Enrico Laoh

Enrico Laoh

Roy and Virginia Dorrough Distinguished Graduate Fellow in the Area of Elaborative and Transparent Artificial Intelligence Technology

About Me

Hi, thank you for visiting my online portfolio.
I am Enrico Laoh, welcome to my homepage and please do not hestitate to contact me for more information.

My Expertise

  • Machine Learning and Predictive Modeling
    • Enabling data-driven decision-making across various domains.
    • Harnessing the power of data to make accurate forecasts, identify trends, and automate processes.
    • Extracting valuable insights from data to optimize operations, predict future outcomes, and make informed strategic choices.
  • Unstructured Data Analytics
    • Gathering and preprocessing unstructured data includes text, images, audio, and more.
    • Analyzing and extracting meaning from unstructured data is essential for making informed decisions, understanding customer sentiments, and gaining a competitive edge.
    • Leveraging the information from unstructured data together with traditional database driven model.
  • Blockchain and Distributed Ledger Technology (DLT)
    • Developing secure and immutable record-keeping.
    • Enabling peer-to-peer transactions and reducing the need for intermediaries.
    • Enhancing security, streamline processes, and reduce fraud for the data-sensitive system like finance, supply chain, and healthcare.

Research Interests

My current research interest is to develop explainable artificial intelligence (XAI) frameworks and methodologies to support high-stake decision-making systems. I am especially interested in building interpretable machine learning models, incorporating human capability limitations, and designing human-ai collaborative decision-making systems to improve decision quality and adaptability.

  • Methodology
    Descriptive modeling, predictive modeling, data analytics, text analytics, statistical learning, probabilistic learning, deep learning, bayesian analysis, multivariate analysis, clustering algorithm, classification algorithm, time series analysis, perturbation method, cognitive analytics, and physiological measurement.
  • Applications
    Healthcare system, supply chain system, power system, military system, network configuration, time series prediction, customer relationship management, sentiment modeling, and strategic management.

Education

  • Doctor of Philosophy, Industrial Engineering and Management, Oklahoma State University, Stillwater, United States Expected 05/2025
  • Master of Science, Industrial Engineering and Management, (GPA 4.00/4.00) Oklahoma State University, Stillwater, United States
  • Graduate Certificate, Business Analytics and Data Science, (GPA 4.00/4.00) Oklahoma State University, Stillwater, United States
  • Master of Engineering, Data and Quality Engineering, (GPA 4.00/4.00) University of Indonesia, Depok, Indonesia
  • Bachelor of Engineering, Industrial Engineering, (GPA 3.88/4.00) University of Indonesia, Depok, Indonesia

Special Thanks

I wish to extend my profound gratitude to the esteemed institutions that have generously provided funding for my research endeavors
University of Indonesia Kemenristekdikti OSU NIH NSF