Wei Xie
Assistant Professor
Mechanical and Industrial Engineering
Northeastern University


Research Interests  

Journal Publication

Conference and Other Papers

Presentations

  • Green Simulation Assisted Policy Gradient To Accelerate Stochastic Process Control. INFORMS Annual Meeting, October, 2021
  • Policy Optimization in Bayesian Network Hybrid Models of Biomanufacturing Processes. INFORMS Annual Meeting, October, 2021
  • Probabilistic Knowledge Graph Assisted Reinforcement Learning for Biomanufacturing Process Control. Production and Operations Management Society (POMS) conference, May, 2021
  • Blockchain-Enabled Internet-of-Things Platform for End-to-End Industrial Hemp Supply Chain. Production and Operations Management Society (POMS) conference, May, 2021
  • Optimizing Biomanufacturing Harvesting Decisions under Limited Historical Data. Production and Operations Management Society (POMS) conference, May, 2021
  • Simulation-Based Digital Twin Development for Blockchain Enabled End-to-End Industrial Hemp Supply Chain Risk Management. Winter Simulation Conference, Dec. 2020
  • Green Simulation Assisted Reinforcement Learning with Model Risk for Biomanufacturing Learning and Control. Winter Simulation Conference, Dec. 2020
  • Interpretable AI for End-to-End Biopharmaceutical Production Process Risk Analysis and Facilitation of QbD, ISPE Facilities of the Future Conference, San Francisco, January, 2020. ISPE: International Society for Pharmaceutical Engineering (invited)
  • Simulation-based Blockchain Design to Secure Biopharmaceutical Supply Chain, Winter Simulation Conference, Washington D.C., December, 2019.
  • End-to-End Interpretable Production Process Risk and Sensitivity Analysis for PAT, QbD and Stability Control, NIIMBL Summit Meeting, Washington D.C., October, 2019.
  • A Systematic Risk Analysis and Sensitivity Analysis Framework to Facilitate Biopharmaceutical Production Learning and Stability Improvement, INFORMS Annual Meeting, Seattle, October, 2019.
  • A Simulation-based Decision Framework for Stable, Flexible and Efficient Biomanufacturing Development, INFORMS Annual Meeting, Seattle, October, 2019.
  • Data-Driven Stochastic Optimization for Power Grids Scheduling under High Wind Penetration, Applied Energy Symposium MIT A+B, Boston, May 2019.
  • Data Integrity, Big Data Analytics and Interpretable AI for End-to-End Biomanufacturing Risk Management, 2019 NIIMBL Technology Workshop I - Process Intensification, Boston, April 2019.
  • An Integrated Research, Education and Industry Practice Framework to Accelerate the Innovations in Biopharmaceuticals Manufacturing and Eliminate Drug Shortage, ASEE conference, Niagara Falls, NY, April 2019.
  • Metamodel-Assisted Risk Analysis for Stochastic Simulation with Input Uncertainty, Winter Simulation Conference, Gothenburg, Sweden, December 2018.
  • A Simulation-Based Prediction Framework for Stochastic System Dynamic Risk Management, Winter Simulation Conference, Gothenburg, Sweden, December 2018.
  • A Metamodel-Assisted Framework for Two-Stage Stochastic Programming via Simulation, INFORMS Annual Meeting, Phoenix, November 2018.
  • Distributional Metamodel for Stochastic Simulation Risk Quantification, INFORMS Annual Meeting, Phoenix, November 2018.
  • A Simulation-Based Prediction and Optimization Framework for Bio-pharmaceutical Supply Chain Dynamic Risk Management, Joint Statistical Meeting, Vancouver, July 2018.
  • Data-Driven Stochastic Optimization for Power Grids Scheduling under High Wind Penetration, Technical Conference: Increasing Real-Time and Day-Ahead Market Efficiency and Enhancing Resilience through Improved Software, hosted by Federal Energy Regulatory Commission, Washington D.C., June 2018.
  • A Stochastic Simulation Calibration Framework for Real-Time System Control, 2017 Winter Simulation Conference, Las Vegas, Nevada, December 2017.
  • A Simulation Optimization for Two-Stage Decision Making, 2017 INFORMS Annual Meeting, Houston, Texas, October 2017.
  • A Simulation Calibration Framework for the Production Control, 2017 INFORMS Annual Meeting, Houston, Texas, October 2017.
  • A Stochastic Simulation Calibration Framework for the Production Control, SRC conference, Piscataway, New Jersey, May 2017.
  • A Simulation-Based Prediction Framework for Two-Stage Dynamic Decision Making, Winter Simulation Conference, Washington, D.C., December 2016.
  • Quantification Input Uncertainty for Dependent Input Models with Factor Structure, Winter Simulation Conference, Huntington Beach, CA, December 2015.
  • An Efficient Design of Experiments for Stochastic Simulation: Quantifying Input Uncertainty, INFORMS Annual Meeting, Philadelphia, PA, November 2015.
  • Statistical Uncertainty Quantification for Stochastic Simulation with Dependent Input Models, Albany Chapter of the American Statistical Association , Albany, NY, May 2015.
  • A Bayesian Framework for Statistical Uncertainty Quantification in Stochastic Simulation, CSE Seminar at Rensselaer Polytechnic Institute , Troy, NY, May 2015.
  • Statistical Uncertainty Analysis for Stochastic Simulation with Dependent Input Models, Winter Simulation Conference, Savannah, GA, Dec. 2014.
  • Multivariate Input Uncertainty in Output Analysis for Stochastic Simulation, INFORMS Annual Meeting, San Francisco, Nov. 2014.
  • A Bayesian Framework for Quantifying Uncertainty in Stochastic Simulation, INFORMS Annual Meeting, San Francisco, Nov. 2014.
  • Modeling the effect of engagement and disengagement with mobile apps on customer purchase behavior, Marketing EDGE Professor's Institute, Cincinnati, Jan. 2014.
  • Statistical uncertainty analysis for stochastic simulation, INFORMS Annual Meeting , Minneapolis, Oct. 2013.
  • The influence of correlation functions on stochastic kriging metamodels, Winter Simulation Conference , Baltimore, Dec. 2010.
  • Approximate dynamic programming for serial multi-echelon system with economies of scale, INFORMS Annual Meeting , Washington DC, Oct. 2008.
  • Development of a time-frequency approach to quantify railroad ballast fouling condition using UWB GPR data, Transportation Research Board , Washington D.C., 2008.
  • Scattering analysis of railroad ballast using ground penetrating radar, Transportation Research Board , Washington D.C., 2007.
  • Quantification of Railroad Ballast Condition Using Ground Penetrating Radar Data, 6th International NDE Conference on Civil Engineering , St. Louis, 2006.