Differenze tra le versioni di "Giada Lops"

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==2026==
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<paper authors="Giada Lops, Francesco De Paola, Vito Andrea Racanelli, Gioacchino Manfredi, Luca De Cicco, Saverio Mascolo" conference="IFAC World Congress"  place="Busan, South Korea" date="August 2026">
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Data-Driven Control of Type 2 Diabetes Progression via Personalized Physical Activity
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</paper>
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<paper authors="Giada Lops, Taha Ramdan, Vito Andrea Racanelli, Luca De Cicco, Saverio Mascolo" conference="European Control Conference (ECC)"  place="Reykjavík, Iceland" date="July 2026">
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Bridging Clinical Knowledge and Reinforcement Learning in Automated Insulin Delivery: An LLM-in-the-Loop Approach
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</paper>
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<paper authors="Federico Baldisseri, Giada Lops, Mohab Mahdy Helmy Atanasious, Danilo Menegatti, Valentina Becchetti, Francesco Delli Priscoli, Saverio Mascolo, Vito Andrea Racanelli, Andrea Wrona" conference="European Control Conference (ECC)"  place="Reykjavík, Iceland" date="July 2026">
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Safe Deep Reinforcement Learning Control of Type 1 Diabetes
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</paper>
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==2025==
 
==2025==
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<paper authors="Giada Lops, Gioacchino Manfredi, Vito Andrea Racanelli, Luca De Cicco, Saverio Mascolo"  conference="Special Session SMCs-DAY: Data-Driven Control for Human-Machine Systems, Automatica.it 2025" place="Perugia and Assisi, Italy" date="Sept. 2025">
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Safe Learning-based Automated Insulin Delivery for Personalized Type 1 Diabetes Treatment
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</paper>
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<paper authors="Federico Baldisseri, Mohab M. H. Atanasious, Valentina Becchetti, Antonio Di Paola, Giada Lops, Danilo Menegatti, Andrea Wrona, Saverio Mascolo, Francesco Delli Priscoli" conference="11th International Conference on Control, Decision and Information Technologies (CoDIT)"  place="Split, Croatia" date="July 2025" pdf="codit2025.pdf">
 
<paper authors="Federico Baldisseri, Mohab M. H. Atanasious, Valentina Becchetti, Antonio Di Paola, Giada Lops, Danilo Menegatti, Andrea Wrona, Saverio Mascolo, Francesco Delli Priscoli" conference="11th International Conference on Control, Decision and Information Technologies (CoDIT)"  place="Split, Croatia" date="July 2025" pdf="codit2025.pdf">
 
A Quantitative Comparison of Deep Reinforcement Learning Algorithms for Type 1 Diabetes Control
 
A Quantitative Comparison of Deep Reinforcement Learning Algorithms for Type 1 Diabetes Control

Revisione 15:45, 28 Apr 2026

Giada Lops
Eng, PhD Student
Contacts
C3Lab, Dipartimento di Ingegneria Elettrica e dell'Informazione (DEI), Politecnico di Bari, ITALY
Lab: +39 080 596 3851
Email: g.lops@phd.poliba.it
LinkedIn: https://www.linkedin.com/in/giada-lops-972659246/
OrcID: https://orcid.org/0009-0005-7863-9183
Google Scholar: https://scholar.google.com/citations?user=gJm0UNAAAAAJ
Short CV
Giada Lops is a Ph.D. student in Electrical and Information Engineering at Politecnico di Bari and a member of the Control Engineering and Computer Science Laboratory (C3Lab). Her research focuses on control strategies for medical systems, particularly reinforcement learning and model predictive control for insulin therapy. She holds both Bachelor's and Master's degrees in Medical Systems Engineering from Politecnico di Bari, graduating with honors. Her Master's thesis focused on reinforcement learning for optimizing bolus insulin delivery.
Research topics
  • Reinforcement Learning and Model Predictive Control for Insulin Therapy
Publications

2026

  • Giada Lops, Francesco De Paola, Vito Andrea Racanelli, Gioacchino Manfredi, Luca De Cicco, Saverio Mascolo
    Data-Driven Control of Type 2 Diabetes Progression via Personalized Physical Activity
    IFAC World Congress, Busan, South Korea, August 2026
  • Giada Lops, Taha Ramdan, Vito Andrea Racanelli, Luca De Cicco, Saverio Mascolo
    Bridging Clinical Knowledge and Reinforcement Learning in Automated Insulin Delivery: An LLM-in-the-Loop Approach
    European Control Conference (ECC), Reykjavík, Iceland, July 2026
  • Federico Baldisseri, Giada Lops, Mohab Mahdy Helmy Atanasious, Danilo Menegatti, Valentina Becchetti, Francesco Delli Priscoli, Saverio Mascolo, Vito Andrea Racanelli, Andrea Wrona
    Safe Deep Reinforcement Learning Control of Type 1 Diabetes
    European Control Conference (ECC), Reykjavík, Iceland, July 2026

2025

  • Giada Lops, Gioacchino Manfredi, Vito Andrea Racanelli, Luca De Cicco, Saverio Mascolo
    Safe Learning-based Automated Insulin Delivery for Personalized Type 1 Diabetes Treatment
    Special Session SMCs-DAY: Data-Driven Control for Human-Machine Systems, Automatica.it 2025, Perugia and Assisi, Italy, Sept. 2025
  • Federico Baldisseri, Mohab M. H. Atanasious, Valentina Becchetti, Antonio Di Paola, Giada Lops, Danilo Menegatti, Andrea Wrona, Saverio Mascolo, Francesco Delli Priscoli
    A Quantitative Comparison of Deep Reinforcement Learning Algorithms for Type 1 Diabetes Control
    11th International Conference on Control, Decision and Information Technologies (CoDIT), Split, Croatia, July 2025 (PDF)
  • Giada Lops,Vito Andrea Racanelli, Gioacchino Manfredi, Luca De Cicco, Saverio Mascolo
    A Safety Aware Deep Reinforcement Learning Technique for Automated Insulin Delivery
    33rd Mediterranean Conference on Control and Automation, Tangier, Morocco, June 2025 (PDF)
  • Giada Lops,Vito Andrea Racanelli, Gioacchino Manfredi, Luca De Cicco, Saverio Mascolo
    A Deep Deterministic Policy Gradient control algorithm for Automatic Insulin Delivery
    1st IFAC Workshop on Engineering Diabetes Technologies (EDT 2025), Valencia, Spain, May 2025 (PDF)
Ricavato da "https://c3lab.poliba.it/index.php?title=Giada_Lops&oldid=7750"
Giada Lops
Eng, PhD Student
Contacts
C3Lab, Dipartimento di Ingegneria Elettrica e dell'Informazione (DEI), Politecnico di Bari, ITALY
Lab: +39 080 596 3851
Email: g.lops@phd.poliba.it
LinkedIn: https://www.linkedin.com/in/giada-lops-972659246/
OrcID: https://orcid.org/0009-0005-7863-9183
Google Scholar: https://scholar.google.com/citations?user=gJm0UNAAAAAJ
Short CV
Giada Lops is a Ph.D. student in Electrical and Information Engineering at Politecnico di Bari and a member of the Control Engineering and Computer Science Laboratory (C3Lab). Her research focuses on control strategies for medical systems, particularly reinforcement learning and model predictive control for insulin therapy. She holds both Bachelor's and Master's degrees in Medical Systems Engineering from Politecnico di Bari, graduating with honors. Her Master's thesis focused on reinforcement learning for optimizing bolus insulin delivery.
Research topics
  • Reinforcement Learning and Model Predictive Control for Insulin Therapy
Publications

2025

  • Federico Baldisseri, Mohab M. H. Atanasious, Valentina Becchetti, Antonio Di Paola, Giada Lops, Danilo Menegatti, Andrea Wrona, Saverio Mascolo, Francesco Delli Priscoli
    A Quantitative Comparison of Deep Reinforcement Learning Algorithms for Type 1 Diabetes Control
    11th International Conference on Control, Decision and Information Technologies (CoDIT), Split, Croatia, July 2025 (PDF)
  • Giada Lops,Vito Andrea Racanelli, Gioacchino Manfredi, Luca De Cicco, Saverio Mascolo
    A Safety Aware Deep Reinforcement Learning Technique for Automated Insulin Delivery
    33rd Mediterranean Conference on Control and Automation, Tangier, Morocco, June 2025 (PDF)
  • Giada Lops,Vito Andrea Racanelli, Gioacchino Manfredi, Luca De Cicco, Saverio Mascolo
    A Deep Deterministic Policy Gradient control algorithm for Automatic Insulin Delivery
    1st IFAC Workshop on Engineering Diabetes Technologies (EDT 2025), Valencia, Spain, May 2025 (PDF)