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Amin Jalali

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Associate Professor

Stockholm University

Sweden

Research Interests

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About

Amin Jalali is an Associate Professor at Stockholms Universitet, Sweden. His research areas include complex information systems, process mining, and user acceptance of modeling languages. He has contributed to various recent articles focusing on practical applications in information systems, signal classification using adversarial learning, and process variant analysis through Markov models.

Recent Grants

Grant: Close

AI-Enhanced Enterprise Business Processes Analysis

Open Date: 2025-01-01

Close Date:

Grant: Close

Data-driven solutions in complex care processes (DISAL)

Open Date: 2022-01-01

Close Date: 2024-12-01

Grant: Close

Digital innovation in collaboration between city, region and academy (DISRA)

Open Date: 2021-08-01

Close Date: 2023-07-01

Grant: Close

Process Mining for Janusmed: Towards safer drug prescription

Open Date: 2018-01-01

Close Date: 2020-01-01

Articles (16)

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2027

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2026

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2026

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2026

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2026

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2026

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2025

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2025

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2024

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2024

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2023

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2022

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2021

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2021

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2021

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2021

Collaborators (2)

Jelena Zdravkovic

Professor, Department of Computer and Systems Sciences, Stockholm University

Stockholm University

SWEDEN

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Thashmee Karunaratne

Associate Professor

KTH Royal Institute of Technology

SWEDEN

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Amin Jalali

Research Interests

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About

Recent Grants

Articles (16)

AI-Decision Checkpoints for AI-Augmented Business Process Management: Framework and Educational Instantiation

An object-centric approach to multi-entity Educational Process Mining

Advancing object-centric process mining with multi-dimensional data operations

An empirical study on the effectiveness of decision trees and decision tables for source-based decision validation

DMN-Guided Prompting: A Framework for Controlling LLM Behavior

Discovering Object-Centric Causal Nets with Edge-Coarse-Graining in Process Mining

WHAT, WHY, AND HOW OF DATAFICATION IN EDUCATION – A SCOPING REVIEW

Discovering Object-Centric Causal Nets with Edge Abstraction

Editorial Introduction to Issue 41 of CSIMQ: Practical Applications and Methods to Manage Complex Information Systems

Motor Imagery Signal Classification Using Adversarial Learning: A Systematic Literature Review

Evaluating user acceptance of knowledge-intensive business process modeling languages

Object Type Clustering Using Markov Directly-Follow Multigraph in Object-Centric Process Mining

dfgcompare: a library to support process variant analysis through Markov models

dfgcompare: a library to support process variant analysis through Markov models

Evaluating Perceived Usefulness and Ease of Use of CMMN and DCR

Graph-Based Process Mining

Collaborators (2)

Jelena Zdravkovic

Thashmee Karunaratne

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