Ph.D. in Control and Computer Engineering from Politecnico di Torino (2019). Her research develops computational methods connecting fabrication and culture protocols to biological organization, maturation and function, drawing on mechanistic and multiscale modelling, machine learning, optimization, digital twins and multimodal data integration. She also works on neuronal dynamics and plasticity and on neuromorphic computing. She is the principal inventor of two national patents (2021, 2022) on the computational generation of biofabrication protocols, developed within the cultura technology transfer initiative and supported by proof-of-concept grants from LIFTT (2020–2021) and the Italian Ministry of Economic Development (2021–2022), and by a research grant from the Just The Woman I Am initiative (2022–2023). She co-authored Bardini, R., Di Carlo, S., "Computational methods for biofabrication in tissue engineering and regenerative medicine – a literature review" (Computational and Structural Biotechnology Journal, 2024). A central element of her research vision is that progress in intelligent biofabrication depends on interdisciplinary collaboration across computational and systems biology, bioengineering, tissue engineering, control and the experimental life sciences, and on open and FAIR computational ecosystems in which models, datasets, protocols, benchmarks, and software can be shared, compared, and reused. Her work in this direction includes contributing to SMILIE's open-source software (https://github.com/smilies-polito) and FAIR digital assets (https://zenodo.org/communities/smilies/records).

	Laurence Calzone Computational Oncology Unit, Institut Curie France
Short Bio Dr. Laurence Calzone is Senior Researcher and co-PI of the Computational Systems Biology of Cancer group, specialising in systems biology, mechanistic modelling, and computational oncology. She has held leadership roles in several EU-funded initiatives and developed computational tools supporting personalised cancer modelling through multimodal data integration and mathematical/statistical inference. More specifically, Dr Laurence Calzone has a long experience in developing mathematical models based on nonlinear ordinary differential equations, Boolean formalism and agent-based approaches to address specific biological questions related to cancer with the aim to provide personalized treatments. She is involved in developing methods and tools to build and integrate omics data into these models. She is trying to connect machine learning approaches to mechanistic modelling. She is an active member of modelling communities such as CoLoMoTo, (http://www.colomoto.org/), Bioss (https://gt-bioss.cnrs.fr/), or BIDT (https://immunedt.github.io/team/).

	Miriam Filippi Institute for Robotics and Intelligent Systems, ETH Zurich Switzerland
Short Bio Dr. Miriam Filippi is an Established Researcher in Bio-hybrid Robotics and Principal Investigator at the Soft Robotics Lab, ETH Zurich, where she leads research on biofabrication, intelligent biological machines, and adaptive, biomimetic robotic systems. Her work integrates living tissues with synthetic structures to create biohybrid robots capable of sensing, actuation and autonomous function, with applications in environmental monitoring, service robotics and medical technologies. She earned her Ph.D. in Pharmaceutical and Biomolecular Sciences at the University of Turin, working on nano- and microsystems for theranostics and regenerative therapies, and subsequently advanced tissue engineering research at the University Hospital of Basel, exploring nanomaterials, magnetic actuation and regenerative strategies for bone, cartilage and nerve implants. At ETH Zurich she combines biology, materials science and robotics to develop sustainable biohybrid platforms, including cardiac and skeletal muscle tissue-based actuators, neural-inspired control architectures and integrated feedback systems. Her recent work focuses on machine learning approaches to study biomechanics and bioelectronic signals as developmental cues, enabling a deeper understanding of how functional tissue properties emerge over time and how they can be predicted and guided during biofabrication. In parallel, she develops computational and AI-driven frameworks to model tissue maturation and functional evolution, aiming to make biofabrication more controllable, reproducible and sustainable. Her contributions have been recognised through the Wittenstein Biointelligence Award (2024), the Micromachines Young Investigator Award (2025), the IEEE EMBS Early Career Achievement Award (2026) and the MDPI Young Women in Engineering Award (2026). She is also a sustainability officer promoting eco-conscious biomanufacturing and robotics.

	Diana Massai Politecnico di Torino Italy
Short Bio Diana Massai is Associate Professor of Bioengineering at Politecnico di Torino (Italy), where she leads the Bioreactor Division of the Solid and Fluid Biomechanics Group at the Department of Mechanical and Aerospace Engineering and teaches the course “Bioreactors.” She is a member of the Executive Board of the Italian Interuniversity Center for the Promotion of the 3Rs Principles in Teaching and Research (Centro 3R). She has more than 15 years of experience in the design and development of advanced bioreactor technologies and experimental platforms for dynamic cell and engineered tissue culture, mechanotransduction studies, and, more recently, cellular agriculture. Her research combines engineering, biology, and multiscale mechanical characterization to develop physiologically relevant in vitro 3D models and investigate the interactions between cells, biomaterials, and biophysical stimuli. A major focus of her current research is the development of New Approach Methodologies (NAMs) based on advanced in vitro models and controlled bioreactors, with the aim of improving the physiological relevance, reproducibility, and translation of experimental studies while contributing to the implementation of the 3Rs principles. Her research activity strongly emphasizes the integration of quantitative experimental approaches with computational and data-driven methods, providing well-controlled experimental datasets for model development and validation. She is also actively engaged in technology transfer and in translating bioengineering research into innovative tools for biomedical and industrial applications.

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