Dr. Geetha Chilla is a scientist at the A*STAR’s Bioinformatics Institute (BII), Singapore. She investigates neurodevelopment, neuropsychiatry, and other neurodegenerative diseases using medical imaging and artificial intelligence. She graduated from Nanyang Technological University, Singapore, with a Ph.D. in biomedical engineering.

Neuro-radiomics, medical imaging and image processing, and artificial intelligence.

Explore regional alterations in subjects stratified with risk of dementia based on image-based markers obtained from mild and moderate Alzheimer’s disease and evaluate them with respect to changes in cognitive measures. Also, explore the possibility of predicting AD and dementia based on brain morphometry measures prior to the onset of symptoms.

Dr. Ricardo D’Oliveira Albanus is a biologist and postdoctoral associate at the Washington University School of Medicine in St. Louis, USA. His research focuses on the interplay between aging and neurodegeneration from a genomics viewpoint. He is especially interested in mapping the interface between genetics and gene regulation. He graduated from the University of Michigan, USA, with a Ph.D. in bioinformatics.

Functional genomics of AD and aging.

Understand how aging predisposes to AD and identify the differences between healthy aging and AD. This will be done with deep molecular characterization of human brain tissues across a broad spectrum of ages and neuropathological states, including cognitively healthy centenarians.

Dr. Sam Danso is a senior lecturer in computer science at the University of Sunderland, UK. He is also a principal for the Ghana Prevent Programme, a project to develop a cohort of underrepresented populations for neurodegenerative disorders. He graduated from the University of Leeds, UK, with a Ph.D. in artificial intelligence.

Applied artificial intelligence and data science with a focus on explainable artificial intelligence (XAI) for brain health.

Develop a deep phenotype of data that combines data from heterogeneous sources and different populations to obtain a life-course cohort of representative sample using already existing data. Also, explore and develop early detection XAI models using the harmonized life-course cohort.

Dr. Jiyang Jiang is a research fellow at the Centre for Healthy Brain Ageing, University of New South Wales, Australia. His primary research interest is applying advanced computational skills to resolve complex questions in medicine. He graduated from the University of New South Wales, Australia with a Ph.D. in psychiatry.

Machine learning, medical imaging, brain and cognitive aging, and dementia.

Develop robust prediction models for dementia in low- and middle-income countries (LMICs), using data that are easily accessible to LMICs such as demographics, risk factors, cognition, and physical function.

Dr. Hangfan Liu is an assistant professor at the Center for Advanced Imaging Research (CAIR), University of Maryland, USA. He is especially interested in exploring the disease heterogeneity within ADRD and improving disease subtyping. He graduated from Peking University, China, with a Ph.D. in computer science.

Image processing, machine learning, and neuroimaging analysis.

Use innovative applications of machine learning, image processing, and neuroimaging analysis for the advancement of personalized treatment strategies. Efforts will include three key phases to disentangle the heterogeneity of ADRD – signal-adaptive image enhancement, joint feature representation learning, and robust collaborative clustering.

Dr. Jermaine Ross is the CEO and co-founder of Alleo Labs and a board member for the Alzheimer’s Association in New York City. He is interested in examining AD as a syndrome rather than a single disease, analyzing disease progression by AD subgroups. He graduated from Brown University, USA, with a Ph.D. in neuroscience.

Alzheimer’s disease, Lewy body dementia, and Parkinson’s disease.

Advance biomarker research for early detection and diagnosis by examining the relationship between levels of markers such as insulin-like growth factor-1 and AD progression.

Dr. Natalia Vilor-Tejedor leads the genetic neuroepidemiology and biostatistics team at Barcelona Beta Brain Research Center, Spain. Her research focuses on genetic (non-modifiable) and environmental (modifiable) factors in the development of neurological disorders and related traits. She graduated from Pompeu Fabra University, Spain, with a Ph.D. in biomedicine.

Genetic neuroepidemiology and biostatistical modelling.

Develop a modeling framework that can generate functional predictive omics scores to identify endophenotypes of neurodegeneration at early, preclinical, and advanced stages. The goal is to enable the identification of specific molecular mechanisms of neurodegenerative disease prior to symptom development.