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. Despite being widely recognized as an essential part of IPE education worldwide, the curriculum of the Industrial and Production Engineering department of Shahjalal University of Science and Technology (SUST-IPE) lacks sufficient emphasis on AI/ML. It 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.

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

• SupplyGraph: A Benchmark Dataset for Supply Chain Planning using Graph Neural Networks
  • Authors: Azmine Toushik Wasi, MD Shafikul Islam Sohan, Adipto Raihan Akib
  • Venue: AAAI'24 Graphs and more Complex structures for Learning and Reasoning Workshop (Full Paper)
  • Status: Accepted
  • Topics: GNN, Supply Chains, Datasets and Benchmarks
  • GitHub

• Optimizing Inventory Routing: A Decision-Focused Learning Approach using Neural Networks
  • Authors: MD Shafikul Islam Sohan, Azmine Toushik Wasi
  • Venue: NeurIPS'23 New in ML Workshop (Extended Abstracts)
  • Status: Accepted
  • Topics: CO, OR-ML, Supply Chains
  • Paper Site, arXiv, OpenReview

• Explainable Identification of Hate Speech towards Islam using Graph Neural Networks
  • Author: Azmine Toushik Wasi
  • Venue: NeurIPS'23 Muslims in ML Workshop (Extended Abstracts)
  • Status: Accepted, Oral
  • Topics: GNN, XAI
  • arXiv, OpenReview

Last Updated on: 16 December 2023