Thematic Area 1 – Health

Awad Bin Naeem

Awad Bin Naeem

AI-based neurobiological phenotyping of patients with expansion repeats and brain disorders

University of Bologna, PhD in Biomedical and Neuromotor Sciences

 

I am a PhD candidate and research fellow at the University of Bologna's Department of Biomedical and Neuromotor Sciences, specializing in AI-driven diagnostics. I hold an MSc in Computer Science from NCBA&E (2022), focusing on smart transportation and medical disease diagnosis using ML/DL. With 28 publications and 8 international presentations, my interests include heart, brain, cancer detection, and V2X communication.

Cristalina Perpetua Mahumane Uamusse Pranzini

Cristalina Perpetua Mahumane Uamusse Pranzini

Implementation of artificial intelligence in the assessment of higher risk pregnancy conditions using ultrasound

University of Parma, PhD in Translational Medical and Surgical Sciences 

 

I am PhD student in Implementation of artificial intelligence algorithms in the sonographic assessment of fetal anatomy in University of Parma. I am a doctor from Mozambique, Master degree in International Health and Medicine for Cooperation with Developing Countries in Italy ( UNIPR). My research focuses on using artificial intelligence ultrasound to improve  the detection rate of higher risk pregnancy conditions, contributing to faster and more reliable diagnoses during pregnancy.

 

Eloïse Breton

Eloïse Breton

Evolutionary Perspective on health and medicine through the lense of paleogenomics

University of Ferrara, PhD in Life Sciences and Biotechnology

 

I’m Eloïse, from France. I’m pursuing my PhD at the University of Ferrara in pharmacogenomics and paleogenomics, with a focus on the evolutionary dynamics of pharmacogenes. I graduated in Biodiversity, Ecology and Evolution with a specialization in Genomics from Université Claude Bernard Lyon 1 (France). My academic background focuses on population genomics, ancient DNA, and evolutionary biology. I completed my Master’s thesis on the bioinformatic analysis of ancient human DNA from individuals of the Catacomb culture in Ukraine. I have gained international research experience through internships and training in paleogenetics. My research interests lie in studying ancient DNA and past human populations to address contemporary challenges, particularly in medicine, through interdisciplinary approaches

Izhar Muhammad

Izhar Muhammad

Big data and statistical theory for enhanced inferences in domain sciences

University of Bologna, PhD in Statistical Sciences

 

I am Izhar Muhammad. I belong to Batkhela, KPK, Pakistan. I have done B.S in Statistics from University of Malakand in the session "2015-2019". After that, i did M.Phil. in Statistics from Quaid-i-Azam University, Islamabad, in the session "2020-2022". After M.Phil., i joined Shaheed Benazir Bhutto University Sheringal and University of Wah as a lecturer from December 2022 to September 2023 and October 2023 to April 2024, respectively. Now, i am a PhD student under the project “Futuredata4eu”.

Karen Cardenas Casillas

Karen Cardenas Casillas

Illuminating dark gene targets in the human genome through big data analysis

University of Parma, PhD in Biotechnology and Biosciences

 

I’m Karen Cárdenas Casillas from Mexico, pursuing a PhD at the University of Parma, focused on high-throughput screening and protein modeling of complexes to reveal their structure and function. I hold a BSc in Biotechnology Engineering from Tec de Monterrey and a MSc in Molecular Medicine from the University of Sheffield, and have also specialized in Data Science. My research aims to uncover molecular mechanisms of protein interaction through structure prediction and large-scale data analysis.

Kun Karnchanapandh

Kun Karnchanapandh

High-performance computing and data analysis in drug design and discovery

University of Parma, PhD in Drug Sciences

 

I am a 27-year-old graduate student from Thailand and have recently completed a master’s degree in Bioinformatics and Computational Biology. I also hold a bachelor's degree in Biochemistry and have been conducting research in the field of computational drug simulation. I have published several research papers, with a recent focus on the elucidation and design of novel drug candidates. I plan to further advance this line of research in my Ph.D. studies. 

Mahmoud Shalash

Mahmoud Shalash

Data driven determination of statistical properties of proteins

University of Bologna, PhD in Physics

 

I am a PhD student in Computational Biophysics at the University of Bologna. I hold a BSc in Pharmaceutical Sciences from MSA University, Egypt, and an MSc in Medicinal and Biological Chemistry from the University of Edinburgh. My research focuses on using HDX-MS and AI-driven simulations to explore protein dynamics, especially in intrinsically disordered proteins. I integrate machine learning with molecular modelling to advance structural biology.

Sami Al-Nawaiseh

Sami Al-Nawaiseh

Artificial Intelligence-Based Perioperative Guidance Tool for Vitreoretinal Surgery

University of Ferrara, Phd in Advanced Therapies and Experimental Pharmacology

 

I am a German board-certified ophthalmologist with a PhD from Bonn University. I completed my residency in Münster and Sulzbach and have worked as a specialist in Germany. My clinical and research focus includes medical and surgical retina, OCT, AI applications in ophthalmology, and stem cell-based therapies. I am fluent in German, Arabic, and English.

Zaineb Al-Awan

Zaineb Al-Awan

Enhancing Dermatologic Interventions through Big Data-Driven Understanding of Placebo Effects

University of Bologna,  PhD in Surgical Sciences and Innovative Technologies

I am a German-Arab PhD fellow, holding a BSc in Psychology from Tilburg University, and a MSc specializing in Health and Medical Psychology from Leiden University. Driven by a deep interest in mind-body interactions, I have focused my work on psychosomatization and placebo mechanisms, while promoting a holistic and biopsychosocial perspective on health. My current project focuses on placebo and nocebo effects in psoriasis, using big data methodologies and machine learning approaches.