Erraguntla, Madhav
individual record
Associate Professor of the Practice
Positions:
- Associate Professor of the Practice, Industrial and Systems Engineering, College of Engineering
education and training
- Ph.D. in Industrial Engineering, Texas A&M University - (College Station, Texas, United States) 1996
- M.Tech. in Industrial Engineering, National Institute of Industrial Engineering - (Mumbai, Maharashtra, India) 1989
- B.T. in Mechanical Engineering, Sri Venkateswara University - (Tirumala - Tirupati, Andhra Pradesh, India) 1987
selected publications
Academic Articles31
- Yu, M., Pasman, H., Erraguntla, M., Quddus, N., & Kravaris, C. (2022). A framework to identify and respond to weak signals of disastrous process incidents based on FRAM and machine learning techniques. Process Safety and Environmental Protection. 158, 98-114.
- Erraguntla, M., Dave, D., Zapletal, J., Myles, K., Adelman, Z. N., Pohlenz, T. D., & Lawley, M. (2021). Predictive model for microclimatic temperature and its use in mosquito population modeling. Scientific Reports. 11(1), 18909.
- Dave, D., DeSalvo, D. J., Haridas, B., McKay, S., Shenoy, A., Koh, C. J., Lawley, M., & Erraguntla, M. (2021). Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.. J Diabetes Sci Technol. 15(4), 842-855.
- Yu, M., Erraguntla, M., Quddus, N., & Kravaris, C. (2021). A data-driven approach of quantifying function couplings and identifying paths towards emerging hazards in complex systems. Process Safety and Environmental Protection. 150, 464-477.
- Curry, G. L., Moya, H., Erraguntla, M., & Banerjee, A. (2021). Transient Queueing Analysis for Emergency Hospital Management. IISE Transactions on Healthcare Systems Engineering. 1-20.
Chapters3
- Qaraqe, M., Erraguntla, M., & Dave, D. (2021). AI and Machine Learning in Diabetes Management: Opportunity, Status, and Challenges. Multiple Perspectives on Artificial Intelligence in Healthcare. 129-141. Springer International Publishing.
- Tomasulo, P., Erraguntla, M., & Kamel, H. (2012). Blood Donation: An Approach to Donor Vigilance. Hemovigilance. 75-98. Wiley.
- Ramachandran, S., Erraguntla, M., & Benjamin, P. (2002). A Knowledge Based Framework for the Design of Soft-Computing Systems. GRID-BASED PROBLEM SOLVING ENVIRONMENTS. Intelligent Information Processing. 129-140. Springer US.
Conference Papers32
- Islam, M. S., Qaraqe, M. K., Abbas, H. T., Erraguntla, M., & Abdul-Ghani, M. (2020). The Prediction of Diabetes Development: A Machine Learning Framework. 2020 IEEE 5th Middle East and Africa Conference on Biomedical Engineering (MECBME), 2020 IEEE 5th Middle East and Africa Conference on Biomedical Engineering (MECBME). 00, 1-6.
- Islam, M. S., Qaraqe, M. K., Abbas, H. T., Erraguntla, M., Abdul-Ghani, M., & IEEE. (2020). The Prediction of Diabetes Development: A Machine Learning Framework. 2020 IEEE 5TH MIDDLE EAST AND AFRICA CONFERENCE ON BIOMEDICAL ENGINEERING (MECBME). 154-159.
- Aljihmani, L., Abbas, H., Zhu, Y., Mehta, R. K., Sasangohar, F., Erraguntla, M., ... Qaraqe, K. (2019). Features of Physiological Tremor in Diabetic Patients. 2019 IEEE International Smart Cities Conference (ISC2), 2019 IEEE International Smart Cities Conference (ISC2). 00, 268-271.
- Aljihmani, L., Zhuz, Y., Abbas, H. T., Mehta, R., Sasangohar, F., Erraguntla, M., Abbasi, Q. H., & Qaraqe, K. (2019). Spectral Analysis of Hand Tremors Induced During a Fatigue Test. 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS). 00, 658-663.
- Freeze, J., Erraguntla, M., & Verma, A. (2018). Data Integration and Predictive Analysis System for Disease Prophylaxis: Incorporating Dengue Fever Forecasts. Proceedings of the 51st Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences. 913-922.
Repository Documents / Preprints5
- Ziyadidegan, S., Razavi, M., Pesarakli, H., Javid, A. H., & Erraguntla, M. (2021). Factors affecting the COVID-19 risk in the US counties: an innovative approach by combining unsupervised and supervised learning.
- Ziyadidegan, S., Razavi, M., Pesarakli, H., Javid, A., & Erraguntla, M. (2021). Factors affecting the COVID-19 risk in the US counties: an innovative approach by combining unsupervised and supervised learning.
- Dave, D., Erraguntla, M., Lawley, M., DeSalvo, D., Haridas, B., McKay, S., & Koh, C. (2021). Improved Low-Glucose Predictive Alerts Based on Sustained Hypoglycemia: Model Development and Validation Study (Preprint).
- Zahed, K., Sasangohar, F., Mehta, R., Erraguntla, M., & Qaraqe, K. (2020). Diabetes Management Experience and the State of Hypoglycemia: National Online Survey Study (Preprint).
- Abbas, H., Alic, L., Erraguntla, M., Ji, J., Abdul-Ghani, M., Abbasi, Q., & Qaraqe, M. (2019). Predicting long-term Type 2 Diabetes with Support Vector Machine using Oral Glucose Tolerance Test.
researcher on
Principal Investigator1
Co-Principal Investigator2
recent teaching activities
- ISEN302 Econ Anly Engr Project Instructor
- ISEN310 Uncertainty Modeling For Ie Instructor
- ISEN340 Operations Research Ii Instructor
- ISEN413 Advanced Data Analytics Instructor
- ISEN491 Hnr-research Instructor
Email
merraguntla@tamu.edu
First Name
Madhav
Last Name
Erraguntla
mailing address
Texas A&M University; Industrial Engineering; 3131 TAMU
College Station, TX 77843-3131
USA