Matthew M. Engelhard

Bio

Developing new machine learning methods for multi-modal longitudinal clinical data to support clinical decision-making.

Education

• M.D. University of Virginia, 2014
• Ph.D. University of Virginia, 2016

Positions

• Assistant Professor of Biostatistics & Bioinformatics
• Assistant Professor in the Department of Electrical and Computer Engineering

Courses Taught

• MMCI 517: Applied Data Science
• CRP 278: Machine Learning For Health

Publications

• Wu P, Davis NO, Engelhard MM, Dawson G, Goldstein BA. Using mixture cure models to address algorithmic bias in diagnostic timing: autism as a test case. JAMIA Open. 2025 Dec;8(6):ooaf148.
• Foote HP, Ou YJ, Bhatt S, Engelhard MM, Bederman L, Laughon MM, et al. Machine Learning Risk Prediction for Treated Retinopathy of Prematurity in Infants. Neonatology. 2025 Nov 18;1u20139.
• Wang M, Engelhard MM, Pun PH, Goldstein BA. Discrete Time Neural Network Models to address time-varying predictor importance: An illustration in predicting mortality over different time horizons. IEEE J Biomed Health Inform. 2025 Aug 18;PP.
• Meng M-L, Li Y, Fuller M, Lanners Q, Habib AS, Federspiel JJ, et al. Development and Validation of a Predictive Model for Maternal Cardiovascular Morbidity Events in Patients With Hypertensive Disorders of Pregnancy. Anesth Analg. 2025 Aug 1;141(2):352u201362.
• Sun M, Engelhard MM, Goldstein BA. Borrowing From the Future: Enhancing Early Risk Assessment through Contrastive Learning. In: Proc Mach Learn Res. 2025.
• Zhao Y, Engelhard MM. Balancing Interpretability and Flexibility in Modeling Diagnostic Trajectories with an Embedded Neural Hawkes Process Model. In: Proc Mach Learn Res. 2025.
• Doerstling SS, Engelhard MM, Akrobetu D, Sloan CE, Campagna A, Nguyen T-V, et al. Impact of Medical Conditions and Area Deprivation on Fundraising Success in Online Crowdfunding: Cross-Sectional Study. J Med Internet Res. 2025 Jul 29;27:e72475.
• Li F, Hill ED, Jiang S, Gao J, Engelhard MM. IRIS: Interpretable Retrieval-Augmented Classification for Long Interspersed Document Sequences. Proc Conf Assoc Comput Linguist Meet. 2025 Jul;2025:30263u201383.
• Sweitzer MM, Lazzari J, Lunsford-Avery J, McClernon FJ, Kollins SH, Perkins KA, et al. Effects of initial nicotine exposure on cognition and nicotine reinforcement among non-smoking young adults with and without attention deficit hyperactivity disorder. J Psychopharmacol. 2025 Jul;39(7):694u2013702.
• Hill ED, Kashyap P, Raffanello E, Wang Y, Moffitt TE, Caspi A, et al. Author Correction: Prediction of mental health risk in adolescents. Nat Med. 2025 Jul;31(7):2453.
• Engelhard M, Wojdyla D, Wang H, Pencina M, Henao R. Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models. Artif Intell Med. 2025 Jun;164:103130.
• Hill ED, Kashyap P, Raffanello E, Wang Y, Moffitt TE, Caspi A, et al. Prediction of mental health risk in adolescents. Nat Med. 2025 Jun;31(6):1840u20136.
• Lunsford-Avery J, Shaw R, Engelhard M, Davis N, Sweitzer M, Parekh S, et al. 1017 Feasibility and Acceptability of SHEETS: A New Digital Intervention for Enhancing Sleep Regularity in Adolescents. In: SLEEP. Oxford University Press (OUP); 2025. p. A440u2013A440.
• Zhao Y, Engelhard M. Balancing Interpretability and Flexibility in Modeling Diagnosticn Trajectories with an Embedded Neural Hawkes Process Model. 2025.
• Loh DR, Hill ED, Liu N, Dawson G, Engelhard MM. Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis. JMIR AI. 2025 Mar 27;4:e62985.
• Kumar A, Wang H, Muir KW, Mishra V, Engelhard M. A Cross-Sectional Study of GPT-4u2013Based Plain Language Translation of Clinical Notes to Improve Patient Comprehension of Disease Course and Management. NEJM AI. 2025 Jan 23;2(2).
• Wang D, Sklar B, Tian J, Gabriel R, Engelhard M, McNabb RP, et al. Improving Artificial Intelligence-based Microbial Keratitis Screening Tools Constrained by Limited Data Using Synthetic Generation of Slit-Lamp Photos. Ophthalmol Sci. 2025;5(3):100676.
• Wang D, Ownagh V, Hsu ST, Valikodath N, Kuo AN, Engelhard M, et al. Improving Pediatric Retinal Disease AI Screening Tools Constrained by Limited Data Using Synthetic Generation of Ultra-widefield Fundus Photos. In: INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE. 2025.
• Yan M, Xia M, Huang WA, Hong C, Goldstein BA, Engelhard MM. Predicting Partially Observed Long-Term Outcomes with Adversarial Positive-Unlabeled Domain Adaptation. In: Proceedings of Machine Learning Research. 2025.
• Cheng T, Cheng TX, Sepulveda JMG, Engelhard MM, Reed SD, Ozdemir S. Predicting Patient Preferences Using Large-Language-Models (LLM). In: PATIENT-PATIENT CENTERED OUTCOMES RESEARCH. 2025. p. 583u2013583.
• Pisetsky D, Zhao Y, Engelhard M, Eudy A, Tedeschi P, Verdone A, et al. A NOVEL MODELING APPROACH TO ELUCIDATE THE ROLE OF AUTOANTIBODIES IN COMPLEMENT ACTIVATION IN SLE. In: JOURNAL OF RHEUMATOLOGY. 2025. p. 221u20132.
• Huang WA, Engelhard M, Coffman M, Hill ED, Weng Q, Scheer A, et al. A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis. J Biomed Inform. 2024 Sep;157:104711.
• Choi J, Palumbo N, Chalasani P, Engelhard MM, Jha S, Kumar A, et al. MALADE: Orchestration of LLM-powered Agents with Retrieval Augmentedn Generation for Pharmacovigilance. 2024.
• Sun M, Engelhard MM, Bedoya AD, Goldstein BA. Incorporating informatively collected laboratory data from EHR in clinical prediction models. BMC Med Inform Decis Mak. 2024 Jul 24;24(1):206.
• Meng M-L, Fuller M, Federspiel JJ, Engelhard M, McNeil A, Ernst L, et al. Maternal Morbidity According to Mode of Delivery Among Pregnant Patients With Pulmonary Hypertension. Anesth Analg. 2024 May 1;138(5):1011u20139.
• Hickey J, Henao R, Wojdyla D, Pencina M, Engelhard M. Adaptive Discretization for Event PredicTion (ADEPT). Proc Mach Learn Res. 2024 May;238:1351u20139.
• Song A, Lusk JB, Roh K-M, Hsu ST, Valikodath NG, Lad EM, et al. RobOCTNet: Robotics and Deep Learning for Referable Posterior Segment Pathology Detection in an Emergency Department Population. Transl Vis Sci Technol. 2024 Mar 1;13(3):12.
• Lanners Q, Weng Q, Meng ML, Engelhard MM. Common Event Tethering to Improve Prediction of Rare Clinical Events. In: Proceedings of Machine Learning Research. 2024. p. 2136u201362.
• Wang D, Sklar B, Tian J, Garson N, Gabriel R, Engelhard M, et al. Synthetic Data Generation of Microbial Keratitis Slit Lamp Photos Using Limited Data. In: INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE. 2024.
• Li B, Thomson AJ, Nassif H, Engelhard MM, Page D. On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models. In: Advances in neural information processing systems. 2024. p. 4598u2013628.
• Choi J, Palumbo N, Chalasani P, Engelhard MM, Jha S, Kumar A, et al. MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance. In: Proceedings of Machine Learning Research. 2024.
• Pisetsky D, Zhao Y, Engelhard M, Eudy A, Tedeschi P, Verdone A, et al. A Novel Modeling Approach to Elucidate the Role of Autoantibodies in Complement Activation in SLE. In: ARTHRITIS & RHEUMATOLOGY. 2024. p. 4860u20133.
• Lunsford-Avery J, Krystal A, Engelhard M. LIGHT REGULARITY ASSOCIATED WITH COGNITIVE PERFORMANCE IN ADOLESCENTS WITH ADHD. In: SLEEP. 2024. p. A349u2013A349.
• Meng M-L, Federspiel JJ, Fuller M, McNeil A, Habib AS, Quist-Nelson J, et al. Severe Maternal Morbidity According to Mode of Delivery Among Pregnant Patients With Cardiomyopathies. JACC Heart Fail. 2023 Dec;11(12):1678u201389.
• Gu Z, Dawson G, Engelhard M. Sex differences in the age of childhood autism diagnosis and the impact of co-occurring conditions. Autism Res. 2023 Dec;16(12):2391u2013402.
• Hickey J, Henao R, Wojdyla D, Pencina M, Engelhard MM. Improving Event Time Prediction by Learning to Partition the Event Timen Space. 2023.
• Chen J, Engelhard M, Henao R, Berchuck S, Eichner B, Perrin EM, et al. Enhancing early autism prediction based on electronic records using clinical narratives. J Biomed Inform. 2023 Aug;144:104390.
• Li B, Thomson AJ, Nassif H, Engelhard MM, Page D. On Neural Networks as Infinite Tree-Structured Probabilistic Graphicaln Models. 2023.
• Engelhard MM, Henao R, Berchuck SI, Chen J, Eichner B, Herkert D, et al. Predictive Value of Early Autism Detection Models Based on Electronic Health Record Data Collected Before Age 1 Year. JAMA Netw Open. 2023 Feb 1;6(2):e2254303.
• Hong C, Pencina MJ, Wojdyla DM, Hall JL, Judd SE, Cary M, et al. Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups. JAMA. 2023 Jan 24;329(4):306u201317.
• Bidopia T, Engelhard MM, Kollins SH, Lunsford-Avery JR. Screen media technology and ADHD in children and adolescents: Potential perils and emerging opportunities. In: Encyclopedia of Child and Adolescent Health First Edition. 2023. p. 260u201374.
• Glasgow TE, Adams EL, Ksinan A, Barsell DJ, Lunsford-Avery J, Chen S, et al. Sleep onset, duration, or regularity: which matters most for child adiposity outcomes? In: Int J Obes (Lond). 2022. p. 1502u20139.
• Doerstling SS, Akrobetu D, Engelhard MM, Chen F, Ubel PA. A Disease Identification Algorithm for Medical Crowdfunding Campaigns: Validation Study. J Med Internet Res. 2022 Jun 21;24(6):e32867.
• Lunsford-Avery JR, Wang KW, Kollins SH, Chung RJ, Keller C, Engelhard MM. Regularity and Timing of Sleep Patterns and Behavioral Health Among Adolescents. J Dev Behav Pediatr. 2022 May 1;43(4):188u201396.
• Correction. Journal of the American Academy of Child & Adolescent Psychiatry. 2022 Mar;61(3):461u2013461.
• Lunsford-Avery JR, Kollins SH, Kansagra S, Wang KW, Engelhard MM. Impact of daily caffeine intake and timing on electroencephalogram-measured sleep in adolescents. J Clin Sleep Med. 2022 Mar 1;18(3):877u201384.
• Engelhard M, Henao R. Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data. Proc Mach Learn Res. 2022 Mar;151:9571u201381.
• Oliver J, Engelhard M, Stevens B, McQuoid J, McClernon FJ. Probing Disparities in Exposure to Smoking Contexts Using Computer Vision. In: NEUROPSYCHOPHARMACOLOGY. 2022. p. 439u201340.
• Lunsford-Avery J, Kansagra S, Kollins S, Engelhard M. Leveraging convenient wearable technology to assess adolescent sleep: Physical and psychiatric health correlates of single-channel sleep EEG in a community sample of youth. In: JOURNAL OF SLEEP RESEARCH. 2022.
• Lunsford-Avery JR, Engelhard MM, Navar AM, Kollins SH. Author Correction: Validation of the Sleep Regularity Index in Older Adults and Associations with Cardiometabolic Risk. Sci Rep. 2021 Dec 16;11(1):24398.
• Engelhard MM, Du2019Arcy J, Oliver JA, Kozink R, McClernon FJ. Prediction of Smoking Risk From Repeated Sampling of Environmental Images: Model Validation. J Med Internet Res. 2021 Nov 1;23(11):e27875.
• Engelhard M, McGough D, Kollins S. 5.22 Improving the Predictive Value of Self-Report in Adult ADHD Diagnosis. In: Journal of the American Academy of Child & Adolescent Psychiatry. Elsevier BV; 2021. p. S157u2013S157.
• Engelhard M, Berchuck S, Garg J, Rusincovitch S, Dawson G, Kollins S. Patterns of Health Services Use Before Age 1 in Children Later Diagnosed With ADHD. J Atten Disord. 2021 Oct;25(12):1639.
• Doerstling SS, Akrobetu D, Engelhard MM, Chen F, Ubel PA. A Disease Identification Algorithm for Medical Crowdfunding Campaigns: Validation Study (Preprint). JMIR Publications Inc. 2021.
• Oliver JA, Sweitzer MM, Engelhard MM, Hallyburton MB, Ribisl KM, McClernon FJ. Identifying neural signatures of tobacco retail outlet exposure: Preliminary validation of a "community neuroscience" paradigm. Addict Biol. 2021 Sep;26(5):e13029.
• Engelhard MM, Navar AM, Pencina MJ. Incremental Benefits of Machine Learning-When Do We Need a Better Mousetrap? JAMA Cardiol. 2021 Jun 1;6(6):621u20133.
• Engelhard MM, Du2019Arcy J, Oliver JA, Kozink R, McClernon FJ. Prediction of Smoking Risk From Repeated Sampling of Environmental Images: Model Validation (Preprint). 2021 Feb 11;
• Subramanian V, Engelhard M, Berchuck S, Chen L, Henao R, Carin L. SpanPredict: Extraction of Predictive Document Spans with Neural Attention. In: Naacl Hlt 2021 2021 Conference of the North American Chapter of the Association for Computational Linguistics Human Language Technologies Proceedings of the Conference. 2021. p. 5234u201358.
• Vilardaga R, Fisher T, Palenski PE, Kumaresan V, Mannelli P, Sweitzer MM, et al. Review of Popularity and Quality Standards of Opioid-Related Smartphone Apps. Curr Addict Rep. 2020 Dec;7(4):486u201396.
• Engelhard MM, Berchuck SI, Garg J, Henao R, Olson A, Rusincovitch S, et al. Health system utilization before age 1 among children later diagnosed with autism or ADHD. Sci Rep. 2020 Oct 19;10(1):17677.
• Lunsford-Avery JR, Keller C, Kollins SH, Krystal AD, Jackson L, Engelhard MM. Feasibility and Acceptability of Wearable Sleep Electroencephalogram Device Use in Adolescents: Observational Study. JMIR Mhealth Uhealth. 2020 Oct 1;8(10):e20590.
• Lunsford-Avery JR, Keller C, Kollins SH, Krystal AD, Jackson L, Engelhard MM. Feasibility and Acceptability of Wearable Sleep Electroencephalogram Device Use in Adolescents: Observational Study (Preprint). 2020 May 25;
• Engelhard M, Berchuck S, Du2019Arcy J, Henao R. Neural Conditional Event Time Models. 2020 Apr 3;
• Lunsford-Avery JR, Engelhard MM, Navar AM, Kollins SH. Author Correction: Validation of the Sleep Regularity Index in Older Adults and Associations with Cardiometabolic Risk. Sci Rep. 2020 Feb 14;10(1):2993.
• Lunsford-Avery JR, Damme KSF, Engelhard MM, Kollins SH, Mittal VA. Sleep/Wake Regularity Associated with Default Mode Network Structure among Healthy Adolescents and Young Adults. Sci Rep. 2020 Jan 16;10(1):509.
• Oliver J, Froeliger B, Engelhard M, Conklin C, McClernon F. Exposure to Smoking Context Potentiates Habitual Motor Response. In: NEUROPSYCHOPHARMACOLOGY. 2020. p. 356u2013356.
• Engelhard M, Berchuck S, Du2019Arcy J, Henao R. Neural Conditional Event Time Models. In: Proceedings of Machine Learning Research. 2020. p. 223u201344.
• Lunsford-Avery J, Wang KW, Engelhard M, Keller C, Kansagra S, Kollins S. Impact of Daily Caffeine on Actigraphically-Measured Sleep Duration Among Adolescents With and Without Attention-Deficit/Hyperactivity Disorder. In: NEUROPSYCHOPHARMACOLOGY. 2020. p. 82u20133.
• Lunsford-Avery J, Kollins S, Keller C, Engelhard M. Ambulatory EEG-measured sleep associated with attention-deficit/hyperactivity disorder symptom severity among adolescents. In: JOURNAL OF SLEEP RESEARCH. 2020. p. 162u20133.
• Engelhard MM, Oliver JA, McClernon FJ. Digital envirotyping: quantifying environmental determinants of health and behavior. NPJ Digit Med. 2020;3:36.
• Engelhard MM, Kollins SH. The Many Channels of Screen Media Technology in ADHD: a Paradigm for Quantifying Distinct Risks and Potential Benefits. Curr Psychiatry Rep. 2019 Aug 13;21(9):90.
• Engelhard MM, Oliver JA, Henao R, Hallyburton M, Carin LE, Conklin C, et al. Identifying Smoking Environments From Images of Daily Life With Deep Learning. JAMA Netw Open. 2019 Aug 2;2(8):e197939.
• Raman S, Engelhard M, Kollins SH. Driving the Point Home: Novel Approaches to Mitigate Crash Risk for Patients With ADHD. Pediatrics. 2019 May 20;
• Chen S, Perera R, Engelhard MM, Lunsford-Avery JR, Kollins SH, Fuemmeler BF. A generic algorithm for sleep-wake cycle detection using unlabeled actigraphy data. In: 2019 IEEE EMBS International Conference on Biomedical and Health Informatics Bhi 2019 Proceedings. 2019.
• Kuo CT, Lu Y, Kovarik L, Engelhard M, Karim AM. Structure Sensitivity of Acetylene Semi-Hydrogenation on Pt Single Atoms and Subnanometer Clusters. ACS Catalysis. 2019 Jan 1;11030u201341.
• Lunsford-Avery JR, Engelhard MM, Navar AM, Kollins SH. Validation of the Sleep Regularity Index in Older Adults and Associations with Cardiometabolic Risk. Sci Rep. 2018 Sep 21;8(1):14158.
• Engelhard M, Xu H, Carin L, Oliver JA, Hallyburton M, McClernon FJ. Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model. Proc Mach Learn Res. 2018 Aug;85:312u201331.
• Engelhard M, Xu H, Carin L, Oliver JA, Hallyburton M, Joseph McClernon F. Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model. In: Proceedings of Machine Learning Research. 2018. p. 312u201331.
• LeFevre AE, Dane P, Copley CJ, Pienaar C, Parsons AN, Engelhard M, et al. Unpacking the performance of a mobile health information messaging program for mothers (MomConnect) in South Africa: evidence on program reach and messaging exposure. BMJ Glob Health. 2018;3(Suppl 2):e000583.
• Engelhard M, Copley C, Watson J, Pillay Y, Barron P, LeFevre AE. Optimising mHealth helpdesk responsiveness in South Africa: towards automated message triage. BMJ Glob Health. 2018;3(Suppl 2):e000567.
• Engelhard MM, Patek SD, Lach JC, Goldman MD. Real-world walking in multiple sclerosis: Separating capacity from behavior. Gait Posture. 2018 Jan;59:211u20136.
• Dandu SR, Engelhard MM, Qureshi A, Gong J, Lach JC, Brandt-Pearce M, et al. Understanding the Physiological Significance of Four Inertial Gait Features in Multiple Sclerosis. IEEE J Biomed Health Inform. 2018 Jan;22(1):40u20136.
• Brenton JN, Engelhard M, Woolbright E, Koshiya H, Herod SG, Engel CE, et al. Continuous accelerometry as a measure of physical activity impairment in paediatric-onset multiple sclerosis subjects versus healthy controls. In: MULTIPLE SCLEROSIS JOURNAL. SAGE PUBLICATIONS LTD; 2017. p. 107u20138.
• Qureshi A, Engelhard MM, Brandt-Pearce M, Goldman MD. Demonstrating the real-world significance of the mid-swing to heel strike part of the gait cycle using spectral features. In: 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks Bsn 2017. 2017. p. 133u20136.
• Qureshi A, Brandt-Pearce M, Engelhard MM, Goldman MD. Relationship between kernel density function estimates of gait time series and clinical data. In: 2017 IEEE EMBS International Conference on Biomedical and Health Informatics Bhi 2017. 2017. p. 329u201332.
• Engelhard MM, Patek SD, Sheridan K, Lach JC, Goldman MD. Remotely engaged: Lessons from remote monitoring in multiple sclerosis. Int J Med Inform. 2017 Apr;100:26u201331.
• Brenton JN, Koshiya H, Engel C, Herod S, Engelhard M, Goldman M. Utility of Physical Disability Outcome Measures in Pediatric-Onset Multiple Sclerosis. In: NEUROLOGY. 2017.
• Engelhard MM, Schmidt KM, Engel CE, Brenton JN, Patek SD, Goldman MD. The e-MSWS-12: improving the multiple sclerosis walking scale using item response theory. Qual Life Res. 2016 Dec;25(12):3221u201330.
• Engelhard MM, Lach JC, Schmidt KM, Goldman MD, Patek SD. Adaptive symptom reporting for mobile patient-reported disability assessment. In: 2016 IEEE Wireless Health Wh 2016. 2016. p. 172u20139.
• Cincotta MC, Engelhard MM, Stankey M, Goldman MD. Fatigue and fluid hydration status in multiple sclerosis: A hypothesis. Mult Scler. 2016 Oct;22(11):1438u201343.
• Engelhard MM, Dandu SR, Patek SD, Lach JC, Goldman MD. Quantifying six-minute walk induced gait deterioration with inertial sensors in multiple sclerosis subjects. Gait Posture. 2016 Sep;49:340u20135.
• Dandu SR, Engelhard MM, Goldman MD, Lach J. Determining physiological significance of inertial gait features in multiple sclerosis. In: Bsn 2016 13th Annual Body Sensor Networks Conference. 2016. p. 266u201371.
• Engelhard MM, Dandu SR, Lach JC, Goldman MD, Patek SD. Toward detection and monitoring of gait pathology using inertial sensors under rotation, scale, and offset invariant dynamic time warping. In: Bodynets International Conference on Body Area Networks. 2015.
• Gong J, Engelhard MM, Goldman MD, Lach J. Correlations between inertial body sensor measures and clinical measures in multiple sclerosis. In: Bodynets International Conference on Body Area Networks. 2015.
• Zee R, Seaman SJ, Engelhard M, Schenkman NS. MP14-07 SURGICAL ATTENTION AND MOVEMENT IN NOVICE AND EXPERT ROBOTIC SURGEONS. In: Journal of Urology. Ovid Technologies (Wolters Kluwer Health); 2014.
• Ribeiro S, Shi X, Engelhard M, Zhou Y, Zhang H, Gervasoni D, et al. Novel experience induces persistent sleep-dependent plasticity in the cortex but not in the hippocampus. Front Neurosci. 2007 Nov;1(1):43u201355.
• Engelhard M. Adaptive Algorithms for Personalized Health Monitoring.

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