Publications associées à Education in Process Systems Engineering: Why it matters more than ever and how it can be structured

Publications associées (38)

How data structures affect generalization in Kernel Methods and Deep Learning

Artificial Intelligence has revolutionized numerous fields, driving advancements in healthcare, finance, and autonomous systems. At the core of this revolution lies Deep Learning---algorithms that learn representations from data through computational layer ...

EPFL2025

On the Guarantees of Minimizing Regret in Receding Horizon

Giancarlo Ferrari Trecate, Luca Furieri, Andrea Martin

Toward bridging classical optimal control and online learning, regret minimization has recently been proposed as a control design criterion. This competitive paradigm penalizes the loss relative to the optimal control actions chosen by a clairvoyant policy ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

The impact of different methods of increasing the intensity of compassion in engineering ethics cases

Roland John Tormey, Nihat Kotluk

Despite the growing interest in emotions in engineering education, empirical research on incorporating them into engineering ethics education is limited. Therefore, we designed this experimental study to assess how different methods for integrating compass ...

2024

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

Richard Pitts, Federico Alberto Alfredo Felici, Federico Pesamosca, Anna Ngoc Minh Trang Vu

The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control ...

Elsevier Science Sa2024

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning

Zhuan Shi, Gang Wang

Federated learning (FL) is a privacy-preserving collaboratively machine learning paradigm. Traditional FL requires all data owners (a.k.a. FL clients) to train the same local model. This design is not well-suited for scenarios involving data and/or system ...

IJCAI2024

Co-optimising Design and Operation of Energy Systems using Reinforcement Learning

Marine Dominique Cauz

The energy transition is ongoing, in Switzerland and abroad, leading to an ever-increasing development of renewable energy sources. These sources are decentralised, heterogeneous, come with a high dependance on weather conditions, and are therefore hard t ...

EPFL2024

Design ontology for cognitive thread supporting traceability management in model-based systems engineering

Dimitrios Kyritsis, Jinzhi Lu, Yan Yan

Industrial information integration engineering (IIIE) is an interdisciplinary field to facilitate the industrial information integration process. In the age of complex and large-scale systems, model-based systems engineering (MBSE) is widely adopted in ind ...

Elsevier2024

Evaluating the Impact of Learner Control and Interactivity in Conversational Tutoring Systems for Persuasive Writing

Tanja Christina Käser Jacober, Thiemo Wambsganss

Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner cont ...

2024

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Loris Di Natale

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

EPFL2024

Microbial electrochemical bioremediation of petroleum hydrocarbons (PHCs) pollution: Recent advances and outlook

Sami Rtimi

Soil contamination by petroleum hydrocarbons (PHCs) causes various acute problems such as crop growth, yield, and grain quality. Many Physico-chemical and biological approaches are employed to remove the PHCs from polluted soil. However, some of these appr ...

ELSEVIER SCIENCE SA2023

Critical analysis of decision variables for high-throughput experimentation (HTE) with perovskite solar cells

Mohammad Khaja Nazeeruddin, François Maréchal, Naveen Bhati

Perovskite solar cells are among the most dominant emerging PV technologies which have shown unparallel improvement in power conversion efficiency in just over a decade. Long charge carrier diffusion lengths and lifetimes, high absorption coefficients, ban ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

Jürg Alexander Schiffmann, Cyril Picard

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

Amer Soc Mechanical Engineers2023

Making Bridges Sustainable

Eugen Brühwiler

Lack of incentives mainly explains why the implementation of novel methods and technologies in bridge engineering practice is generally postponed by the engineering community despite the urgent need to advance also bridge engineering to meet the objectives ...

Taylor and Francis / CRC Press2023

Real-time model calibration with deep reinforcement learning

Olga Fink

The real-time, and accurate inference of model parameters is of great importance in many scientific and engineering disciplines that use computational models (such as a digital twin) for the analysis and prediction of complex physical processes. However, f ...

2022

Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice

Martin Josifoski

Meta-Learning aims to speed up the learning process on new tasks by acquiring useful inductive biases from datasets of related learning tasks. While, in practice, the number of related tasks available is often small, most of the existing approaches assume ...

2023

Emotional labor experienced in team-projects: A comparison of engineering and hospitality students

Roland John Tormey, Nihat Kotluk

Team projects are an integral part of the student learning experience. However, emotions can significantly affect student performance during team projects. Students use different emotion regulation strategies, such as surface-acting (emotive dissonance) an ...

2023

3D Printed Acoustically Programmable Soft Microactuators

Mahmut Selman Sakar, Murat Kaynak, Amit Yedidia Dolev

The concept of creating all-mechanical soft microrobotic systems has great potential to address outstanding challenges in biomedical applications, and introduce more sustainable and multifunctional products. To this end, magnetic fields and light have been ...

2023

Multi-agent Learning with Privacy Guarantees

Elsa Rizk

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

EPFL2023

Biochemistry of Aminoacyl tRNA Synthetase and tRNAs and Their Engineering for Cell-Free and Synthetic Cell Applications

Sebastian Maerkl, Ragunathan Bava Ganesh

Cell-free biology is increasingly utilized for engineering biological systems, incorporating novel functionality, and circumventing many of the complications associated with cells. The central dogma describes the information flow in biology consisting of t ...

FRONTIERS MEDIA SA2022

Semiconductor-based device architectures in multimaterial fibers

William Nicolas Duncan Esposito

Semiconductor materials have given rise to today's digital technology and consumer electronics. Widespread adoption is closely linked to the ability to process and integrate them in devices at scale. Where flexibility and large surfaces are required, such ...

EPFL2023