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Dinesh Mendhe, M.S.

Computer and Information Research Scientist (USCIS Class)
Programmer Analyst I
Institute for Health, Health Care Policy and Aging Research
Office of Research Computing

dm1367@ifh.rutgers.edu, (848) 932-5828

Mr. Dinesh has been leading software development efforts for IFH’s research grants and for IFH’s general-purpose web presence. Mr. Dinesh has built statistical and scientific web applications, mobile apps,  AI/ML algorithms and models, deep learning algorithms, custom Android OS, complex runtimes, big data algorithms and frameworks, data structures, genomic and bioinformatics tools and pipelines, epigenetics tools, and research databases. In addition, he has built the ADHI software suite comprising complex statistical and survey tools. ADHI survey tool is a complete end-to-end survey tool consisting of participant management, biospecimen management, contact and scheduling, multilingual consent management, multilingual interview management, family genealogy architecture, phlebotomy management, saliva protocol management, actigraphy management, staff workflow management, and many more. ADHI software suits also consist of ADHI Coupon Manager, ADHI Canvassing tool, GPS Mobile app, Daily Questionnaire mobile app, and digital recruitment and registration tools.

Mr. Dinesh has been a full-stack developer for all the applications that were built in-house. At IFH, he has worked on a wide variety of programming technologies such as JAVA, ReactJS, Node.JS, PHP, C, C++, Python, Scala, HTML, CSS, JavaScript, AngularJS, JQuery, MySQL, SQL Server, Android, Laravel, Spring framework, Struts framework, Hibernate ORM, Eloquent ORM, etc. Mr. Dinesh also built a virtual call center using Twilio services, which uses a combination of machine learning and algorithmic techniques to route calls to different agents based on the caller’s language preference.

Project Portfolio:

List of statistical and research web applications, mobile app endpoints, reports and dashboards, and online enrollment tools:

  1. https://pophealth.rutgers.edu:6443/dashboard  (NJHealth Study central dashboard to access all research and statistical applications)
  2. https://survey.rutgers.edu/ (Inhouse-built multilingual survey platform, which also contains features such as phlebotomy management, inline multilingual consent management, contact management, participant management, actigraphy management, family tree construct, gift card management, interview management, instrument & questionnaire management, interview scheduling and calendar management, granular roles, and permissions management, and also has strong encryption and hashing mechanism)
  3. https://njhealthstudy.rutgers.edu:6444/#/login (Respondent-driven sampling tool/ snowball sampling with coupons generation, management, and tracking)
  4. https://njhealthstudy.rutgers.edu:6443/#/login (Probability sampling tool and household enumerator)
  5. https://pophealth.rutgers.edu:6443/gps-dashboard/build/#/ (GPS mobile app admin dashboard to view real-time data and study compliance)
  6. https://ifh.rutgers.edu/community-hub/
  7. https://pophealth.rutgers.edu/ (Chinese Healthy Aging Website and modified legacy survey platform / PINE and PIETY study)
  8. https://api.rutgers.edu/ (Documentation site and RESTful API endpoints for mobile apps and external partners)
  9. https://ifh.rutgers.edu/web-enrollments/register (Online Trust in Research and registration tool)
  10. http://mocksurvey.rutgers.edu/#/login (Mock survey platform for new survey platform)
  11. http://pbrn.rutgers.edu/mocksurvey/gotologin (Mock survey platform for legacy survey platform)
  12. https://ifhcore.rutgers.edu/familytree/ (Tool to build family genealogy and dyads)
  13. https://ifh.rutgers.edu/web-enrollments/sign-up (60+ enrollment marketing campaign and multilingual registration tool)

List of Public-facing websites:

  1. https://ifh.rutgers.edu/
  2. https://njhealthstudy.rutgers.edu/en
  3. https://cahpe.rutgers.edu/
  4. https://rcasia.rutgers.edu/
  5. https://cpbh.rutgers.edu/
  6. https://ifhcore.rutgers.edu/
  7. https://rcmar.rutgers.edu/
  8. https://njpbrn.rutgers.edu/private/
  9. https://healthyaging.rutgers.edu/
  10. https://ifhcommunity.rutgers.edu/
  11. https://cplb.rutgers.edu/
  12. https://promis.rutgers.edu/
  13. https://cohort.rutgers.edu/en
  14. https://capp.rutgers.edu/

Published mobile apps:

  1. Offline Registration Tool & Trust in Research Android app.
  2. GPS mobile app
  3. Daily Questionnaire mobile app
  4. Interview Screen Recorder mobile app
  5. CHAP offline survey platform mobile app
  6. Customized Android OS with Rutgers, IFH branding, custom apps, and runtime for the NJCOHORT longitudinal study.
  7. https://play.google.com/store/apps/details?id=com.casl.caslsurvey&hl=en_US&gl=US&pli=1
  8. https://www.amazon.com/Dinesh-Mendhe-Casl-Survey/dp/B07X1MWRF6
  9. https://www.amazon.com/Dinesh-Mendhe-IFH-Registration-App/dp/B085LTQ4ZP/ref=sr_1_2?qid=1670875841&refinements=p_4%3ADinesh+Mendhe&s=mobile-apps&search-type=ss&sr=1-2
  10. https://play.google.com/store/apps/details?id=com.dinesh.NJCRegistrationApp&hl=en_AU&gl=US

Peer-reviewed Journal Publications:

  1. “Human gene and disease associations for clinical‐genomics and precision medicine research.” Clinical and translational medicine, Wiley, 2020
  2. “Leveraging technology to improve health disparity research: trilingual data collection using tablets.” Journal of the American Geriatrics Society, 2019
  3. “Benchmarking student performance and engagement in an early alert predictive system using interactive radar chart.” Journal of Learning Analytics, 2016
  4. “Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine.” Scientific Reports, Nature, 2024
  5. “IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles.” Bioinformatics, 2023
  6. “A novel multifrequency GPS app for studying older adults: improving accuracy and reliability of data.” Innovation in Aging, 2023
  7. “Neighborhood segregation and characteristics of older Chinese immigrants living in greater Chicago.” Innovation in Aging, 2023
  8. “Role of genome-wide association studies, polygenic risk score and AI/ML using big data for personalized treatment to the patients with cardiovascular disease.” Future Medicine AI, 2023
  9. “Health Implications of Enduring and Emerging Stressors: Design of the New Jersey Population Health Cohort (NJHealth) Study.” SSRN, 2023
  10. “A Novel Survey Platform in the Age of COVID-19 to Increase Accuracy and Adoptability While Reducing Selection Bias.” Innovation in Aging, 2020
  11. “Mining multi-omics/genomics data to integrate ACMG approved genes and ICD codes for translational research and precision medicine.” Frontiers in Genetics, 2022
  12. “Hardware Design and Implementation of Multiagent MLP Regression for the Estimation of Gunshot Direction on IoBT Edge Gateway.”, IEEE, 2023
  13. “Integrated ACMG approved genes and ICD codes for the translational research and precision medicine.” Database. 2023.