Data Champions Search

My current work combines neurobehavioral observation, fMRI and EEG in patients with Disorders of Consciousness. In particular, my research investigates which factors might predict patient performance, which technique (or combination of techniques), might be most sensitive in detecting residual conscious awareness, and which pattern of performance best classifies conscious state. 
I am also interested in the role of attentional mechanisms in conscious perception; specifically, I have been studying which temporal and spatial factors influence divided attention when stimuli in different sensory modalities compete for conscious access, leading to integration or interference. 
I strongly believe in the importance of open access and data sharing. I joined the Data Champions initiative at the University of Cambridge, aiming to increase awareness of the importance and benefits of sharing data, and to providing support within my department on how to share data through the university repository.

Additional areas of expertise:

Attentional cognitive processes, disorder of consciousness.

My research lies at the intersection of psychology, education, and computer science. I am interested in the philosophical underpinnings of different statistical paradigms and reproducible science. I was previously trained in Bayesian cognitive modeling at the JAGS and WinBUGS workshop (by Prof. Michael Lee and Prof. Eric-Jan Wagenmakers) and Bayesian item response modeling at the University of Twente (by Prof. Jean-Paul Fox). 

Swati is a Research Assistant in the Department of Engineering at the University of Cambridge. Currently, her research focuses primarily on understanding the temporal structure of pain through behavioral assessment of chronic pain patients. In addition to her research, she actively participates in mentorship initiatives such as Google’s WomenTechmaker Program. Prior to joining Nox lab, she worked with collaborators from Mayo Clinic, Oxford University, and Accenture Research Lab. 

Yasmin Fathy is a Research Associate at the Department of Engineering, University of Cambridge and a Fellow of the Higher Education Academy. Before joining Cambridge, she was a Software Developer at Genomics Analytics Group at European Bioinformatics Institute (EMBL-EBI), Research Associate in IoT and Machine Learning at Cambridge University, and a KTP Research Associate in Data Science and Machine Learning at UCL. She obtained her PhD from the Institute for Communication Systems (ICS) at the University of Surrey and an MSc in Applied Science and Engineering from the Artificial Intelligence (AI) Lab at Vrije Universiteit Brussel (VUB) in Belgium. Her research interests include IoT, data analytics, digital twin and applied machine learning.
   
 She is an active reviewer and a technical program committee member for multidisciplinary and international journals and conferences, including CCNC, The Web Conference (WWW), IEEE Systems, IEEE IoT Journal, IEEE Transactions on Big Data, and IEEE Access. She is a Topic Editorial in Frontiers in Big Data: Women in Machine Learning and Artificial Intelligence Initiative, a Data Champion at the University of Cambridge and a member of the Cambridge Centre for Data-Driven Discovery (C2D3). She was a BSF (Become a Science Founder) Fellow for entrepreneurship scientists in 2021 and was awarded MEDASTAR Erasmus Mundus and University of Surrey scholarships.
   
Yasmin is also a volunteer mentor for supporting students with soft & English skills development at Manara and a volunteer instructor at Code First Girls (CFGs).

http://yasminfathy.github.io/