Michael Bidollahkhani

E-mailmichael.bkhani@uni-goettingen.de

Biography

Michael Bidollahkhani, under the supervision of Prof. Dr. Julian Martin Kunkel, is a dedicated computer engineer and machine intelligence researcher. His expertise in software engineering and automated systems is recognized by his Young Scientist award from the YSF of Iran in 2017 and 2023. As a member of the National Elites Foundation and the ACM, Michael is actively engaged in the development of advanced intelligent systems.
ORCID: 0000-0001-8122-4441
Google Scholar: https://scholar.google.com/citations?user=_rLezLYAAAAJ

Research Interests

  • Complex Systems
  • Computational Intelligence
  • Cognitive Modeling
  • Neural Information Processing
  • Neuroinformatics
  • Emergent Intelligence
  • Artificial Neural Networks
  • Cognitive Robotics

Projects

Advisory roles

  • 2024, Track chair, The Eighteenth International Conference on Advanced Engineering Computing and Applications in Sciences; AISys, ICSEA, CENTRIC tracks

Journal review duties

  • 2023, The American Journal of Artificial Intelligence (AJAI)
  • 2020, IEEE Signal Processing Society

Teaching

Summer Term 2025

Autumn Term 2024

Open Thesis Topics

AI-Driven Anomaly Detection in Compute Continuum SystemsApply

This thesis focuses on developing advanced AI techniques for anomaly detection in Compute Continuum systems. By leveraging state-of-the-art machine learning models, the research will explore effective methods for identifying anomalies in diverse environments, ranging from edge devices to HPC clusters. The work includes creating datasets, designing algorithms, and implementing prototypes to validate the models' efficiency in real-world scenarios.

Michael Bidollahkhani AIAnomaly Detection

Edge AI for Real-Time Predictive Maintenance in Distributed SystemsApply

Edge computing is revolutionizing real-time predictive maintenance by processing data locally, minimizing latency, and enhancing system reliability. This thesis aims to design an edge AI-based framework for predictive maintenance in distributed systems. The student will develop and test a real-time solution to detect and predict potential failures using sensor data and logs from edge devices, ensuring robust and efficient operations.

Michael Bidollahkhani Edge AIPredictive Maintenance

Scalability Challenges in AI-Enhanced Workload Scheduling for HPC SystemsApply

This research addresses the scalability challenges associated with implementing AI-driven workload scheduling in HPC systems. By analyzing bottlenecks and proposing innovative solutions, the thesis will contribute to optimizing workload distribution for large-scale computing environments. The student will explore and test novel approaches for enhancing the scalability and performance of scheduling algorithms tailored to HPC systems.

Michael Bidollahkhani AIHPCWorkload Scheduling

Theses

  • Implementation of a Liquid Neural Network Control System for Multi-Join Cyber Physical ARM, Michael Bidollahkhani (Master's Thesis), Advisors: Ferhat Atasoy, Abdellatef Hamdan, 2023-06, BibTeX
  • Extract and mining government services, especially USO and their impacts on the development of rural communities using data mining algorithms and artificial intelligence, Michael Bidollahkhani (Bachelor's Thesis), Advisors: I. Soleimani, A. Shahbahrami, 2016, BibTeX

Publications

2024

  • Poster: Predictive Maintenance in Server Farms with Time Series Analysis (Michael Bidollahkhani, Julian Kunkel), 2nd NHRConference 2024 at NHR4CES@TUDarmstadt, Darmstadt, Germany, 2024-09-09 BibTeX URL PDF
  • HOSHMAND: Accelerated AI-Driven Scheduler Emulating Conventional Task Distribution Techniques for Cloud Workloads (Michael Bidollahkhani, Aasish Kumar Sharma, Julian Kunkel), IEEE Computers, Software, and Applications Conference, pp. 1-8, IEEE, IEEE, COMPSAC 2024, 2024-07 BibTeX
  • Distracted AI: Integrating Neuroscience-Inspired Attention and Distraction Learning in ANN (Michael Bidollahkhani, M. Raahemi, P. Haskul), 2024 20th CSI International Symposium on Artificial Intelligence and Signal Processing, pp. 1-8, IEEE, IEEE, AISP, 2024-02 BibTeX DOI
  • Comparing Fault-tolerance in Kubernetes and Slurm in HPC Infrastructure (Mirac Aydin, Michael Bidollahkhani, Julian Kunkel), Proceedings of the 18th International Conference on Advanced Computing (ADVCOMP 2024), pp. 40-49, Venice, Italy, ISSN: 2308-4499. ISBN: 978-1-68558-184-8, 2024 BibTeX URL
  • Revolutionizing system reliability: The role of AI in predictive maintenance strategies (Michael Bidollahkhani, Julian Kunkel), IARIA CloudComputing 2024 Conference, pp. 1-9, Venice, Italy, ISSN: 2308-4294. ISBN: 978-1-68558-156-5, 2024 BibTeX URL

2023

  • LTC-SE: Expanding the Potential of Liquid Time-Constant Neural Networks for Scalable AI and Embedded Systems (Michael Bidollahkhani, Ferhat Atasoy, Hamdan Abdellatef), In arXiv preprint arXiv:2304.08691, 2023-04-18 BibTeX
  • A Novel Approach for Muscle Fatigue Disorders Detection Using EMG Based Time-Constant Neural Networks (Michael Bidollahkhani, F. Atasoy), In Gazi Journal of Engineering Sciences (2), 2023 BibTeX URL
  • LoRaline: A Critical Message Passing Line of Communication for Anomaly Mapping in IoV Systems (Michael Bidollahkhani, O. Dakkak, A. S. M. Alajeeli, B. S. Kim), In IEEE Access (11), pp. 18107-18120, 2023 BibTeX
  • Real-Time Building Management System Visual Anomaly Detection Using Heat Points Motion Analysis Machine Learning Algorithm (Michael Bidollahkhani, Isa Avci), In Tehnički vjesnik (30), pp. 318–323, 2023 BibTeX
  • Liquid Time-Constant Neural Networks (Michael Bidollahkhani), In Interdisciplinary Artificial Intelligence, Series: Nobel Scientific Works, Edition: 1, pp. 163 (Turkey), 2023 BibTeX URL

2018

  • The Neural Connection Spot (Michael Bidollahkhani, S. Darbarpanah), The International Conference on New Horizons in the Engineering Science, Istanbul, Turkey, 2018 BibTeX
  • The RPAT Algorithm for Politician Assessment and Evaluation (Michael Bidollahkhani, F. Bidollahkhani), The International Conference on New Horizons in the Engineering Science, Istanbul, Turkey, 2018 BibTeX

2017

  • Parallel programming Application on Medical Image Processing: MRI contours matching algorithm based on GPU accelerated methods for Tumor differential Analysis (Michael Bidollahkhani), International Congress on Science and Engineering, Hamburg, Germany, 2017 BibTeX
  • Subjects Extraction and text data classification by CHERNOFF algorithm and implementation with Java general-purpose computer programming language (Michael Bidollahkhani, M. F. Masouleh), IEEE Second National and First International Conference on Soft Computing, IEEE, IEEE, Guilan, Iran, 2017 BibTeX

2015

  • Optimization of Artificial Retina implant's vision (Michael Bidollahkhani, S. Darbarpanah), International Conference on Science and Engineering of Istanbul Technical University (ITU), Istanbul Technical University, Istanbul, Iran, 2015 BibTeX

2014

  • A Survey on Different Strategies on Preparing Data for Data Mining (Michael Bidollahkhani, M. F. Masouleh), ISC National conference on Soft computing at Guilan technical university, Guilan technical university, Guilan, Iran, 2014 BibTeX

All publications as BibTex