Sarath Chandra Kumar Jagupilla (sjagupil)

Sarath Chandra Kumar Jagupilla

Teaching Associate Professor and Associate Chair for Undergraduate Studies in the Department of Civil, Environmental and Ocean Engineering

Charles V. Schaefer, Jr. School of Engineering and Science

Department of Civil, Environmental and Ocean Engineering

Davidson Laboratory 244D
(201) 216-8098
(201) 216-8303
Website

Education

  • PhD (2009) Stevens Institute of Technology (Environmental Engineering)
  • MS (2002) Anna University (Irrigation Water Management)
  • BE (1999) Hindustan College of Engineering (Civil Engineering)

Research

Prof. J's research interests are in modeling and data analysis as applied to environmental and water systems. He uses empirical modeling techniques such as multivariate polynomial regression and symbolic regression, mechanistic models such as WASP, besides R and GIS to this end. He would like to work towards applications of geospatial statistics in the field of environmental and water modeling.

He has experience in field data collection for water quality modeling, solid remediation for chromium ore processing residue, and measurement of geotechnical properties.

General Information

Professor Jagupilla (Prof. J) is an Associate Professor and Associate Chair of Undergraduate Studies in the Civil, Environmental and Ocean Engineering Department at Stevens Institute of Technology. He is also a licensed professional engineer, a board-certified environmental engineer, an ASCE ExCEEd graduate and an ABET PEV (program evaluator) for AAEES. Prof. J has ~18 years of teaching and research experience in water, environmental and geo-environmental experimentation, field sampling, data analysis, and modeling. He has eleven refereed journal articles and twelve conference proceedings with 169 citations. Prof. J serves as the program director for all undergraduate programs in the CEOE department and as the instructor for probability and statistics with data science applications, modeling and simulation of environmental systems, introduction to geographic information systems, and regression and stochastic methods. He also acts as a faculty advisor for senior design projects. In the past he also taught geotechnical engineering, statistical methods in sustainability, and groundwater hydrology and pollution.

Institutional Service

  • Ocean Engineering Program Committee Chair
  • Civil Engineering Program Committee Chair
  • Environmental Engineering Program Committee Chair
  • Undergraduate Curriculum Committee Member
  • CEOE Program Assessment Coordinator Chair
  • ESRI License Manager Chair
  • Teaching-Learning Excellence Committee Member
  • Civil Engineering ABET Committee Member
  • Environmental Engineering ABET Committee Chair
  • Naval Engineering ABET Committee Member
  • ABET Working Group Member

Professional Service

  • ABET, AAEES Program Evaluator for Environmental Engineering
  • ASCE Reviewer

Appointments

Teaching Associate Professor and Associate Chair, Undergraduate Studies - CEOE Department

Honors and Awards

ASCE's ExCEEd Graduate
Board Certified Environmental Engineer (Water Supply and Wastewater). AAEES.
Professional Engineer (Civil Engineering, Water and Environmental Engineering Specialty: (NH) 14614.
Institute Best Teaching Assistant, Stevens Institute of Technology, 2009.
The ASCE Student Chapter Award given to the Outstanding Teaching Assistant, 2008.
The ASCE Student Chapter Award given to the Outstanding Teaching Assistant, 2007.
Graduate Aptitude Test in Engineering (GATE) scholarship for Masters in Engineering in India, 2000-2002.

Professional Societies

  • WEF – Water Environment Federation Member
  • AAEES – American Academy of Environmental Engineers and Scientists Member
  • ASCE – American Society of Civil Engineers Member

Selected Publications

Conference Proceeding

  1. Jagupilla, S. C.; Shah, V.; Vaccari, D. (2019). Spatial trends in logistic models and linear relations of pathogen indicators and total suspended solids in a CSO-impacted urban river. WEFTEC 2019 - 92nd Annual Water Environment Federation's Technical Exhibition and Conference (pp. 675-688).

Journal Article

  1. Banerjee, A.; Jagupilla, S.; Pasupuleti, S.; Annavarapu, C. S. (2023). Alternative relationships to enhance the applicability of nonlinear filtration models in porous media. Acta Geophysica (4 ed., vol. 71, pp. 1787-1799).
  2. Liu, T.; Ramirez-Marquez, J.; Jagupilla, S. C.; Prigiobbe, V. N. (2021). Combining a statistical model with machine learning to predict groundwater flooding (or infiltration) into sewer networks. Journal of Hydrology (vol. 603).
  3. Shah, V.; Jagupilla, S. C.; Vaccari, D.; Gebler, D. (2021). Non-linear visualization and importance ratio analysis of multivariate polynomial regression ecological models based on river hydromorphology and water quality. Water (Switzerland) (19 ed., vol. 13).
  4. Ilbeigi, M.; Jagupilla, S.. An Empirical Analysis of Association Between Socioeconomic Factors and Communities' Vulnerability to Natural Disasters. Sustainability (6 ed., vol. 12, pp. 6342). MDPI.
  5. Zhang, F.; Orton, P.; Madajewicz, M.; Jagupilla, S. C.; Bakhtyar, R. (2020). Mortality during Hurricane Sandy: the effects of waterfront flood protection on Staten Island, New York. Natural Hazards (1 ed., vol. 103, pp. 57-85).
  6. Jagupilla, S. C.; Shah, V.; Ramaswamy, V.; Gurumurthy, P.; Vaccari, D. (2020). Prediction of boundary and Stormwater E. Coli concentrations using river flows and baseflow index. Journal of Environmental Engineering (United States) (4 ed., vol. 146).
  7. Zhang, F.; Orton, P.; Madajewicz, M.; Jagupilla, S.; Bakhtyar, R.. Hurricane Sandy Staten Island Flood Conditions and Mortality: Did a Waterfront Berm Protect or Endanger Residents. Journal of Natural Hazards and Earth System Sciences. Gottingen: Copernicus Publications.
  8. Jagupilla, S.; Vaccari, D.; Miskewitz, R.; Su, T.; Hires, R. I. (2015). Symbolic regression of upstream, stormwater, and tributary E. coli concentrations using river flows.. Water environment research : a research publication of the Water Environment Federation (1 ed., vol. 87, pp. 26-34).

Courses

ENGR 241 (Probability and Statistics for Engineers with Data Science Applications)
EN 250 (Quantitative Biology)
EN 580 (Modeling and Simulation of Environmental Systems)
CE 537 (Introduction to Geographic Information Systems)
CE 679 (Regression and Stochastic Methods)