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  1. Ansatte

Språkvelger

English

Mirza Muntasir Nishat

Last ned pressefoto
Last ned pressefoto
Foto:

Mirza Muntasir Nishat

Stipendiat
Fakultet for ingeniørvitenskap

mirza.m.nishat@ntnu.no
Verkstedteknisk, Gløshaugen, Richard Birkelands vei 2B
ResearchGate Scopus Google Scholar
Om Forskning Publikasjoner Formidling

Om

Forskningen min omfatter systemteknikk med integrering av maskinlæring og kunstig intelligens, som fokuserer på å utvikle digitale tvillinger og datadrevne, avgjørende verktøy for prediktiv analyse.

Kompetanseord

  • dataanalyse
  • datadrevet system
  • digitalisering
  • kunstig intelligens
  • modellering og simulering
  • systemteknikk

Forskning

Project Data Analysis and Database Development  

Structured DiSCO Database for AI based Safety Automation

This study aims to provide experiences of a pilot database development to discuss the opportunities for automation of safety in construction.

Neural Network based Risk Assessment Prototype with Human-in-the-loop approach

The proof-of-concept we present here shows that it is possible to capitalize on expert knowledge in a dynamic and user-friendly way.

Predictive Analysis with ML in Project based data

This study provides a foundation for developing integrated ML models and project management software, fostering data-driven decision-making in dynamic project scenarios.

Publikasjoner

  • Kronologisk
  • Etter kategori
  • Alle publikasjoner i Nasjonalt vitenarkiv (NVA)

2026

  • Nishat, Mirza Muntasir; Rauzy, Antoine Bertrand; Olsson, Nils Olof Emanuel. (2026) A Contribution to Digital Prediction of Safety Performance in the Construction Industry. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling
  • Nishat, Mirza Muntasir; Nervik, Peder Solem; Olsson, Nils Olof Emanuel; Andersen, Bjørn Sørskot; Rauzy, Antoine Bertrand. (2026) A semantically structured relational database for construction safety analysis. Construction Innovation
    Vitenskapelig artikkel
  • Nishat, Mirza Muntasir; Olai, Aarvold, Magnus; Jan, Hartvig, Wilhelm; Olsson, Nils Olof Emanuel. (2026) Investigating the Applicability of Long Short-Term Memory (LSTM) Algorithm in Project Decision-Making: A Case Study in ML-Driven Forecasting | SpringerLink.
    Vitenskapelig kapittel

2025

  • Nishat, Mirza Muntasir; Rauzy, Antoine Bertrand; Olsson, Nils Olof Emanuel. (2025) A Prototype Risk Assessment Dashboard for the Construction Industry: Getting Experts in the Loop Thanks to Machine Learning. Safety
    Vitenskapelig artikkel
  • Nishat, Mirza Muntasir; Ahsan, Aneeq; Olsson, Nils Olof Emanuel. (2025) APPLYING MACHINE LEARNING FOR PREDICTIVE ANALYSIS IN PROJECT-BASED DATA: INSIGHTS INTO VARIATION ORDERS. Electronic journal of information technologies in construction
    Vitenskapelig artikkel

2024

  • Nishat, Mirza Muntasir; Naraas, Sander Magnussen; Marsov, Andrei; Olsson, Nils Olof Emanuel. (2024) Prediction of project activity delays caused by variation orders: a machine-learning approach. IOP Conference Series: Earth and Environmental Science (EES)
    Vitenskapelig artikkel
  • Nishat, Mirza Muntasir; Borkenhagen, Ingrid Renolen; Olsen, Jenni Sveen; Rauzy, Antoine Bertrand. (2024) Investigating on Combining System Dynamics and Machine Learning for Predicting Safety Performance in Construction Projects. IOP Conference Series: Earth and Environmental Science (EES)
    Vitenskapelig artikkel

Tidsskriftspublikasjoner

  • Nishat, Mirza Muntasir; Nervik, Peder Solem; Olsson, Nils Olof Emanuel; Andersen, Bjørn Sørskot; Rauzy, Antoine Bertrand. (2026) A semantically structured relational database for construction safety analysis. Construction Innovation
    Vitenskapelig artikkel
  • Nishat, Mirza Muntasir; Rauzy, Antoine Bertrand; Olsson, Nils Olof Emanuel. (2025) A Prototype Risk Assessment Dashboard for the Construction Industry: Getting Experts in the Loop Thanks to Machine Learning. Safety
    Vitenskapelig artikkel
  • Nishat, Mirza Muntasir; Naraas, Sander Magnussen; Marsov, Andrei; Olsson, Nils Olof Emanuel. (2024) Prediction of project activity delays caused by variation orders: a machine-learning approach. IOP Conference Series: Earth and Environmental Science (EES)
    Vitenskapelig artikkel
  • Nishat, Mirza Muntasir; Borkenhagen, Ingrid Renolen; Olsen, Jenni Sveen; Rauzy, Antoine Bertrand. (2024) Investigating on Combining System Dynamics and Machine Learning for Predicting Safety Performance in Construction Projects. IOP Conference Series: Earth and Environmental Science (EES)
    Vitenskapelig artikkel
  • Nishat, Mirza Muntasir; Ahsan, Aneeq; Olsson, Nils Olof Emanuel. (2025) APPLYING MACHINE LEARNING FOR PREDICTIVE ANALYSIS IN PROJECT-BASED DATA: INSIGHTS INTO VARIATION ORDERS. Electronic journal of information technologies in construction
    Vitenskapelig artikkel

Del av bok/rapport

  • Nishat, Mirza Muntasir; Olai, Aarvold, Magnus; Jan, Hartvig, Wilhelm; Olsson, Nils Olof Emanuel. (2026) Investigating the Applicability of Long Short-Term Memory (LSTM) Algorithm in Project Decision-Making: A Case Study in ML-Driven Forecasting | SpringerLink.
    Vitenskapelig kapittel

Studentoppgave eller avhandling

  • Nishat, Mirza Muntasir; Rauzy, Antoine Bertrand; Olsson, Nils Olof Emanuel. (2026) A Contribution to Digital Prediction of Safety Performance in the Construction Industry. Norges teknisk-naturvitenskapelige universitet
    Doktoravhandling

Formidling

Dynamic Safety and Risk Assessment of Tunnel Construction: Leveraging Systems Engineering through Sigma Modeling

Dynamic Safety and Risk Assessment of Tunnel Construction: Leveraging Systems Engineering through Sigma Modeling

Investigating the Applicability of Long Short-Term Memory (LSTM) Algorithm in Project Decision-Making: A Case Study in ML-Driven Forecasting

This study investigates how machine learning algorithms like the Long Short-Term Memory (LSTM) can analyze project progress data and assist in strategic decision-making.

Investigating on Combining System Dynamics and Machine Learning for Predicting Safety Performance in Construction Projects

This study focuses on an investigative approach to combine system dynamics and machine learning algorithms to develop an early warning system for the safety management of construction projects.

Prediction of project activity delays caused by variation orders: a machine-learning approach

This study is a pilot study to investigate how data from large project databases can be used for an ML analysis.

Artificial Intelligence in Construction Safety: A Decade of Progress, Challenges, and Future Implications

This review has highlighted a significant transformation regarding machine learning (ML) and deep learning (DL) applications in construction safety, a move from retrospective statistical analyses to active and contextualized decision support systems.

2024

  • Konferanseforedrag
    Nishat, Mirza Muntasir; Ahsan, Aneeq; Olsson, Nils Olof Emanuel. (2024) Machine Learning Enabled Predictive Analysis on Project Based Data – Applications on Variation Orders. IRNOP
  • Konferanseforedrag
    Nishat, Mirza Muntasir; Neraas, Sander Magnussen; Marsov, Andrei; Olsson, Nils Olof Emanuel. (2024) Prediction of project activity delays caused by variation orders: a machine learning approach. CREON 2024 The 12th Nordic Conference on Construction Economics and Organisation

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