HR job title
- Professor of the Practice
- Contact Info
- 1 979 458 2336
Erraguntla, Madhav Associate Professor of the Practice
Positions
- Associate Professor of the Practice, Industrial and Systems Engineering, College of Engineering
- Overview
- Publications
- Research
- Teaching
- Background
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Overview
Publications
selected publications
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academic article
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Zahed, K., Mehta, R., Erraguntla, M., Qaraqe, K., & Sasangohar, F.
(2023).
Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample. JMIR Diabetes.
8, e41501-e41501.
-
Jahromi, R., Zahed, K., Sasangohar, F., Erraguntla, M., Mehta, R., & Qaraqe, K.
(2023).
Hypoglycemia Detection Using Hand Tremors: Home Study of Patients With Type 1 Diabetes. JMIR Diabetes.
8, e40990-e40990.
-
Sultana, I., Erraguntla, M., Kum, H., Delen, D., & Lawley, M.
(2022).
The Interrelationships between the length of stay, readmission, and post-acute care referral in cardiac surgery patients. 2, 100062-100062.
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Aljihmani, L., Kerdjidj, O., Petrovski, G., Erraguntla, M., Sasangohar, F., Mehta, R. K., & Qaraqe, K.
(2022).
Hand tremor-based hypoglycemia detection and prediction in adolescents with type 1 diabetes. Biomedical Signal Processing and Control.
78, 103869-103869.
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Dave, D., Vyas, K., Branan, K., McKay, S., DeSalvo, D. J., Gutierrez-Osuna, R., Cote, G. L., & Erraguntla, M.
(2022).
Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: ECG and Accelerometry. Journal of Diabetes Science and Technology.
19322968221116393-193229682211163.
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Menon, S., Desalvo, D., Erraguntla, M., Pamidimukkala, K., Mckay, S., Villegas, C., & Hilliard, M. E.
(2022).
Fear of Hypoglycemia, Hypoglycemia Confidence, and Time in Range in Adolescents and Young Adults with Type 1 Diabetes (T1D). Diabetes.
71(Supplement_1),
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Ziyadidegan, S., Razavi, M., Pesarakli, H., Javid, A. H., & Erraguntla, M.
(2022).
Factors affecting the COVID-19 risk in the US counties: an innovative approach by combining unsupervised and supervised learning. Stochastic Environmental Research and Risk Assessment.
36(5), 1469-1484.
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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: Transactions of the Institution of Chemical Engineers, Part B.
158, 98-114.
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Curry, G. L., Moya, H., Erraguntla, M., & Banerjee, A.
(2022).
Transient queueing analysis for emergency hospital management. 12(1), 36-51.
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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.
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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. Journal of Diabetes Science and Technology.
15(4), 842-855.
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Dave, D., DeSalvo, D. J., Haridas, B., McKay, S., Shenoy, A., Koh, C. J., Lawley, M., & Erraguntla, M.
(2021).
Erratum on Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction. Journal of Diabetes Science and Technology.
15(4), 19322968211027985-NP2.
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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: Transactions of the Institution of Chemical Engineers, Part B.
150, 464-477.
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Zapletal, J., Najmitabrizi, N., Erraguntla, M., Lawley, M. A., Myles, K. M., & Adelman, Z. N.
(2021).
Making gene drive biodegradable. Philosophical Transactions of the Royal Society B: Biological Sciences.
376(1818), 20190804-20190804.
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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. JMIR Diabetes.
6(2), e26909-e26909.
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Aljihmani, L., Kerdjidj, O., Zhu, Y., Mehta, R. K., Erraguntla, M., Sasangohar, F., & Qaraqe, K.
(2020).
Classification of Fatigue Phases in Healthy and Diabetic Adults Using Wearable Sensor. Sensors.
20(23), 6897-6897.
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Tyagi, O., Zhu, Y., Johnson, C., Mehta, R. K., Sasangohar, F., Erraguntla, M., & Qarake, K.
(2020).
Neuromuscular Fatigue mechanisms in Type 1 diabetic men and women. Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting Human Factors and Ergonomics Society. Annual Meeting.
64(1), 960-961.
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Zahed, K., Sasangohar, F., Mehta, R., Erraguntla, M., & Qaraqe, K.
(2020).
Diabetes Management Experience and the State of Hypoglycemia: National Online Survey Study. JMIR Diabetes.
5(2), e17890-e17890.
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Zhu, Y., Jayagopal, J. K., Mehta, R. K., Erraguntla, M., Nuamah, J., McDonald, A. D., Taylor, H., & Chang, S.
(2020).
Classifying Major Depressive Disorder Using fNIRS During Motor Rehabilitation. IEEE Transactions on Neural Systems and Rehabilitation Engineering.
28(4), 961-969.
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Tyagi, O., Zhu, Y., Johnson, C., Mehta, R. K., Sasangohar, F., Erraguntla, M., & Qaraqe, K.
(2020).
Neural Signatures of Handgrip Fatigue in Type 1 Diabetic Men and Women. Frontiers in Human Neuroscience.
14, 564969.
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Zhu, Y., Mehta, R. K., Erraguntla, M., Sasangohar, F., & Qaraqe, K.
(2020).
Quantifying Accelerometer-Based Tremor Features of Neuromuscular Fatigue in Healthy and Diabetic Adults. IEEE Sensors Journal.
20(19), 11183-11190.
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Erraguntla, M., Zapletal, J., & Lawley, M.
(2019).
Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management. Health Informatics Journal.
25(4), 1170-1187.
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Sultana, I., Erraguntla, M., Kum, H., Delen, D., & Lawley, M.
(2019).
Post-acute care referral in United States of America: a multiregional study of factors associated with referral destination in a cohort of patients with coronary artery bypass graft or valve replacement. 19(1), 223.
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Sands, L. P., Savla, J., Erraguntla, M., & Lawley, M.
(2019).
CHANGE IN UNMET NEEDS FOR DAILY MOBILITY AND SELF-CARE ACTIVITIES AND FUTURE HEALTH OUTCOMES. Innovation in Aging.
3(Supplement_1), s202-s202.
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Nuamah, J. K., Sasangohar, F., Erraguntla, M., & Mehta, R. K.
(2019).
Correction to: The past, present and future of opioid withdrawal assessment: a scoping review of scales and technologies. BMC Medical Informatics and Decision Making.
19(1), 126.
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Nuamah, J. K., Sasangohar, F., Erraguntla, M., & Mehta, R. K.
(2019).
The past, present and future of opioid withdrawal assessment: a scoping review of scales and technologies. BMC Medical Informatics and Decision Making.
19(1), 113.
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Zapletal, J., Gupta, H., Erraguntla, M., Adelman, Z. N., Myles, K. M., & Lawley, M. A.
(2019).
Predicting aquatic development and mortality rates of Aedes aegypti. PLoS ONE.
14(5), e0217199-e0217199.
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McGowan, C. J., Biggerstaff, M., Johansson, M., Apfeldorf, K. M., Ben-Nun, M., Brooks, L., ... Influenza Forecasting Working Group.
(2019).
Collaborative efforts to forecast seasonal influenza in the United States, 2015-2016. Scientific Reports.
9(1), 683.
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Abbas, H. T., Alic, L., Erraguntla, M., Ji, J. X., Abdul-Ghani, M., Abbasi, Q. H., & Qaraqe, M. K.
(2019).
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test. PLoS ONE.
14(12), e0219636-e0219636.
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Hosseinian, S. M., Zhu, Y., Mehta, R. K., Erraguntla, M., & Lawley, M. A.
(2019).
Static and Dynamic Work Activity Classification from a Single Accelerometer: Implications for Ergonomic Assessment of Manual Handling Tasks. IISE Transactions on Occupational Ergonomics and Human Factors.
7(1), 59-68.
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Zahed, K., Sasangohar, F., Mehta, R., Erraguntla, M., Lawley, M., & Qaraqe, K.
(2018).
Investigating the Efficacy of Using Hand Tremors for Early Detection of Hypoglycemic Events: A Scoping Literature Review. Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting Human Factors and Ergonomics Society. Annual Meeting.
62(1), 1211-1215.
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Zhu, Y., Zahed, K., Mehta, R. K., Sasangohar, F., Erraguntla, M., Lawley, M., Abbas, H. T., & Qaraqe, K.
(2018).
Non-invasive Wearable System for Hypoglycemia Detection: A Proof of Concept User-Centered Design Process. Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting Human Factors and Ergonomics Society. Annual Meeting.
62(1), 1052-1056.
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Madanagopal, K., Erraguntla, M., & Mayer, R.
(2018).
MySidewalk Incentivized crowdsourcing to improve walkable communities. Gerontechnology : international journal on the fundamental aspects of technology to serve the ageing society.
17(s), 96-96.
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Zapletal, J., Erraguntla, M., Adelman, Z. N., Myles, K. M., & Lawley, M. A.
(2018).
Impacts of diurnal temperature and larval density on aquatic development of Aedes aegypti. PLoS ONE.
13(3), e0194025-e0194025.
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Zapletal, J., Gupta, H., Erraguntla, M., Adelman, Z. N., Myles, K. M., & Lawley, M. A.
(2018).
Predicting Aquatic Development and Mortality Rates of Aedes Aegypti. 407502.
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Delen, D., Erraguntla, M., Mayer, R. J., & Wu, C.
(2011).
Better management of blood supply-chain with GIS-based analytics. 185(1), 181-193.
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Benjamin, P. C., Erraguntla, M., Mayer, R. J., & Marshall, C.
(1999).
Toolkit for enabling analysis and modeling of adaptive workflow (TEAMWORK). ACM SIGGROUP Bulletin.
20(3), 9-9.
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BENJAMIN, P. C., ERRAGUNTLA, M., & MAYER, R. J.
(1995).
USING SIMULATION FOR ROBUST SYSTEM-DESIGN. Simulation.
65(2), 116-128.
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Mayer, R., Erraguntla, M., Menzel, C., & Hwang, J. C.
(1994).
Formal model of single agent planning situations. Journal of Systems Integration.
4(3), 219-241.
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Zahed, K., Mehta, R., Erraguntla, M., Qaraqe, K., & Sasangohar, F.
(2023).
Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample. JMIR Diabetes.
8, e41501-e41501.
-
chapter
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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.
(pp. 129-141).
Springer Nature.
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Tomasulo, P., Erraguntla, M., & Kamel, H.
(2012).
Blood Donation: An Approach to Donor Vigilance. Hemovigilance.
(pp. 75-98).
Wiley.
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Ramachandran, S., Erraguntla, M., & Benjamin, P.
(2002).
A Knowledge Based Framework for the Design of Soft-Computing Systems. IFIP Advances in Information and Communication Technology.
Intelligent Information Processing.
(pp. 129-140).
Springer Nature.
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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.
(pp. 129-141).
Springer Nature.
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conference paper
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Yang, M. u., Dave, D., Erraguntla, M., Cote, G. L., & Gutierrez-Osuna, R.
(2022).
JOINT HYPOGLYCEMIA PREDICTION AND GLUCOSE FORECASTING VIA DEEP MULTI-TASK LEARNING. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing / sponsored by the Institute of Electrical and Electronics Engineers Signal Processing Society. ICASSP (Conference).
1136-1140.
-
Branan, K. L., Reyes, G., Abel, J. A., Erraguntla, M., Gutierrez-Osuna, R., & Cote, G. L.
(2022).
Multi-Modal Physiological Sensing on the Upper Arm. Proceedings of SPIE.
1195608-1195608-6.
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Islam, S., Qaraqe, M. K., Abbas, H. T., Erraguntla, M., & Abdul-Ghani, M.
(2020).
The Prediction of Diabetes Development: A Machine Learning Framework. 1-6.
-
Islam, M. S., Qaraqe, M. K., Abbas, H. T., Erraguntla, M., & Abdul-Ghani, M.
(2020).
The Prediction of Diabetes Development: A Machine Learning Framework. 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. 268-271.
-
Aljihmani, L., Zhu, Y., Abbas, H. T., Mehta, R., Sasangohar, F., Erraguntla, M., Section, Q., & Qaraqe, K.
(2019).
Spectral Analysis of Hand Tremors Induced during a Fatigue Test. 2019 IEEE 32ND INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS).
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 ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences.
913-922.
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Zahed, K., Sasangohar, F., Zhu, Y., Mehta, R., Erraguntla, M., Lawley, M., & Qaraqe, K.
(2018).
NonInvasive Wearable Sensors to detect onset of hypoglycemia: A Literature Review
-
Gonzalez, K., Sasangohar, F., Mehta, R. K., Lawley, M., & Erraguntla, M.
(2017).
Measuring Fatigue through Heart Rate Variability and Activity Recognition: A Scoping Literature Review of Machine Learning Techniques. Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting Human Factors and Ergonomics Society. Annual Meeting.
1748-1752.
-
Erraguntla, M., Freeze, J., Delen, D., Madanagopal, K., Mayer, R., & Khojasteh, J.
(2017).
Data Integration and Predictive Analysis System for Disease Prophylaxis. Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences.
1132-1141.
-
Benjamin, P., Madanagopal, K., Erraguntla, M., & Corlette, D.
(2016).
Distributed information gathering, exploration and sensemaking toolkit (DIGEST). 449-455.
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Erraguntla, M., Tomasulo, P., Land, K., Kamel, H., Bravo, M., Whitaker, B., Mayer, R., & Khaire, S.
(2014).
Data Mining to Improve Safety of Blood Donation Process. Proceedings of the Annual Hawaii International Conference on System Sciences.
789-795.
-
Erraguntla, M., May, L., Gopal, B., Mayer, R. J., & Benjamin, P. C.
(2012).
Open source text based biovigilance. 417-422.
-
Erraguntla, M., Gopal, B., Ramachandran, S., & Mayer, R.
(2012).
Inference of Missing ICD 9 Codes Using Text Mining and Nearest Neighbor Techniques. Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences.
1060-1069.
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Kamel, H., Townsend, M., Schroeder, K., Bravo, M., Erraguntla, M., Whitaker, B., Tomasulo, P. A., & Land, K.
(2011).
United States Donor Hemovigilance System: Experience of 3 Blood Centers. Transfusion.
32A-32A.
-
Erraguntla, M., Ramachandran, S., Wu, C., & Mayer, R. J.
(2010).
Avian Influenza Datamining Using Environment, Epidemiology, and Etiology Surveillance and Analysis Toolkit (E3SAT). Proceedings of the Annual Hawaii International Conference on System Sciences.
1152-1158.
-
Erraguntla, M., Ramachandran, S., Wu, C., & Mayer, R. J.
(2010).
Avian Influenza Datamining Using Environment, Epidemiology, and Etiology Surveillance and Analysis Toolkit (E3SAT). 1-7.
-
Erraguntla, M., & Mayer, R. J.
(2007).
Medical material management support using data mining and analytics. 1578-1588.
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Ramachandran, S., Erraguntla, M., Mayer, R., & Benjamin, P.
(2007).
Data Mining in Military Health Systems - Clinical and Administrative Applications1 1 This material is based upon work partially supported by the United States Army Military Health Data Mining Library (MHDML) project (contract number DAMD17-02-C-0071). The MHDML project has developed a research data cube and the advanced data mining methods serving as knowledge analysis templates for medical knowledge discovery demonstrated in this study. This material is also partially supported by the United States Army Blood Reserve Availability Assessment, Tracking, and Management System (BRAMS) project (contract number W81XWH-05-C-0074). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Army. 158-163.
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Ramachandran, S., Erraguntla, M., Mayer, R., & Benjamin, P.
(2007).
Data mining in military health systems - Clinical and administrative applications. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
584-589.
-
Painter, M. K., Erraguntla, M., Hogg, G., & Beachkofski, B.
(2006).
Using simulation, data mining, and knowledge discovery techniques for optimized aircraft engine fleet management. Proceedings of the ... Winter Simulation Conference. Winter Simulation Conference.
1253-+.
-
Graul, M., Benjamin, P., Patki, M., & Erraguntla, M.
(2006).
A framework for modeling and simulation at multiple levels of abstraction. Proceedings of SPIE.
622706-622706-9.
-
Benjamin, P., Ramachandran, S., & Erraguntla, M.
(2005).
Towards a method for ontology driven systems reengineering (ODSR). 143-150.
-
Benjamin, P., Koola, P., Ramachandran, S., Erraguntla, M., & Fernandes, R.
(2004).
Adaptive Knowledge Discovery Framework (AKDF). 80-82.
-
Benjamin, P., Graul, M., & Erraguntla, M.
(2002).
Toolkit for Enabling Adaptive Modeling and Simulation (TEAMS). Winter Simulation Conference Proceedings.
763-771.
-
Benjamin, P., Ramachandran, S., Erraguntla, M., & Delen, D.
(2000).
Towards a Knowledge Discovery Wizard (KDW). 267-273.
-
Delen, D., Benjamin, P. C., & Erraguntla, M.
(1999).
An integrated toolkit for enterprise modeling and analysis. Winter Simulation Conference Proceedings.
289-297.
-
Benjamin, P., Painter, M., Erraguntla, M., Marshall, C., & Mayer, R.
(1998).
A Framework for Adaptive Process Modeling and Execution (FAME). 3-9.
-
Benjamin, P. C., Delen, D., & Erraguntla, M.
(1998).
An introduction to using PROSIM for business process simulation and analysis. Winter Simulation Conference Proceedings.
315-321.
-
Delen, D., Benjamin, P. C., & Erraguntla, M.
(1998).
Integrated modeling and analysis generator environment (image): A decision support tool. Winter Simulation Conference Proceedings.
1401-1408.
-
Benjamin, P., Erraguntla, M., Delen, D., & Mayer, R.
(1998).
Simulation modeling at multiple levels of abstraction. Winter Simulation Conference Proceedings.
391-398.
-
Dalal, M. A., Erraguntla, M., & Benjamin, P.
(1997).
An introduction to using ProSim for business process simulation and analysis. Winter Simulation Conference Proceedings.
718-724.
-
CECIL, J., ERRAGUNTLA, M., & MAYER, R.
(1994).
A FUZZY INFERENTIAL APPROACH FOR THE DIAGNOSIS OF DEFECTS IN ELECTRONICS ASSEMBLY. 70-74.
-
ERRAGUNTLA, M., BENJAMIN, P. C., & MAYER, R. J.
(1994).
AN ARCHITECTURE OF A KNOWLEDGE-BASED SIMULATION ENGINE. Winter Simulation Conference Proceedings.
673-680.
-
Yang, M. u., Dave, D., Erraguntla, M., Cote, G. L., & Gutierrez-Osuna, R.
(2022).
JOINT HYPOGLYCEMIA PREDICTION AND GLUCOSE FORECASTING VIA DEEP MULTI-TASK LEARNING. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing / sponsored by the Institute of Electrical and Electronics Engineers Signal Processing Society. ICASSP (Conference).
1136-1140.
-
institutional repository document
-
Zahed, K., Mehta, R., Erraguntla, M., Qaraqe, K., & Sasangohar, F.
(2022).
Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample (Preprint)
-
Jahromi, R., Zahed, K., Sasangohar, F., Erraguntla, M., Mehta, R., & Qaraqe, K.
(2022).
Hypoglycemia Detection Using Hand Tremors: Home Study of Patients With Type 1 Diabetes (Preprint)
-
Aljihmani, L., Kerdjidj, O., Petrovski, G., Erraguntla, M., Sasangohar, F., Mehta, R. K., & Qaraqe, K.
(2022).
Hand Tremor-Based Hypoglycemia Detection and Prediction in Adolescents with Type 1 Diabetes
-
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
-
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
-
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
-
Zahed, K., Mehta, R., Erraguntla, M., Qaraqe, K., & Sasangohar, F.
(2022).
Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample (Preprint)
Research
principal investigator on
co-principal investigator on
- SenSE: Multimodal noninvasive wearable sensors and machine learning for predicting critical glycemic events awarded by Directorate for Engineering - (Arlington, Virginia, United States) 2020 - 2023
- IPA for Madhav Erraguntla awarded by United States Department of Veterans Affairs - (Washington D.C., District of Columbia, United States) 2016 - 2017
Teaching
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
- ISEN613 Engr Data Analysis Instructor
- ISEN667 Engineering Economy Instructor
- ISEN684 Professional Internship: In-ab Instructor
- ISEN684 Professional Internshp Instructor
- ISEN685 Directed Studies Instructor
- ISEN691 Research Instructor
- ISEN692 Professional Study Instructor
Background
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
Contact
first name
- Madhav
has last name
- Erraguntla
mailing address
-
Texas A&M University
Industrial Engineering
3131 TAMU
College Station, TX 77843-3131
USA
Other
- merraguntla@tamu.edu