Dr Haomiao Jin
Lecturer in Health Data Sciences
Academic and research departments
School of Health Sciences, Digital health research cluster, Long-term Conditions and Ageing Research Cluster.About
Biography
Dr Haomiao Jin has an interdisciplinary background in health systems engineering and social work. He holds a PhD in Industrial and Systems Engineering from the University of Southern California, where he gained expertise in information technology, data science, and health. Since then, he has built a career in the field of health informatics, with a particular interest in digital survey methdology and machine learning modelling of complex health survey data.
Currently, Dr Jin's research focuses on two areas. Firstly, he develops and evaluates technology solutions for health self-monitoring and longitudinal assessment with a particular emphasis on long-term conditions, healthy ageing, and mental and behavioural health. This work aims to support individuals in taking a more active role in their own health management and to facilitate early detection and intervention when health problems arise.
Secondly, Dr Jin works on machine learning and advanced statistics techniques to model health-related data, particularly longitudinal and intensive longitudinal data. By leveraging these approaches, this work can generate insights that support better prediction, stratification, and intervention in the context of clinical and public health.
Dr Jin has published over 30 academic papers on health informatics and clinical and public health journals, including the Journal of Biomedical Informatics, Journal of Medical Internet Research, Journal of Official Statistics, Diabetes Care, American Journal of Preventive Medicine, and Journals of Gerontology, Series B. He is the University of Surrey PI of three subaward grants from the US National Institutes of Health and is actively building an Informatics Lab on Longitudinal Health Assessment and Modelling Technologies at Surrey.
My qualifications
2018
Postdoctoral Training in Social Work (focus: primary data collection, ageing, mental health)
University of Southern California
2016
Ph.D. in Industrial and Systems Engineering (focus: information technology, data science, and health)
University of Southern California
2015
M.S. in Operations Research
University of Southern California
2012
M.S. in Industrial Engineering
Zhejiang University
2009
B.S. in Industrial Engineering
Zhejiang University
ResearchResearch projects
Function and Emotion in Everyday Life with Type 1 Diabetes: FEEL-T1DUniversity of Surrey PI - Subaward from US NIH/NIDDK
Project PIs: Pyatak, Spruijt-Metz, Gonzalez
Testing early markers of cognitive decline and dementia derived from survey response behaviorsUniversity of Surrey PI - Subaward from US NIH/NIA
Project PI: Schneider
Diagnostic Assessment of Dementia in the Longitudianl Aging Study in India (LASI-DAD)University of Surrey PI - Subaward from US NIH/NIA
Project PI: Lee
Research projects
Function and Emotion in Everyday Life with Type 1 Diabetes: FEEL-T1D
University of Surrey PI - Subaward from US NIH/NIDDK
Project PIs: Pyatak, Spruijt-Metz, Gonzalez
Testing early markers of cognitive decline and dementia derived from survey response behaviors
University of Surrey PI - Subaward from US NIH/NIA
Project PI: Schneider
Diagnostic Assessment of Dementia in the Longitudianl Aging Study in India (LASI-DAD)
University of Surrey PI - Subaward from US NIH/NIA
Project PI: Lee
Publications
Haomiao Jin, Surabhi S Nath, Stefan Schneider, Doerte Junghaenel, Shinyi Wu, Charles Kaplan (2021) An informatics approach to examine decision-making impairments in the daily life of individuals with depression. Journal of biomedical informatics 122, 103913
Haomiao Jin, Sandy Chien, Erik Meijer, Pranali Khobragade, Jinkook Lee (2021) Learning From Clinical Consensus Diagnosis in India to Facilitate Automatic Classification of Dementia: Machine Learning Study. JMIR Mental Health, 8(5): e27113.
Jungeun Olivia Lee, Arie Kapteyn, Adriane Clomax, Haomiao Jin (2021) Estimating influences of unemployment and underemployment on mental health during the COVID-19 pandemic: who suffers the most? Public health 201, 48-54
Tyler B Mason, Kathryn E Smith, Ross D Crosby, Scott G Engel, Carol B Peterson, Stephen A Wonderlich, Haomiao Jin (2021) Multi-state modeling of thought-shape fusion using ecological momentary assessment. Body Image 39, 139-145
Raymond Hernandez, Shawn C Roll, Haomiao Jin, Stefan Schneider, Elizabeth A Pyatak (2021) Validation of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) Adapted for the whole day repeated measures context. Ergonomics, 1-16
Elizabeth Ann Pyatak, Raymond Hernandez, Loree T Pham, Khatira Mehdiyeva, Stefan Schneider, Anne Peters, Valerie Ruelas, Jill Crandall, Pey-Jiuan Lee, Haomiao Jin, Claire J Hoogendoorn, Gladys Crespo-Ramos, Heidy Mendez-Rodriguez, Mark Harmel, Martha Walk (2021) Function and Emotion in Everyday Life With Type 1 Diabetes (FEEL-T1D): Protocol for a Fully Remote Intensive Longitudinal Study. JMIR Research Protocols 10 (10), e30901
Raymond Hernandez, Elizabeth A Pyatak, Cheryl LP Vigen, Haomiao Jin, Stefan Schneider, Donna Spruijt-Metz, Shawn C Roll (2021) Understanding Worker Well-Being Relative to High-Workload and Recovery Activities across a Whole Day: Pilot Testing an Ecological Momentary Assessment Technique. International Journal of Environmental Research and Public Health 18 (19), 10354
Inna Arnaudova, Haomiao Jin, Hortensia Amaro (2020) Pretreatment social network characteristics relate to increased risk of dropout and unfavorable outcomes among women in a residential treatment setting for substance use. Journal of substance abuse treatment 116, 108044
Haomiao Jin, Shinyi Wu (2020) Text messaging as a screening tool for depression and related conditions in underserved, predominantly minority safety net primary care patients: validity study. Journal of Medical Internet Research 22 (3), e17282
Haomiao Jin, Shinyi Wu (2019) Use of Patient-Reported Data to Match Depression Screening Intervals With Depression Risk Profiles in Primary Care Patients With Diabetes: Development and Validation of Prediction Models for Major Depression. JMIR formative research 3 (4), e13610
Haomiao Jin, Shinyi Wu (2019) Screening depression and related conditions via text messaging versus interview assessment: protocol for a randomized study. JMIR research protocols 8 (3), e12392
Shinyi Wu, Francisca Rodriguez, Haomiao Jin, William A Vega (2019) Latino and Alzheimer’s: Social determinants and personal factors contributing to disease risk. Contextualizing health and aging in the Americas, 63-84
Joel W Hay, Pey-Jiuan Lee, Haomiao Jin, Jeffrey J Guterman, Sandra Gross-Schulman, Kathleen Ell, Shinyi Wu (2018) Cost-effectiveness of a technology-facilitated depression care management adoption model in safety-net primary care patients with type 2 diabetes. Value in Health 21 (5), 561-568
Shinyi Wu, Kathleen Ell, Haomiao Jin, Irene Vidyanti, Chih-Ping Chou, Pey-Jiuan Lee, Sandra Gross-Schulman, Laura Myerchin Sklaroff, David Belson, Arthur M Nezu, Joel Hay, Chien-Ju Wang, Geoffrey Scheib, Paul Di Capua, Caitlin Hawkins, Pai Liu, Magaly Ram (2018) Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial. Journal of medical Internet research 20 (4), e7692
Magaly Ramirez, Shinyi Wu, Haomiao Jin, Kathleen Ell, Sandra Gross-Schulman, Laura Myerchin Sklaroff, Jeffrey Guterman (2016) Automated remote monitoring of depression: acceptance among low-income patients in diabetes disease management. JMIR mental health 3 (1), e4823
Shinyi Wu, William A Vega, Jason Resendez, Haomiao Jin (2016) Latinos & Alzheimer’s disease: New numbers behind the crisis
H Jin, S Wu, I Vidyanti, P Di Capua, B Wu (2015) Predicting depression among patients with diabetes using longitudinal data. Methods of Information in Medicine 54 (06), 553-559
Haomiao Jin, Shinyi Wu, Paul Di Capua (2015) Development of a clinical forecasting model to predict comorbid depression among diabetes patients and an application in depression screening policy making. Preventing chronic disease 12
Haomiao Jin, Shinyi Wu (2014) Developing depression symptoms prediction models to improve depression care outcomes: preliminary results. Proceedings of the 2nd International Conference on Big Data and Analytics in Healthcare
Brian Wu, Haomiao Jin, Irene Vidyanti, Pey-Jiuan Lee, Kathleen Ell, Shinyi Wu (2014) Collaborative Depression Care Among Latino Patients in Diabetes Disease Management, Los Angeles, 2011–2013. Preventing chronic disease 11
Raymond Hernandez, Shawn C Roll, Haomiao Jin, Stefan Schneider, Elizabeth A Pyatak (2022) Validation of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) Adapted for the whole day repeated measures context. Ergonomics 65(7): 960-975
Stefan Schneider, Haomiao Jin, Bart Orriens, Doerte U Junghaenel, Arie Kapteyn, Erik Meijer, Arthur A Stone (2022) Using Attributes of Survey Items to Predict Response Times May Benefit Survey Research. Field Methods, in press.
Adam M Leventhal, Junhan Cho, Lara A Ray, Rosalie Liccardo Pacula, Brian P Lee, Norah Terrault, Eric Pedersen, Jungeun Olivia Lee, Jordan P Davis, Haomiao Jin, Jimi Huh, John P Wilson, Reid C Whaley (2022) Alcohol use trajectories among US adults during the first 42 weeks of the COVID‐19 pandemic. Alcoholism: clinical and experimental research, 46(6): 1062-1072
Stefan Schneider, Doerte U Junghaenel, Erik Meijer, Elizabeth M Zelinski, Haomiao Jin, Pey-Jiuan Lee, Arthur A Stone (2022) Quality of survey responses at older ages predicts cognitive decline and mortality risk. Innovation in Aging, 6(3): igac027
Junghaenel DU, Schneider S, Orriens B, Jin H, Lee PJ, Kapteyn A, Meijer E, Zelinski E, Hernandez R, Stone AA (2022) Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample. Journal of Intelligence, 23;11(1):3.
Schneider S, Jin H, Orriens B, Junghaenel DU, Kapteyn A, Meijer E, Stone AA (2022) Using Attributes of Survey Items to Predict Response Times May Benefit Survey Research. Field Methods, 20:1525822X221100904.
Jin H, Kapteyn A (2022) Relationship Between Past Survey Burden and Response Probability to a New Survey in a Probability-Based Online Panel. Journal of Official Statistics, 38(4):1051-67.
Jin H, Crimmins E, Langa KM, Dey AB, Lee J (2023) Estimating the Prevalence of Dementia in India Using a Semi-Supervised Machine Learning Approach. Neuroepidemiology, online first.
Jungeun Olivia Lee, Woo Jung Lee, Alexandra F. Kritikos, Haomiao Jin, Adam M. Leventhal, Eric R. Pedersen, Junhan Cho, Jordan P. Davis, Arie Kapteyn, John P. Wilson, Rosalie L. Pacula (2023) Regular Cannabis Use During the First Year of the Pandemic: Studying Trajectories Rather Than Prevalence. American Journal of Preventive Medicine, online first.
Pyatak EA, Spruijt-Metz D, Schneider S, Hernandez R, Pham LT, Hoogendoorn CJ, Peters AL, Crandall J, Jin H, Lee PJ, Gonzalez JS (2023) Impact of overnight glucose on next-day functioning in adults with type 1 diabetes: An intensive longitudinal study. Diabetes Care, in press.
Schneider, S., Junghaenel, D.U., Meijer, E., Stone, A.A., Orriens, B., Jin, H., Zelinski, E.M., Lee, P.J., Hernandez, R., Kapteyn, A (2023) Using item response times in online questionnaires to detect mild cognitive impairment. Journals of Gerontology, Series B, in press.