IASIM-2024

Giulia Gorla, born in 1995, received her Bachelor’s degree in Chemistry and Industrial Chemistry in 2018 from the Università degli Studi dell’Insubria, where she also completed her Master’s degree in Chemistry in 2019. She earned her PhD in Chemical and Environmental Sciences in 2023, graduating with a dissertation titled "Infrared Spectroscopy and Chemometrics: Facing Analytical Chemistry Issues Through Data." Since January 2024, she has been working as a postdoctoral researcher in the Analytical Chemistry Department at UPV/EHU, contributing to the HyperSort – Hyperspectral Optical Engine project. Her scientific interests include spectroscopic instrumentation, data analysis, hyperspectral imaging, and the development and application of chemometric methods, spanning Machine Learning and Deep Learning techniques. Giulia has authored 22 scientific publications and has experience in data fusion, Process Analytical Technology (PAT), and anomaly detection, with particular attention to uncertainty and errors in both spectra and models, topics she considers essential for building reliable analytical workflows.

Anna de Juan is a professor at the Department of Analytical Chemistry at the University of Barcelona since 2003, where she leads the Chemometrics group. Her expertise is in the development of chemometric methods, in particular Multivariate Curve Resolution methodologies, for data fusion and analysis of complex analytical measurements, such as hyperspectral images and monitoring and control of bioanalytical and industrial processes. In the context of hyperspectral images, she has developed unmixing algorithms to adapt to multimodal measurements, time series and big data. She has published numerous works in scientific journals and has been provided a large number of invited lectures in chemometrics, imaging and process analysis conferences. Since 2023, she is Associate Editor-in-chief of Journal of Chemometrics. She is also member of the Editorial Advisory Board of Chemometrics and Intelligent Laboratory systems and Analytica Chimica Acta and acted as section editor in the reference work Comprehensive Chemometrics. She received the 4th Chemometrics Elsevier Award in 2004 and the TIC2023 award for Comprehensive Collaboration in Chemometrics in 2023. She has served as invited professor in research stages and graduate schools in Dalhousie Univ. (Canada), Univ. Lille (France), Univ. Copenhagen (Denmark), Università degli Study di Modena e Reggio Emilia (Italy) among others. She is currently president of the Spanish Society of Chemometrics and Qualimetrics and delegate of the Division of Analytical Chemistry (DAC) of EuChemS. She has organized and fostered conferences in the areas of Chemometrics, Process Analytics and Analytical Chemistry.

Rodrigo Rocha de Oliveira earned his PhD (Cum Laude) from the Universitat de Barcelona, specializing in chemometric strategies for data fusion, modeling, and chemical process control. His postdoctoral work at the University of Genova (Italy) advanced near-infrared chemical imaging analysis of biological processes. His research focuses on developing chemometric tools for Process Analytical Technology (PAT), with emphasis on spectroscopic sensors and chemical imaging. Currently, he is exploring Generative Artificial Intelligence (GenAI) applications in chemometrics. Dr. Oliveira was awarded the 2021 Siemens Process Analytics Prize for outstanding contributions by a young scientist.

Adrián Gómez Sánchez is a researcher working in the areas of chemometrics, hyperspectral imaging, and data fusion for analytical chemistry. He obtained a double PhD through an international cotutelle between the Universitat de Barcelona and the Université de Lille, where his doctoral research focused on the development and application of new strategies for hyperspectral image fusion. His research interests include the development of multivariate curve resolution and unmixing methodologies to address missing data, multimodal measurements, and complex analytical imaging scenarios. He previously worked as a postdoctoral researcher in the DyNaChem team at CNRS–LASIRE (Université de Lille), where he combined advanced chemometric modelling with cutting-edge fluorescence microscopy systems. In parallel, he is developing Lovelace’s Square, a non-profit digital platform that provides free access to chemometric algorithms, educational materials, and computational resources, with the aim of supporting open science, education, and collaboration within the chemometrics community.

Marianna Smidth Buschle is the Lead of the Software Department at Qtechnology A/S, where she has spent 18 years advancing the capabilities of embedded vision systems. She holds a Bachelor’s degree in Mechatronics from the University of Southern Denmark (SDU) and a Master’s degree in Electronic Engineering from the Technical University of Denmark (DTU). Throughout her tenure at Qtechnology, Marianna has specialized in the application side of industrial smart cameras, focusing on the seamless integration of computer vision and image analysis within demanding embedded environments. The software team at Qtechnology develops the Hypervision Explorer and the Hypervision SDK, tools specifically designed to support both exploratory data analysis and the transition to real-time implementation.

Anton Mølbjerg Eskildsen is a Software Engineer at Qtechnology A/S and the lead architect of the Hypervision software ecosystem. He holds a Bachelor’s degree in Software Development and a Master’s degree in Computer Science from the IT University of Copenhagen (ITU). Anton is the primary developer of the Hypervision SDK and Hypervision Explorer GUI, where he focuses on building a modular, intuitive framework for hyperspectral data management and analysis. His work is dedicated to providing researchers and engineers with a powerful interface to analyze and process spectral data, specifically designed to lower the barrier between complex algorithm development and functional application deployment.

Mathias Møller is a Software Engineer at Qtechnology A/S specializing in hyperspectral imaging and embedded systems. He holds a B.Eng. in Electronic Engineering from the Technical University of Denmark (DTU). Mathias is responsible for the integration of HSI-specific camera functionality and the HyperScan lab scanner system within both the Hypervision SDK and Hypervision Explorer GUI. His work focuses on creating an intuitive and easy-to-use interface for complex spectral sensors and scanning hardware, ensuring that the integration of high-performance equipment remains accessible to the user. He also leads the software development of a dual-head multispectral drone camera system for vegetation analysis, enabling moisture estimation through synchronized multi-band imaging.