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Computational Intelligence and Operations Lab - CIOL

Empowering smarter decisions through computational intelligence.

Computational Intelligence and Operations Lab (CIOL)


Artificial Intelligence and Machine Learning play a crucial role in Industrial and Production Engineering, particularly in optimizing processes, enhancing efficiency, enabling predictive maintenance, and more. Our curriculum lacks sufficient emphasis on AI/ML, which is vital to address this gap and ensure that students acquire the necessary skills to meet both industry and academic demands, contributing to the growth of the country.

Computational Intelligence and Operations Lab (CIOL) is founded by MD Shafiqul Islam and Azmine Toushik Wasi to accelerate IPE-AI combinational research at SUST-IPE, filling up the current gap of ML-focused research in the department. It is a virtual research facility focusing on the development and application of advanced artificial intelligence, machine learning, and computational techniques for solving complex problems in various domains such as manufacturing, operations research, supply chain management, logistics, and transportation. The lab's research aims to push the boundaries of AI, ML, optimization, and data analytics to create innovative solutions addressing real-world challenges faced by businesses and society.

With a team of highly dedicated researchers and youngsters, CIOL is committed to advancing the field of computational intelligence and developing tools and technologies that enable smarter decision-making and more efficient operations using a combination of OR, ML, and AI.


We recently showcased our success at two NeurIPS'23 workshops and a AAAI'24 Workshop. Additionally, we are currently awaiting review for several works in different venues like ICLR'24 Tiny Papers and HI Workshop @AAAI'24. See our publications page for more details and updates page for recent updates.


Headquarters: Sylhet, Bangladesh
Founded: 2022
Research Area: Operations Research, Machine Learning, and Artificial Intelligence

Popular repositories Loading

  1. SupplyGraph SupplyGraph Public

    A Benchmark Dataset for Supply Chain Planning using Graph Neural Networks

    Jupyter Notebook 25 8

  2. ciol-researchlab.github.io ciol-researchlab.github.io Public

    HTML 1

  3. .github .github Public

  4. SCG SCG Public

    SCG dataset from "Graph Neural Networks in Supply Chain Optimization: Concepts, Perspectives, Dataset and Benchmarks"

  5. UKIL UKIL Public

    Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language Modeling

    Jupyter Notebook

  6. Dhoroni Dhoroni Public

    Data and Code of 'Dhoroni: Exploring Bengali Climate Change and Environmental Views with a Multi-Perspective News Dataset and Natural Language Processing'

    Python

Repositories

Showing 6 of 6 repositories
  • ciol-researchlab/ciol-researchlab.github.io’s past year of commit activity
    HTML 1 BSD-3-Clause 0 0 0 Updated Oct 23, 2024
  • Dhoroni Public

    Data and Code of 'Dhoroni: Exploring Bengali Climate Change and Environmental Views with a Multi-Perspective News Dataset and Natural Language Processing'

    ciol-researchlab/Dhoroni’s past year of commit activity
    Python 0 MIT 0 0 0 Updated Oct 23, 2024
  • UKIL Public

    Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language Modeling

    ciol-researchlab/UKIL’s past year of commit activity
    Jupyter Notebook 0 Apache-2.0 0 0 0 Updated Oct 23, 2024
  • SupplyGraph Public

    A Benchmark Dataset for Supply Chain Planning using Graph Neural Networks

    ciol-researchlab/SupplyGraph’s past year of commit activity
    Jupyter Notebook 25 LGPL-2.1 8 0 0 Updated Oct 16, 2024
  • SCG Public

    SCG dataset from "Graph Neural Networks in Supply Chain Optimization: Concepts, Perspectives, Dataset and Benchmarks"

    ciol-researchlab/SCG’s past year of commit activity
    0 LGPL-2.1 0 0 0 Updated Oct 16, 2024
  • .github Public
    ciol-researchlab/.github’s past year of commit activity
    0 0 0 0 Updated Sep 10, 2024

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