Wei Xie
Assistant Professor
Mechanical and Industrial Engineering
Northeastern University

Research Interests

Journal Publication

Conference Proceedings

Presentations

  • Structure and Function Dynamics Hybrid Modeling: RNA Degradation, Winter Simulation Conference, in San Antonio, Texas. December 10-13, 2023.
  • Stochastic Molecular Reaction Queueing Network Modeling for In Vitro Transcription Process, Winter Simulation Conference, in San Antonio, Texas. December 10-13, 2023.
  • Multi-scale Bioprocess Hybrid Modeling, Mechanism Learning, and Optimization. Statistics and Biostatistics seminar presentation. University of Waterloo, Ontario, Canada. November 15, 2023.
  • Bayesian Knowledge Graph assisted Reinforcement Learning for Biomanufacturing Process Prediction and Optimal Control. Seminar Talk. Texas A&M. College Station, TX. October 19-20, 2023.
  • Reinforcement Learning Based Process Control with Digital Twin Model Calibration. INFORMS Annual Meeting, Phoenix, Arizona, October 15-18, 2023 (presented by my student).
  • Biological System-of-Systems Framework for iPSC Culture in Aggregates. INFORMS Annual Meeting, Phoenix, Arizona, October 15-18, 2023.
  • A Unified Analytical Platform to Accelerate Induced Pluripotent Stem Cells (iPSCs) Manufacturing Process Development and Scale-Up. NIIMBL Project Call 7.1 Summit. Invited poster presentation. Washington D.C., September 13, 2023.
  • Multi-scale Bioprocess Knowledge Graph Hybrid Modeling and Interpretable AI/ML. Seminar talk, NIST Systems Integration Division. Online presentation, August 28, 2023. Onsite visit, September 14, 2023.
  • Challenges and Opportunities for the Innovations on Biomanufacturing Process Modeling, Analysis, and Control. ASME conference IDETC/CIE. Boston, August 20-23, 2023. Scheduled.
  • Experience Replay for Policy Optimization ? Let AI remember and intelligently learn from the past. Seminar Talk. North Carolina State University. April 14, 2023.
  • Induced Pluripotent Stem Cells Culture Modeling and Process Analysis. The fifth annual COE PhD Research Expo. February 27, 2023 (Poster presentation by my student)
  • Modularized PAT Online Training Platform to Accelerate the Workforce Innovation in Biopharmaceuticals Manufacturing. The fifth annual COE PhD Research Expo. February 27, 2023 (Poster presentation by my student)
  • Blockchain-Enabled IoT Platform for End-to-End Supply Chain Risk Management. The fifth annual COE PhD Research Expo. February 27, 2023 (Poster presentation by my student)
  • Green Simulation based Policy Optimization with Partial Historical Trajectory Reuse, Winter Simulation Conference, Singapore, December 11-14, 2022.
  • From Discovery to Production: Challenges and Novel Methodologies for Next Generation Biomanufacturing, Winter Simulation Conference, Singapore, December 11-14, 2022.
  • Sequential Importance Sampling for Hybrid Model Bayesian Inference to Support Bioprocess Mechanism Learning and Robust Control, Winter Simulation Conference, Singapore, December 11-14, 2022.
  • Modularized PAT Online Training Platform to Accelerate Workforce Innovation in Biopharmaceuticals Manufacturing. The NIIMBL Member Forum, October 27, 2022.
  • Green Simulation Assisted Policy Gradient to Accelerate Stochastic Process Control. INFORMS Annual Meeting, October 16-19, 2022. Indianapolis, IN.
  • Blockchain-Enabled IoT Platform for End-to-End Supply Chain Risk Management. INFORMS Annual Meeting, October 16-19, 2022. Indianapolis, IN.
  • Probabilistic Knowledge Graph Hybrid Model-based Reinforcement Learning for Integrated Biomanufacturing Process Policy Optimization. Seminar Talk. Eindhoven University of Technology. October 13, 2022.
  • Variance Reduction based Experience Replay for Policy Optimization. Seminar Talk. George Mason University. September 23, 2022.
  • Hybrid Model-based Reinforcement Learning for Cell Therapy Manufacturing Mechanism Learning and Process Control. Bioprocessing Summit, August 15-18, 2022. Boston (invited presentation)
  • Modularized PAT Online Training Platform to Accelerate the Workforce Innovation in Biopharmaceuticals Manufacturing. The 2022 NIIMBL Annual Meeting, July 26-28, 2022. Washington, D.C.
  • Mixture Importance Sampling Assisted Reinforcement Learning for Process Control with Partial Trajectory Reuse. Production and Operations Management Society (POMS) conference, April 21-25, 2022
  • Knowledge Graph Hybrid Model-based Bayesian Reinforcement Learning for Cell Therapy Manufacturing Process Control. Production and Operations Management Society (POMS) conference, April 21-25, 2022
  • Stochastic Simulation Uncertainty Analysis to Accelerate Modular Biomanufacturing Process Digital Twin Development. Production and Operations Management Society (POMS) conference, April 21-25, 2022
  • 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.