Data mining for space borne astrophysical and cosmological observations
University of Ferrara, PhD in Physics
Megha Das is a Marie Skłodowska-Curie PhD Researcher within FutureData4EU, supervised by Dr Mattia Bulla. Her research focuses on multimessenger transient astrophysics, mainly double white dwarf merger remnants & kilonova modelling, with expertise in data reduction & statistical modelling. She earned an MSc in Astrophysics from the University of Sheffield, working on eclipse lightcurves of cataclysmic variables. She works in the data science & astrophysics overlap, and enjoys music & travelling.
Big Data Analysis for Industrial Diagnostic
University of Modena and Reggio Emilia, PhD in Industrial Innovation Engineering
I hold a Master’s degree in Artificial Intelligence and Data Processing from Badji Mokhtar University, Algeria. I have experience in machine learning, data analysis, and optimization. I am currently enrolled in the FutureData4EU Ph.D. programme at UNIMORE, where my research focuses on big data analysis for industrial diagnostics.
Artificial Intelligence to support manufacturing through production efficiency, quality and strategies of maintenance.
Politecnico di Milano, PhD in Mechanical Engineering
I graduated in Mechanical Production Engineering from the University of São Paulo (USP). Later, I earned a postgraduate diploma in Business Management from Fundação Getulio Vargas (FGV) and a Master’s degree in Production Engineering from the Federal University of Santa Catarina (UFSC). I’m now pursuing my PhD in Mechanical Engineering at Politecnico di Milano. With over 20 years of industry experience, I’m passionate about connecting academic knowledge with real-world challenges.
Spin Systems for Quantum Technologies: advanced computing techniques, new concepts and realistic material simulations
University of Parma, PhD in Physics
I am a doctoral fellow in the FutureData4EU programme, holding a Master’s in Physics and a Gold Medal for academic excellence in my Bachelor’s. My experience includes quantum optimization in complex network problems, and my PhD research focuses on spin systems for quantum technologies, combining advanced computing techniques with realistic material simulations.
Deep learning for renal pathology prognosis prediction
University of Modena and Reggio Emilia, PhD in Information and Communication Technologies
I am a Software Engineering researcher with over 5 years of experience in computer vision, machine learning, and deep learning. I have led end-to-end projects addressing real-world challenges in healthcare, tourism, NLP, and software engineering. Currently, I work on renal pathology prognosis prediction using deep learning. My passion lies in advancing AI, especially in computer vision, image processing, symbolic AI, and large language models through impactful research and collaboration.