Vaclav Papez
Computer Scientist and Software Engineer
Vaclav is a Research Associate at the UCL Institute of Health Informatics. He is a computer scientist and a software engineer (PhD thesis on Archetype-based approach for modelling of electroencephalographic/event-related potentials data and metadata). His primary interest is in database technologies (relational and non-relational database), data models and semantic web.
sheng-chia chung
Epidemiologist and Medical Statistician
Sheng-Chia is an epidemiologist and medical statistician working on the clinical presentation, prevention and management of diseases. Her research focuses on nationwide linked electronic health records, and research themes include epidemiology, care and outcome research, disease trajectory and international comparative studies. Sheng-Chia has worked on chronic (dementia, hypertension, cardiovascular diseases, cancer) and acute (tuberculosis) conditions.
Michael CHANG
Research Data Scientist
Having a dual background in Communications and Psychology, Michael utilises flip-thinking between arts and science. He is interested in biological and cognitive psychology and decided to transition to health research to discover better ways of preventing and treating illnesses. His research investigates disease trajectories and prognostic outcomes in psychiatric disorders and cancers, as well as the impact of medications on health progression particularly chronic liver diseases, using data science approaches. Beyond research, he enjoys exercising and watching documentaries.
Yen Yi Tan
Graduate Student, PhD in Health Informatics & MRes in AI-Enabled Healthcare
Yen Yi received the prestigious UCL Overseas Research Scholarship for his PhD studies. His research interest involves the application of artificial intelligence with the integration of diverse types and levels of data including multi-omics biological data, clinical patient data and electronic health records to improve patient outcomes. When he is not working, you can find Yen Yi on his PlayStation 4 in a game of Modern Warfare or jamming on the guitar.
Jurgita KaubryTE
Graduate Student, PhD in Health Informatics
& Senior Data Scientist – Cerner
Jurgita is a healthcare data scientist, working at Cerner, and a PhD candidate at the UCL Institute of Health Informatics. She holds a MSc degree in Financial Economics and has more than seven years of UK and international experience in healthcare analytics and research, including work with NHS organisations. She is passionate about using AI and data science to achieve improvements in the healthcare sector. She is primarily interested in using machine learning algorithms against linked longitudinal electronic health records in the areas of population health, cancer and genomics.
CHRIS TOMLINSON
Graduate Student, PhD and MRes in AI-Enabled Healthcare
& Anaesthetics/Intensive Care Registrar
Chris is a registrar in Anaesthetics & Intensive Care undertaking a combined MRes/PhD at the UKRI UCL Centre for Doctoral Training in AI-enabled Healthcare Systems. He is interested in leveraging the rich data routinely collected in Critical Care, alongside wider healthcare datasets, using machine learning methods to facilitate a more individualised approach to treatment decisions and targets. He hopes to implement these tools as a ‘Clinical Informatics Consult’ empowering clinicians and patients to make better informed decisions, utilising all available evidence.
ASMA ALFAYEZ
Graduate Student, PhD in Cancer Informatics
One Data Science Fellow
Asma’s PhD research is on cancer early diagnosis using machine learning and artificial intelligence. Her enthusiasm for combining health science and computer science developed while studying for an MSc in Health Informatics following her BSc in Information Technology and Computer Science degree. She is interested in applying new algorithms on healthcare problems as big data analytics and artificial intelligence solutions will lead to significant clinical improvements.
NANAKI MAITRA
Graduate Student, PhD in Health Informatics
One Data Science Fellow
Nanaki’s research involves exploring mental health risk factors for cancer onset and progression using electronic health records. Building on her previous academic experience in bioinformatics and genomics, she is especially interested in using a multidisciplinary approach to understand the association between mental illness and cancer prognosis.
In her spare time, she enjoys cooking, debating, and watching sci-fi movies.
FREYA ALLERY
Graduate Student, PhD and MRes in AI-Enabled Healthcare
Freya is a student on the AI-enabled Healthcare Systems PhD programme at the Institute of Health Informatics at UCL, focusing on inequalities in public health. She previously completed an MEng in Engineering Science at Oxford, where she specialised in information and biomedical engineering and developed a keen interest in novel applications of machine learning in healthcare. In her current work, she is looking to employ machine learning techniques to explore factors driving disparities in patient outcomes for different demographic groups, using COVID-19 trajectory data on a population scale as an exemplar.
Tuankasfee Hama
Graduate Student, PhD and MRes in AI-Enabled Healthcare
Tuankasfee graduated with a master's degree in Computer Science and a medical degree from Prince of Songkla University, Thailand. He is experienced in rehabilitation medicine and is interested in the bioinformatics analysis of genetic data. His research interest is primarily focused on long COVID and rare disease using genomic data and electronic health records.
EVALEEN MALGAPO
Graduate Student, MSc in Health Data Science,
Systematic Review Fellow & General Practitioner
Evaleen graduated from UCL Medical School, where she also completed an intercalated Bachelor’s degree at the Institute of Child Health with a research project on drug repurposing for acute myeloid leukaemia using molecular cloning. As a qualified GP, she has developed an interest in the use of epidemiology and statistics to improve the delivery of healthcare and reduce health inequalities. Evaleen believes that by gaining data-driven insights into population characteristics and demographics, we can create tailored health and social care provision.
CHEN LU
Systematic Review Fellow
Chen is a PhD student in auditory neuroscience and studying with Prof. Jennifer Linden at UCL Ear Institute. She majored in biology in her undergraduate studies and neuroscience for postgraduate research. She is interested in how the sensory system function in normal situations and diseases. Her research focuses on abnormalities in the auditory cortex contributed by genetic risk factors and environmental risk factors.
Jennifer JW ChoI
Graduate Student, PhD in Health Informatics
Jennifer is a PhD student working with clinical trials data to determine the association between study variables and the overall trial success/failure. During her MSc in Drug Development and Pharma Management, she became particularly interested in drug R&D and identifying the key challenges in clinical research. Her research is currently focused on trial recruitment, and she aims to build a model that can predict trial success/failure from study design and trial variables.
Zeinab Abubakar
In2Research Data Science Intern
Zeinab is a biochemistry undergraduate at King’s College London. She is a biology enthusiast - particularly about the diversity of biochemical pathways in the human body and the processes underlying the precision of gene expression and manipulation. A quest to find a career to combine her primary interests in genetics and statistics led her to data science. She envisions a career as a data scientist driving data-backed patient decisions in healthcare and pharmacogenetics.
Ria Hoondle
In2Research Data Science Intern
Ria is a Chemistry undergraduate student at Imperial College London. Her research has recently focused on using Python to plot ternary phase diagrams to demonstrate miscibility of liquids, followed by using the Fiji software to extract interfacial tension data of droplets with differing surfactant concentrations. She is particularly passionate about physical chemistry topics and using programming software to analyse large data sets. Asides from lab work, she is a member of Imperials Swim and Waterpolo team where she trains twice a week!
Kai Xiang Lim
One Data Science Fellow
Kai is a PhD student in statistical genetics based at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. He has a background in psychology and holds an MSc in Genes, Environment and Development in Psychology and Psychiatry. Based in an interdisciplinary research setting, he analyses huge genetic and epidemiological datasets using genomic data science/causal inference methods, focusing on self-harm and its risk factors. His passion lies in statistical genetics, mental health and data science. During his free time, he enjoys writing Chinese calligraphy and volunteering on data-for-good projects.
Millie Wagstaff
One Data Science Fellow
Millie is a first-year PhD student at the UCL Great Ormond Street Institute of Child Health. For her PhD she is investigating the impact of treating mental health disorders in children with epilepsy on educational attainment, parental mental health and longer-term physical health outcomes. Millie has a background in Data Science and Neuroscience and is passionate about using Data Science to improve the understanding and treatment of mental health disorders.
Katarzyna Dziopa
One Data Science Fellow
Kasia is a PhD candidate at the UCL Institute of Health Informatics. In her thesis, she explores the topic of predicting cardiovascular disease in type 2 diabetes utilizing contemporary electronic health records and genomic data. She holds an MSc degree in Computer Science and BSc degree in Computer Science and Mathematics. She has gained professional experience working as a software engineer. Additionally, she is involved in conducting workshops and courses on topics ranging from basic Python programming to introductory Machine Learning classes. She is passionate about using data science and machine learning techniques in areas of healthcare and genomics.
your name here!
Love science and data?
Then we want you. ;-)
The Lai Lab is open to graduate students, postdoctorate colleagues and visiting scientists. Find out how you can join.
LAB Alumni
STEFANIE MUELLER
Postdoctoral Fellow in Genetics and Health Informatics
Now at Boehringer Ingelheim
Stefanie’s background is in biochemistry and neurogenetics. During her PhD, she investigated the genetic architecture of different neurological diseases like Essential Tremor, Parkinson’s Disease or autoimmune mediated encephalitis. Her research focus is the application of data science and bioinformatical methods to elucidate the hidden patterns and effects in human genetic and health data sets including electronic health records. These efforts can lead to new pathological insights or new therapeutic considerations.
Suruchi Sharma
Graduate Student, MSc Health Informatics
Now at Eli Lilly
Suruchi is a postgraduate student in Health Informatics. Suruchi obtained my MSc degree in Biotechnology and BSc in Zoology from India. She previously trained at RGCI&RC in Delhi in different molecular diagnostic assays to perform extensive molecule related diagnostic tests especially in inherited cancer syndrome. She worked as a Junior Scientist where her role was to perform technical process of next generation sequence assay for clinical diagnostic purposes. Her area of interest is to investigate the relationship between health informatics applications and human genetics.
Mathilde Boecker
Undergraduate Student
Now at the UK Ministry of Defence
Mathilde is a third-year undergraduate studying Human Sciences, which is a liberal-arts style interdisciplinary degree based in the biosciences. Within her degree she focused on predominantly on cell biology and genetics, however she also has a keen interest in public health, which she aims to pursue at a Master's level next year. She is currently writing a dissertation to determine how genetic testing for Type 2 Diabetes can be used to motivate risk-awareness and risk-reducing behaviours and she is interested in exploring the public health implications of genomics and personalised medicine further in my Master's thesis.
Yuguo Wei
Graduate Student, MSc Health Data Science
Yuguo is a postgraduate student in Health Data Science at the UCL Institute of Health Informatics. Her research focuses on statistical genetics, Bayesian methods and machine learning algorithms including classification methods and clustering analysis. Her undergraduate major was statistics at the University of Glasgow. Her undergraduate research involves building statistical models of the genetic variation in mitochondrial DNA of grouped people. Her internship in Illumina was valuable in helping her understand more about genetic determinants of complex diseases. She is keen to use statistical methods to solve real-world issues.
ELOISE WITHNELL
Graduate Student, rotation
Eloise is a HDR/Turing PhD student in Health Data Science, carrying out a rotation project at the Institute of Health Informatics at UCL, focusing on clustering for cancer classification using genomic data and secondary care health records. She is particularly interested in the bioinformatic analysis of genetic data and have previous completed a MSc in Computer Science where she focused on explainable AI methods applied to genetic cancer classification models.
Shailly Luthra
Systematic Review Fellow
Shailly is a specialist Periodontist and is currently pursuing my PhD at Eastman Dental Institute. For her master’s project, she explored the acute inflammatory response following dental treatment. She is particularly interested in the link between oral and systemic inflammation, which could result in an episode of acute vascular events. She is presently the departmental and lead student representative (Research) for UCL-Eastman Dental Institute, and a member of the Dental Council of India, Indian Dental Association, Indian Society of Periodontology, Indian Society of Oral Implantology, and Indian Red Cross Society.
Aasiyah Rashan
Graduate Student, MRes in AI-Enabled Healthcare
Aasiyah is a health informatician at the UCL Institute of Health Informatics. With her background as a data analyst and clinical terminologist, her interests include improving the interoperability of health care data, and applying causal inference and machine learning methods to observational data relating to critical care. She is currently pursuing her PhD in AI-enabled healthcare.