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Maziyar Khadivi

4 papers hereh-index 5235 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.AI1

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedDeep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

49 citations · 53 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2025

An Innovative Data-Driven and Adaptive Reinforcement Learning Approach for Context-Aware Prescriptive Process Monitoring

Mostafa Abbasi, Maziyar Khadivi, Maryam Ahang +3

The application of artificial intelligence and machine learning in business process management has advanced significantly, however, the full potential of these technologies remains…

cs.LG2024★ 3 cited

Intelligent Condition Monitoring of Industrial Plants: An Overview of Methodologies and Uncertainty Management Strategies

Maryam Ahang, Todd Charter, Mostafa Abbasi +3

Condition monitoring is essential for ensuring the safety, reliability, and efficiency of modern industrial systems. With the increasing complexity of industrial processes, artific…

cs.LG2023★ 49 cited

Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

Maziyar Khadivi, Todd Charter, Marjan Yaghoubi +4

Machine scheduling aims to optimize job assignments to machines while adhering to manufacturing rules and job specifications. This optimization leads to reduced operational costs,…

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