Role
Senior Lecturer in Statistics, Department of Mathematics, School of Science and Technology
As a Senior Lecturer at Nottingham Trent University, consultant, and council member of the Royal Statistical Society, Dr Ulgen leads research and teaching initiatives focused on advancing public health, statistical epidemiology, and statistical genetics.
Dr. Ulgen’s expertise encompasses data science, biostatistics, and statistical genetics, including machine learning, mediation analysis, survival analysis methodologies, multivariate and random effects modelling, and genome-wide linkage and association studies which play a crucial role in the understanding of complex diseases such as COVID-19, cancer, aging, respiratory and neuro-psychiatric disorders. Dr. Ulgen leads and manages interdisciplinary collaborations between researchers, industry, and policy-makers.
As a newly elected member of the council of the Royal Statistical Society, Dr. Ulgen is focused on promoting how data science and AI can improve health outcomes, and the potential consequences of polarization. She is interested in how to overcome these biases and the importance of investing in data science and AI scientifically and economically.
Career overview
With over 15 years of experience in research, consulting, teaching, and scientific diplomacy in academia, biotechnology, and non-governmental sectors, Dr. Ulgen has led and worked on projects extensively in the areas of medical diagnostics, pharmacogenomics, public health, and epidemiology, involving the elucidation of risk factors and complex genetic mechanisms underlying multifactorial diseases at the international and national levels.
As a Fulbright and Chevening Scholar, she has successfully led and contributed to high-impact projects, including UKRI, MRC, NIH-RO1, NSF, and NIMH-funded initiatives, BARDA, Mass Life Science and Small Business Innovation Research (SBIR) grants as well as the French National Study on the Epidemiology and Genetics of Asthma and EU project network of excellence in GABRIEL and GaLEN.
Dr. Ulgen demonstrates visionary leadership through strategic approaches to bridging academic research and industry innovation. By cultivating cross-sector collaborations, she effectively transforms scientific knowledge into practical applications. One of her most recent accomplishments is the management of the machine learning and pre-clinical validation of Botanisol’s COVID-19 diagnostic screener in collaboration with the Harvard School of Medicine. Dr. Ulgen has recently secured an International Partnership Fund, where she is forming research collaborations between UGenome AI, University of Arizona, and the Centre for Computer Science and Informatics, MTIF, and Biological Sciences at NTU. As a PI and Co-PI on various projects, she has mentored students, secured international collaborations, and contributed to global efforts in public health and the environment.
Dr. Ulgen holds memberships in prestigious academic societies, including the London Mathematical Society, Society for Epidemiologic Research, and Royal Statistical Society (as a Fellow). She is also a Fellow of the UK Higher Education Academy (FHEA). Currently, Dr. Ulgen spearheads Equality, Diversity, and Inclusivity initiatives within her department, demonstrating her commitment to fostering an inclusive academic environment alongside her research and teaching pursuits. One of her favourite sayings is ‘"Why treat people and send them back to the conditions that made them sick?" - Sir Michael Marmot. Dr. Ulgen is committed to using her expertise in data science and public health to eliminate health inequalities caused by AI biases and public opinion, and to improve health outcomes for the underprivileged.
Research areas
Dr. Ayse Ulgen leads research in the fields of statistical epidemiology, data science, biostatistics, and statistical genetics. Additionally, she has research collaborations with biotech companies such as med-tech and pharmacogenomics. Dr. Ulgen is currently working on survival analyses and cause-specific competing risk analyses, machine learning applications on COVID-19, and she has extensive work in the field of statistical genetics which is an interdisciplinary field with the goal of finding human disease genes, using tools from mathematics, statistics, computer science, genetics and epidemiology (including GWAs, family-based association analyses, random effects modelling and multivariate analysis) on complex disorders such as epilepsy and neuro-psychiatric disorders, cancer, and asthma.
Dr. Ulgen’s research focuses on methodological and computational applications of data science, statistics, and epidemiology in modelling disease and public health outcomes., often bridging the gap between research and applications, aiming to create meaningful change.
Dr. Ulgen is a member of:
- Centre of Computer Science and Informatics (CIRC)
- Interactive Systems Research Group
- Bioinformatics and Complex Systems Groups
- Mathematical Sciences Research
External activity
External Research Collaborations:
- Harvard University Medical School, Boston, USA
- Columbia University, New York, USA
- Robert Boas Center for Genomics and Human Genetics, Feinstein Institute of Medical Research, New York, USA
- INSERM, Paris, France
- University of Arizona, Tucson, USA
- Arizona State University, Phoenix, USA
- University of Barcelona, Spain
- Marmara University, Istanbul, Turkey
Editorial:
- Advances in Statistical Methods and Machine Learning for Medical
and Genetic Epidemiology - PlosOne
- Cyprus J of Medical Sciences
- International Journal of Genetics and Genomics
- Frontiers in Medicine
Professional Societies:
- Council Member of the Council of the Royal Statistical Society
- Departmental Lead of the London Mathematical Society
- Departmental Lead for Equality, Diversity and Inclusivity
- Athena SWAN Departmental Bronze application Self-Assessment Team Member
- Member of the Society for Epidemiologic Research
Publications
Publications in Peer-Reviewed Journals:
- Özgür EG, Ulgen A, Uzun S, Bekiroğlu GN. (2024) Evaluation of risk factors and survival rates of patients with early-stage breast cancer with machine learning and traditional methods. Int J Med Inform. 2024 Oct;190:105548.
https://doi.org/10.1016/j.ijmedinf.2024.105548
https://www.sciencedirect.com/science/article/pii/S1386505624002119?via%3Dihub
- Sivgin H, Cetin S, Ulgen A, Li W. (2023) Diabetes and bacterial co-infection are two independent risk factors for respiratory syncytial virus disease severity. Front. Med. 10:1231641.
https://doi.org/10.3389/fmed.2023.1231641
- Li W, Cetin S, Ulgen A, Cetin M, Sivgin H, Yang Y. ‘Approximate Reciprocal Relationship Between Two Cause-Specific Hazard Ratios in COVID19 Data with Mutually Exclusive Events.’ Int J of Biostatistics.Apr, 2023.
https://doi.org/10.1515/ijb-2022-0083
- Ulgen A, Sirin Cetin, Meryem Cetin Hakan Sivgin, Wentian Li. A Composite Ranking of Risk Factors for COVID-19 Time-To-Event Data from a Turkish Cohort. Computational Biology and Chemistry. 2022, 98 (2022) 107681.
https://doi.org/10.1016/j.compbiolchem.2022.107681
- Meryem Cetin, Sirin Cetin, Ayse Ulgen, Wentian Li. Blood-Type-A Is A COVID-19 Infection and Hospitalization Risk in a Turkish Cohort . Transfusion Clinique et Biologique, ISSN 1246-7820, 2022.
https://doi.org/10.1016/j.tracli.2022.10.003
- Ersan Berksel, Ayse Ulgen. Magnitude of antibody response and risk factors for reduced immunogenicity after two doses of an inactivated whole-virion COVID-19 vaccine (CoronaVac®). Cyprus Journal of Medical Sciences.2022, 7(4): 438-443.
https://doi.org/10.4274/cjms.2022.2022-10
- Meryem Cetin, Pervin Ozlem Balci, Hakan Sivgin, Sirin Cetin, Ayse Ulgen, Hatice Dortok Demir, Wentian Li. Alpha Variant (B.1.1.7) of SARS-CoV-2 Increases Fatality-Rate for <70 years Old Patients and Hospitalization Risk Overall. Acta Microbiologica et Immunologica Hungarica. 2021,68(2021)3,153–161.
https://www.doi.org/10.1556/030.2021.01524
- Ulgen A, Çetin S, Dede I. ‘Survival Analysis in Colon Cancer Patients’. May 2021; J of Contemp Med 11(3):374-379.
https://www.doi.org/10.16899/jcm.902588
https://dergipark.org.tr/en/pub/jcm/issue/60386/902588#article_cite
- Sirin C, Ulgen A, Balci PO, Sivgin H, Cetin M, Sivgin S, Li W. Survival Analyses of COVID-19 Patients in a Turkish Cohort: Comparison between Using Time to Death and Time to Release. Apr 2021; SciMedicine:Vol 3, Special Issue COVID-19:1-9.
https://www.doi.org/10.28991/SciMedJ-2021-03-SI-1
https://scimedjournal.org/index.php/SMJ/article/view/294
- Sirin C, Ulgen A, Dede I, Li W. ‘On Fair Comparison between Random Survival Forest and Cox Regression: An Example of Colorectal Cancer Study’. Mar 2021; SciMedicine: Vol 3(1):66-76.
https://doi.org/10.28991/SciMedJ-2021-0301-9
https://scimedjournal.org/index.php/SMJ/article/view/343
- Cetin S, Pasin O, Dede I, Ulgen A. An application of a cox mixed cure model for breast cancer patients. 2021;Turkiye Klinikleri J of Biostat, 13(2):131-7
https://doi.org/10.5336/biostatic.2020-79287
- Cetin S, Kose K, Karaaslan E, Ulgen A. Nonparametric Randomization-Based Analysis of Covariance Method in Repeated Clinical Categorical Data. 2021,Turkiye Klinikleri J Biostat: 13(1):50-6.
https://doi.org/10.5336/biostatic.2020-79326
- Ulgen A, Cetin S, Balci PO, Sivgin H, Sivgin S, Cetin M, W. Li. ‘COVID-19 Outpatients and Surviving Inpatients Exhibit Comparable Blood Test Results That Are Distinct from Non-Surviving Inpatients’. May 2021; J of Health Sci Med: 4(3):306-313.
https://www.doi.org/10.32322/jhsm.900462
https://dergipark.org.tr/en/pub/jhsm/issue/62390/900462
- Bekiroglu N, Ulgen A. Application of Parametric Accelerated Failure Time (AFT) Model in Early Stage Breast Cancer Patients.
July 2021; Pamukkale Medical J 14(3): 654-665.
https://doi.org/10.31362/patd.893954
https://dergipark.org.tr/tr/pub/patd/issue/61233/893954
- Ulgen A, Gurkut O, Li W. Potential Predictive Factors for Breast Cancer Subtypes from a North Cyprus Cohort Analysis. Dec, 2020 Cyprus Journal of Medical Sciences. 5(4): 339-49.
https://doi.org/10:5152/cjms.2020.2291
- Sirin C, Ulgen A, Sivgin H, Li W. ‘A Study On Factors Impacting Length of Hospital Stay of COVID-19 Inpatients’. May 2021; J of Contemporary Medicine 11(3): 396-404.
https://www.doi.org/10.16899/jcm.911185
https://dergipark.org.tr/en/download/article-file/1690508
- Acar H, Ulgen A. ‘Comparison of Cost, Risks and Benefits of Robotic or Open Thyroidectomy on Thyroid Cancer’. Cyprus Journal of Medical Sciences. Cyprus J Med Sci , 2021;6(1):1-6
https://www.doi.org/10.4274/cjms.2020.1749
- Acar H, Ulgen A. Relationship between Thyroid Hormone Levels and Crime Type: A Controlled Study in Prisoners. International Journal of Endocrinology. vol. March 2020, Article ID 9172134, pp1-7.
https://doi.org/10.1155/2020/9172134
https://pubmed.ncbi.nlm.nih.gov/32215012/
- Charity J. Morgan, Michael J. Coleman, Ayse Ulgen, Lenore Boling, Jonathan O. Cole, Frederick V. Johnson, Jan Lerbinger, J. Alexander Bodkin, Philip S. Holzman, Deborah L. Levy.Thought Disorder in Schizophrenia and Bipolar Disorder Probands and Their Relatives. J. Schizophrenia Bulletin, March 12017. https://doi.org/10.1093/schbul/sbx016
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5463905/
- Annapurna Poduri, Yuanjia Wang, Derek Gordon, Sandra Barral-Rodriguez, Christie Barker-Cummings, Ayse Ulgen, Vida Chitsazzadeh, Robert Sean Hill, Neil Risch, W. Allen Hauser, Timothy A. Pedley, Christopher A. Walsh, Ruth Ottman. Novel Susceptibility Locus in a Family with GEFS+ Syndrome. Oct 2009, Neurology J, 20;73(16):1264-72
https://doi.org/10.1212/WNL.0b013e3181bd10d3
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2764413/
- Aschard H, Bouzigon E, Ulgen A, Corda E, Dizier MH, Gormand, F, Lathrop M, Kauffman F, Demenais F. Sex-specific effect of IL9 polymorphisms on lung function and polysensitization. Sep 2009, Genes and Immunity Journal;10(6):559-65
https://doi.org/10.1038/gene.2009.46
- Bouzigon E, Ulgen A, Dizier MH, Siroux V, Lathrop M, Kauffman F, Pin I, Demenais F. Evidence for a pleiotropic QTL on chromosome 5q13 influencing both time to asthma onset and asthma score in French EGEA families. 2007, Hum Genet, Vol 121, 6: 711-719
https://doi.org/10.1007/s00439-007-0363-x
https://link.springer.com/article/10.1007/s00439-007-0363-x
- Ulgen A, Li W. Comparing Single-Nucleotide Polymorphism Marker-Based and Microsatellite Marker-Based Linkage Analyses. Dec 2005, BMC Genetics, 6(Suppl I):S13;p1-5.
https://doi.org/10.1186/1471-2156-6-S1-S13
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866807/pdf/1471-2156-6-S1-S13.pdf
- Ulgen A, Yoo YJ, Gordon D, Finch SJ, Mendell NR. Percentiles of the Null Distribution of 2 Maximum Lod Score Tests. 2004, Human Heredity, 57(1):39-48.
https://doi.org/10.1159/000077388
https://www.ncbi.nlm.nih.gov/pubmed/15133311?dopt=Abstract
- Ulgen A, Han Z, Li W. Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.2003, BMC Genetics, 4(Suppl 1): S60-66.
DOI: 10.1186/1471-2156-4-S1-S60
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866498/pdf/1471-2156-4-S1-S60.pdf
Other Publications and Preprints :
- Sirin C, Ulgen A, Sivgin H, Li W. Approximate Reciprocal Relationship Between Two Cause-Specific Hazard Ratios in COVID-19 Data with Mutually Exclusive Events. Apr 2021, MedRxiv:1-20. https://doi.org/10.1101/2021.04.22.21255955
- Ulgen A, Amos C. Quantitative Trait Loci on Chromosome 21 have Pleiotropic Effects on %FEV1 and Allergen Polysensitization: asthma related traits in the EGEA study. April 2020. Medrxiv: 1-36. https://doi.org/10.1101/2020.04.17.20069369
- Ulgen A, Gurkut O, Li W. An Epidemiological Survey of Breast Cancer and Its Subtypes in North Cyprus. Oct, 2019. Medrxiv preprint. https://www.medrxiv.org/content/10.1101/19010181v1
Papers Submitted/In Preparation:
- Ulgen A, Cetin S, Li W. “A Mediation Analysis of Calculated Osmolality – A Strong Predictor for COVID-19 Mortality and Hospitalization – Reveals Its Possible Links with Other Biomarker”, Frontiers in Medicine. Submitted.
- C. Conkbayir C., Ulgen A. Cardiac side effects and psychiatric drugs. Submitted. European Review for Pharmacological and Medical Sciences. Submitted.
Course(s) I teach on
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Postgraduate taught | Full-time / Part-time / SandwichCOURSE
Data Science - MSc
https://www.ntu.ac.uk/course/science-and-technology/pg/msc-data-science
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Undergraduate | Full-time / SandwichCOURSE
Mathematics - BSc (Hons)
https://www.ntu.ac.uk/course/science-and-technology/ug/bsc-hons-mathematics
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Postgraduate taught | Full-time / Part-timeCOURSE
Molecular Biology - MRes
https://www.ntu.ac.uk/course/science-and-technology/pg/mres-molecular-biology