Diplomas/Degrees
Diplomas/Degrees
Ph.D., Stanford University (2008)
Professional Experience
Professional Experience
9/2018 - Present: Assistant Professor in the Department of Decision Sciences and Marketing in the School of Business, Adelphi University, Garden City, NY
9/2013 - 8/2018: Assistant Professor in the School of Management and Marketing at the College of Business and Public Management, Kean University, Union, NJ
8/2008 - 8/2013: Assistant Professor in the Industrial Engineering Department at the College of Engineering, University of Miami, Coral Gables, FL
Recent Courses
Recent Courses
Optimization And Prescriptive Models
Procurement And Global Sourcing
Specialization/Interests
Specialization/Interests
Operations Management
Supply Chain Management
Business Analytics
Research Interests
Research Interests
Simulation-Based Decision Making for Operations and Supply Chain Management
Nonparametric Function Estimation under Shape Constraints
Chapters
Chapters
P. W. Glynn and E. Lim. 2009. Asymptotic Validity of Batch Means Steady-State Confidence Intervals. Advancing the Frontiers of Simulation: A Festschrift in Honor of George Samuel Fishman (International Series in Operations Research & Management Science) Springer, New York. 87-104.
Articles
Articles
E. Lim. 2024. Estimating a Function and Its Derivatives Under a Smoothness Condition. Mathematics of Operations Research. Published in Articles in Advance. https://doi.org/10.1287/moor.2020.0161
E. Lim and P. W. Glynn. 2022. Simulation-based Prediction. Operations Research. 71(1):47-60. https://doi.org/10.1287/opre.2021.2229
E. Lim. 2021c. Simulation-based Optimization for Convex Functions over Discrete Sets. International Journal of Statistics and Probability. 10(5): 31-37.
E. Lim. 2021b. Estimation of Unknown Parameters Using Partially Observed Data. Journal of Modelling in Management. 16 (2): 651–667.
E. Lim. 2021a. Consistency of Penalized Convex Regression. International Journal of Statistics and Probability. 10 (1): 69-78.
E. Lim and K. Kim. 2020. Estimating Smooth and Convex Functions. International Journal of Statistics and Probability. 9 (5): 40-48.
E. Lim. 2020. The Limiting Behavior of Isotonic and Convex Regression Estimators When The Model Is Misspecified. Electronic Journal of Statistics. 14 (1): 2053-2097. https://doi.org/10.1214/20-EJS1714
E. Lim, J. Choi, and Y. Kim. 2018. A Theoretically Sound Approach to Sizing Analog Circuits. Journal of Semiconductor Technology and Science. 18 (2): 200-210.
E. Lim. and F. Tavarez. 2017. Nonparametic Tests for Convexity/Monotonicity/Positivity of Multivariate Functions with Noisy Observations. International Journal of Statistics and Probability. 6 (5): 18-28.
E. Lim and F. Gonzalez. 2017. Estimation of Multivariate Smooth Functions via Convex Programs. International Journal of Statistics and Probability. 6 (3):1-8.
E. Lim and M. Attallah. 2016. Estimation of Smooth Functions via Convex Programs. International Journal of Statistics and Probability. 5 (4): 150-155.
Y. Luo and E. Lim. 2016. On Consistency of Least Absolute Deviations Estimators of Convex Functions. International Journal of Statistics and Probability. 5 (2):1-18.
E. Lim. 2014. On Convergence Rate of Convex Regression in Multiple Dimensions. INFORMS Journal on Computing. 26 616-628.
Y. Luo and E. Lim. 2013. Simulation-based Optimization over Discrete Sets with Noisy Constraints. IIE Transactions. 45 699-715.
E. Lim. 2012. Stochastic Approximation over Multi-dimensional Discrete Sets with Applications to Inventory Systems and Admission Control of Queueing Netwotks. ACM Transactions on Modeling and Computer Simulation. 22 19:1-19:23.
E. Lim and P. W. Glynn. 2012. Consistency of Multi-dmentional Convex Regression. Operations Research. 60 196-208.
E. Lim. 2011. On the Convergence Rate for Stochastic Approximation in the Nonsmoothing Setting. Mathematics of Operations Research. 36 527-537.
Conference Presentations
Conference Presentations
E. Lim. 2023. Simulation-based Prediction. INFORMS Annual Meeting, October 2023.
E. Lim. 2023. The Limiting Behavior of Isotonic and Convex Regression Estimators When the Model is Misspecified. INFORMS APS Conference, June 2023.
E. Lim. 2021. Simulation-based Optimization for Convex Functions over Discrete Sets. INFORMS Annual Meeting, October 2021.
E. Lim. 2020. The Limiting Behavior of Isotonic and Convex Regression Estimators When the Model
is Misspecified. Virtual INFORMS Annual Meeting, November 2020.
E. Lim. 2019. Nonparametric Tests for Convexity, Monotonicity, or Positivity of Multivariate Functions With Noisy Observations. INFORMS Annual Meeting, Seattle, November 2019.
E. Lim, Y. Kim, and J. Choi. 2015. Optimization of Analog Circuits via Simulation and a Lagrangian-type Gradient-based Method. In Proceedings of the 2015 Winter Simulation Conference. 1206-1217.
E. Lim and Y. Luo. 2014. On a Least Absolute Deviations Estimator of a Convex Fuction. In Proceedings of the 2014 Winter Simulation Conference. 2682-2691.
P. W. Glynn and E. Lim. 2011. Brownian Bridge Hypothesis Testing for the Initial Transient Problem. In Proceedings of the 2011 Winter Simulation Conference. 481-487.
Y. Luo and E. Lim. 2011. Simulation-based Optimization over Discrete Sets with Noisy Constraints. In Proceedings of the 2011 Winter Simulation Conference. 4013-4025.
E. Lim. 2010. Response Surface Computation in the Presence of Convexity. In Proceedings of the 2010 Winter Simulation Conference. 1246-1254.
E. Lim and Y. Luo. 2010. Statistical Techniques for the Initial Transient Problem in Steady-State Simulations. In Proceedings of the 2010 International Conference on Engineering and Meta-Engineering.
E. Lim. 2009. Newton-Raphson Version of Stochastic Approximation over Discrete Sets. In Proceedings of the 2009 Winter Simulation Conference. 613-622.
E. Lim and P. W. Glynn. 2006. Simulation-based Response Surface Computation in the Presence of Monotonicity. In Proceedings of the 2006 Winter Simulation Conference. 264-271.
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