About

Jay Mehta, MD, MEd, is a Professor of Clinical Pediatrics specializing in Rheumatology at the Perelman School of Medicine at the University of Pennsylvania. He serves as an Attending Physician in the Division of Rheumatology at the Children's Hospital of Philadelphia. Dr. Mehta is recognized as a nationally-renowned pediatric rheumatology medical educator. He holds multiple leadership roles, including Director of the Pediatric Rheumatology Fellowship Program at Children's Hospital of Philadelphia, Medical Academic Director of the Masters in Medical Education at the University of Pennsylvania Graduate School of Education, and Director of the Coaching Collaborative at Children's Hospital of Philadelphia. His educational background includes a BS in Brain and Cognitive Sciences from the Massachusetts Institute of Technology, an MD from the University of Nevada School of Medicine, an MS in Translational Research from the University of Pennsylvania School of Medicine, and a MEd in Medical Education from the University of Pennsylvania Graduate School of Education. Dr. Mehta's work focuses on pediatric rheumatology, medical education, and fellowship training, with a particular emphasis on developing competency assessments, supervision scales, and implementing entrustable professional activities in pediatric subspecialty training.

Research topics

• Medicine
• Internal medicine
• Mathematics
• Immunology
• Pure mathematics

Selected publications

• Predictive Quality Engineering in Distributed Data Platforms Using Machine Learning

  2026-04-06

  article1st authorCorresponding

  This article examines the role of predictive quality engineering in distributed data platforms by applying machine learning techniques to telemetry data. Modern software systems emit large volumes of logs, metrics, and traces, yet much of this data remains underutilized for quality assurance and failure prevention. This paper presents a practical framework that integrates telemetry ingestion, preprocessing, feature engineering, model selection, and real-time feedback loops to enable early detection of reliability risks. The framework is illustrated through three representative use cases: log anomaly detection, prediction of test flakiness in CI pipelines, and forecasting of performance regressions.In operational deployments used as case studies, the approach reduced major incident frequency by approximately 70%, decreased mean time to resolution by more than 65%, and improved detection of unstable test behavior with F1-scores above 0.85 when compared to rule-based baselines. Rather than proposing a novel algorithm, this work focuses on the systems architecture, engineering practices, and deployment considerations required to operationalize predictive quality engineering in real-world environments. The results suggest that telemetry-driven predictive methods can transform quality assurance from a reactive activity into a proactive engineering discipline.

  PublisherDOI

• Perturbed Dirichlet Series and the Difference Operator

  Axioms · 2026-04-10

  articleOpen access

  The most well-known perturbed Dirichlet series is the Hurwitz zeta-function. Its analytic continuation via the binomial expansion has been studied extensively, beginning with Wilton’s work. In this paper, we shall provide, above all things, two striking instances of the binomial expansion. One is elucidation of Mikolás an integral formula for the Hurwitz zeta-function valid in the critical strip to the effect that it is a manifestation of the picking-up principle of the values at the poles of the gamma function of the binomial expansion. The other is a new proof of Hasse’s formula by the binomial expansion. Also, we show the effectiveness of the difference operator in dealing with a series of the form ∑n=0∞(n+a1)−s1(n+a2)−s2(n+a3)−s3⋯,Resj>2,j=1,2,⋯ where 0<aj≤1 or aj∈H (in the upper half-plane). Furthermore, elucidation of the above results is made in the light of the Hardy–Hecke transform.

  PublisherDOI

• Safest-Value of the Number of Primes in RSA Modulus and an Improvised Generalized Multi-Moduli RSA

  Mathematics · 2025-05-21 · 1 citations

  articleOpen access1st authorCorresponding

  Several attacks on the well-known RSA cryptosystem that can be extended to a multi-prime version of RSA reveal that it is preferable to use the modulus having more prime factors. On the contrary, the larger the number of prime factors of the modulus, the greater the risk of its factorization, due to the reduced size of its prime factors. In this paper, we derive an optimal value of the number of prime factors in a multi-prime RSA modulus and introduce the notion of the “safest-value” and determine such safest-values for moduli of different sizes. By utilizing this concept, we propose an enhanced version of our Generalized Multi-Moduli RSA (GMMRSA), which is now secure against even more attacks than its previous version.

  PublisherOA PDFDOI

• Enhancing Beach Conservation with SSD-Enabled Waste Detection

  Lecture notes in networks and systems · 2025-01-01

  book-chapter
  PublisherDOI

• Pediatric Fellows and Their Ability to Meet Minimum Supervision Levels at Graduation

  PEDIATRICS · 2025-06-15 · 3 citations

  article

  OBJECTIVE: Assessing pediatric subspecialty fellows using entrustable professional activities (EPAs) to determine readiness for graduation has not been described. We aimed to determine whether graduating pediatric fellows are meeting the minimum supervision level at graduation previously identified by program directors for the clinical EPAs and the relationship between meeting these levels and initial subspecialty board certification. METHODS: Pediatric fellows in 14 subspecialties were assessed by clinical competency committees in the spring before graduation in 2019 to 2022 on 3 EPAs common to all subspecialties that involve direct patient care and the subspecialty-specific EPAs. Publicly available board certification data were obtained from the American Board of Pediatrics. RESULTS: EPA supervision levels were collected on 1480 fellows, representing approximately 27% of all graduating fellows. A total of 117 (7.9%) fellows did not meet the minimum supervision level for at least 1 EPA, with some requiring direct supervision. Of fellows who did not achieve the expected level at graduation, 83 (70.9%) were certified. Those who met the minimum level for all clinical EPAs had a higher certification rate compared with those who did not meet the minimum for at least 1 EPA (80.6% vs 70.9%; P = .01). CONCLUSIONS: Almost 10% of pediatric fellows are not meeting the expected supervision level for the clinical EPAs at graduation, and yet over 70% of them passed their subspecialty certification examination. This study provides support for using EPAs to determine readiness for graduation and demonstrates that some fellows may need additional training or continued supervision after completion of their fellowship.

  PublisherDOI

• Many Pediatric Subspecialty Fellows Are Not Ready to Graduate From Fellowship in 2 Years

  PEDIATRICS · 2025-03-17 · 9 citations

  articleOpen access

  BACKGROUND AND OBJECTIVES: The American Board of Pediatrics requires that proposed changes to the duration of pediatric subspecialty training must include a framework for competency assessment with a measurement component. We analyzed the clinical Entrustable Professional Activity (EPA) level of supervision ratings across 3-year pediatric fellowships to determine if trainees met the minimum thresholds for graduation after 2 years of fellowship training. METHODS: From spring 2019 through spring 2022, Clinical Competency Committees (CCCs) reported fellow supervision level ratings for all clinical EPAs, fellowship program directors (FPDs) assessed the scholarship EPA supervision level, and fellows self-reported their required level of supervision for all EPAs. Ratings were compared with minimum supervision level thresholds for fellow graduation previously identified by FPDs. We analyzed the proportion of fellows achieving these EPA supervision level thresholds after 2 and 3 years of training. RESULTS: CCCs reported ratings for 1538 second-year and 1505 third-year fellows. Fewer than 50% of fellows met clinical EPA supervision level thresholds for graduation after 2 years of training, increasing to 86%-100% across subspecialties at 3 years. Fellow self-assessment aligned well with CCC ratings. FPDs reported that 64%-68% of fellows across subspecialties met the scholarship EPA supervision level threshold for graduation after 2 years compared with 99%-100% at 3 years. CONCLUSIONS: As pediatric fellowships are currently structured and using an EPA assessment framework, many trainees are not ready to graduate after 2 years.

  PublisherOA PDFDOI

• AUTONOMOUS PATCH VALIDATION FOR ZERO-DAY EXPLOITS IN ENTERPRISE CLOUDS

  International Journal of Apllied Mathematics · 2025-10-06

  articleOpen access1st authorCorresponding

  Enterprise cloud infrastructures are constantly at risk from zero-day vulnerabilities, which frequently get past traditional security protections before efficient remedies can be put in place.Conventional patch validation techniques are usually slow, reactive, and lack the analytical depth needed to properly link patch interventions to results.This self-contained patch validation system integrates anomaly detection, predictive risk modeling, and causal inference into a single pipeline.The NSL-KDD dataset was used to train and assess machine learning models, enabling proactive prioritizing of high-risk patches, real-time anomaly detection, and statistical validation for change impact through causal analysis.The recommended method achieved a 93.76% detection accuracy and significantly reduced the detection time from 0.61s to 0.22s. Causal inference confirmed that the deployed patches were responsible for the reported behavioral changes with a 99.4% likelihood. Ablation studies validated the contribution of each module, and unsupervised detection further enhanced the system's robustness. The technology provides a scalable, interpretable, and efficient method of addressing enterprise cloud zero-day vulnerabilities.By enabling quicker, more reliable, and understandable patch distribution through a combination of statistical analysis and causal validation, it enhances the overall security posture.

  PublisherOA PDFDOI

• Clinical Spectrum of Epstein Barr Viremia in Hematological Disorders: Case Series and Review of Literature

  Indian Journal of Hematology and Blood Transfusion · 2025-01-27

  article
  PublisherDOI

• Child Health Needs and the Pediatric Rheumatology Workforce: 2020–2040

  PEDIATRICS · 2024-02-01 · 11 citations

  articleSenior author

  The Pediatric Rheumatology (PRH) workforce supply in the United States does not meet the needs of children. Lack of timely access to PRH care is associated with poor outcomes for children with rheumatic diseases. This article is part of a Pediatrics supplement focused on anticipating the future pediatric subspecialty workforce supply. It draws on information in the literature, American Board of Pediatrics data, and findings from a model that estimates the future supply of pediatric subspecialists developed by the Sheps Center for Health Services Research at the University of North Carolina at Chapel Hill, Strategic Modeling and Analysis Ltd., and the American Board of Pediatrics Foundation. PRH has a smaller workforce per capita of children than most other pediatric subspecialties. The model demonstrates that the clinical workforce equivalent of pediatric rheumatologists in 2020 was only 0.27 per 100 000 children, with a predicted increase to 0.47 by 2040. Although the model predicts a 72% increase in providers, this number remains inadequate to provide sufficient care given the number of children with rheumatic diseases, especially in the South and West regions. The likely reasons for the workforce shortage are multifactorial, including lack of awareness of the field, low salaries compared with most other medical specialties, concerns about working solo or in small group practices, and increasing provider retirement. Novel interventions are needed to increase the workforce size. The American College of Rheumatology has recognized the dire consequences of this shortage and has developed a workforce solutions initiative to tackle these problems.

  PublisherDOI

• Blood Guard: An IoT Based Innovative RFID-Enhanced Blood Storage System with Biometric Security and Real-Time Temperature Monitoring

  2024-03-11 · 1 citations

  articleSenior author

  The Indian Council of Medical Research (ICMR) has currently developed a delivery system for medical supplies with the help of drones, called the “i-Drone” initiative. This research work aims to propose an idea, which will help in making a valuable addition to this initiative and make it smarter and more secure through the addition of several new features including RFID tags, fingerprint sensors, temperature sensors and integration with ThingSpeak and IFTTT. RFID tags will enable real-time tracking of blood bags ensuring that they are always in the right place. Fingerprint sensors will restrict access to authorized personnel, preventing unauthorized tampering. Temperature sensors will monitor the temperature of blood bags and send an alert if it falls below a safe level, ensuring that blood bags are always safe and viable. Integration with ThingSpeak and IFTTT will allow the temperature of blood bags to be displayed on a dashboard and for email alerts to be sent to registered users when the temperature drops below a safe level, providing additional transparency and accountability.

  PublisherDOI

Frequent coauthors

• Rae S. M. Yeung

  18 shared

• Edward M. Behrens

  Children's Hospital of Philadelphia

  16 shared

• Beth S. Gottlieb

  Northwell Health

  15 shared

• Daniel J. Lovell

  14 shared

• Grant S. Schulert

  University of Cincinnati

  13 shared

• Timothy Beukelman

  Childhood Arthritis and Rheumatol­ogy Research Alliance

  13 shared

• Hamid Bassiri

  Children's Hospital of Philadelphia

  12 shared

• Scott W. Canna

  Children's Hospital of Pittsburgh

  12 shared

Labs

• Jay Mehta LaboratoryPI

Education

• Ph.D., School of Mathematics

  Harish-Chandra Research Institute

  2015

• M.Sc., Department of Mathematics

  Sardar Patel University

  2008