About me

I am an Assistant Professor at the Institute of Science Tokyo (formerly Tokyo Institute of Technology, Tokyo Tech), School of Computing.
My research focuses on distributed machine learning, including federated learning, graph data processing, and medical data analysis. I study time-series data, missing data imputation, and anomaly detection, with an emphasis on building robust and scalable methods for real-world applications such as IoT systems and healthcare data analytics.
During my studies at Tokyo Tech, I worked in the area of data mining and knowledge discovery, with a particular focus on time-series analysis and sensor data processing in resource-constrained and noisy environments.


For more information, please refer to my CV, and feel free to contact me.

News

  1. Oct. 2024

    Tokyo Institute of Technology (Tokyo Tech) merged with Tokyo Medical and Dental University (TMDU) to form the Institute of Science Tokyo (Science Tokyo) .

  2. Apr. 2023

    Started my new career as an Assistant Professor at Tokyo Tech !

  3. Jan. 2023

    Started my first full-time job as a Researcher at Tokyo Tech.

Daniel lewis
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Resume

Education

  1. Tokyo Institute of Technology

    Apr.2019 — Dec. 2022

    Ph.D in Computer Science
    Belonged to Yokota Laboratory
    Department of Computer Science, School of Computing

  2. Tokyo Institute of Technology

    Apr. 2017 — Mar. 2019

    Master Engineering in Computer Science
    Belonged to Yokota Laboratory
    Department of Computer Science, School of Computing

  3. University of Tunis El Manar

    Sep. 2012 — Jun. 2015

    Engineering Diplome in Computer Science
    Speciality: Software Engineering
    Higher Institute of Computer Science

  4. University of Carthage

    Sep. 2009 — Jun. 2012

    Bachelor Degree in Computer Science
    Speciality: Applied Network Infrastructure and System administration
    National Engineering School of Carthage

Work and Research Experience

  1. Tokyo Institute of Technology

    Mar. 2023 — Present

    Assistant Professor
    Belonging to Kise Laboratory
    Department of Computer Science, School of Computing

  2. Tokyo Institute of Technology

    Jan. 2023 — Mar. 2023

    Researcher
    Topic: Contextual Anomaly Detection and Root Cause Analysis by Fusing Semantic and Data Mining Techniques.

  3. IBM Research - Tokyo

    Aug. 2017 — Sep. 2017

    Paid Intern Student
    Topic: Finding optimization opportunities to improve the execution performance of Hyperledger Fabric on the IBM Z machine.

  4. Tokyo Institute of Technology

    Apr. 2016 — Mar. 2022

    Research Assistant (RA)
    Topic: Contributed to the project “Reliable compromise-resilient mechanisms for managing the data integrity and privacy of heterogeneous IoT devices”, under the Infrastructure Development for Promoting International S&T Cooperation Japan - Taiwan Joint Research Exchange Program. I also took part in one of NEDO (New Energy and Industrial Technology Development Organization) project.

Teaching Experience

  1. Tokyo Institute of Technology

    Apr. 2019 — Mar. 2022

    Teaching Assistant (TA)
    Teaching Assistant for First-year Bachelor's students: Course "Information Literacy I & II" and course "Computer Science I & II" (Conducted In Japanese and English)

Scholarship and Grants-in-Aid

  1. Apr. 2016 - Mar. 2022

    Japan MEXT (Ministry of Education, Culture, Sports, Science and Technology) Scholarship.
    Full support of tuition and living expenses.

  2. Jun. 2021 - Mar. 2023

    New Energy and Industrial Technology Development Organization (NEDO): Next generation framework for real-time data processing.
    Full support of living expenses, travel expenses and research fundings.

  3. Apr. 2016 - Mar.2019

    Grant-in-Aid for Scientific Research of JST (Japan Science and Technology Agency).
    JST-MOST Reliable tamper-resistance with data integrity and privacy detection for heterogeneous IoT devices.
    Full support of travel expenses and research fundings.

Major Honors & Awards

  1. Mar. 2019

    Completed the Master Course with Honors, graduated second on the list and I was elected vice-valedictorian

  2. Apr. 2017

    Won the Best Poster Award in Taiwan-Japan Workshop on “Security and Dependability Technologies for IoT Devices”

  3. Apr. 2016

    Selected candidate for MEXT Scholarship Award

Publications

Domestic Conferences

  1. 2026

    1. 1. Berjab Nesrine "Federated Learning Across Raspberry Pi Generations: Comparative Evaluation of Performance and Power Efficiency" , The 18th Forum on Data Engineering and Information Management (DEIM 2026), Mar. 2026. Link

    2. 2. 多田 亜彩美, Berjab Nesrine, Le Hieu Hanh, 「補完精度と適用可能割合を考慮した電子カルテデータの欠測値補完法の検討」 , The 18th Forum on Data Engineering and Information Management (DEIM 2026), Mar. 2026. Link

    3. 3. 多田 亜彩美, Berjab Nesrine, Le Hieu Hanh, 「電子カルテデータ解析における欠測値補完法の実用性の評価」 , 情報処理学会第88回全国大会論文集, Mar. 2026. Link

  2. 2025

    1. 1. Nesrine Berjab, "Dynamic Trust-Weighted Federated Learning with Gradient-Based Time-Series Anomaly Detection for Robust Model Updates" , The 17th Forum on Data Engineering and Information Management (DEIM 2025), Mar. 2025. Link

    2. 2. Nesrine Berjab, "Semantic-Driven Anomaly Analysis and Root Cause Identification in Heterogeneous Sensor Data" , The 17th Forum on Data Engineering and Information Management (DEIM 2025), Mar. 2025. Link

  3. 2019

    1. 1. Nesrine Berjab, Hieu Hanh Le, and Haruo Yokota, "Fuzzy logic and ECA rules-based misbehaving-node detection for cluster-based heterogeneous IoT systems" , The 11th Forum on Data Engineering and Information Management (DEIM 2019), Mar. 2019. Link

International Journal

  1. 2022

    1. 1. Nesrine Berjab, Hieu Hanh Le, and Haruo Yokota, "Recovering Missing Data via Top-k Repeated Patterns for Fuzzy-based Abnormal Node Detection in Sensor Networks" , IEEE Access, Vol 10, pp. 61046-61064, June 2022. Link

  2. 2021

    1. 2. Nesrine Berjab, Hieu Hanh Le, and Haruo Yokota,"A Spatiotemporal and Multivariate Attribute Correlation Extraction Scheme for Detecting Abnormal Nodes in WSNs", IEEE Access, Vol 9, pp. 135266-135284, Sep. 2021. Link

International Conferences

  1. 2022

    1. 1. Nesrine Berjab, Hieu Hanh Le, and Haruo Yokota, "Trust Assessment Model Based on Hierarchical Decision-making Process in IoT Sensor Networks" , The 18th European Dependable Computing Conference (EDCC 2022), pp. 33-40, Sep. 2022. Link

  2. 2019

    1. 2. Yunfan Li, Nesrine Berjab, Hieu Hanh Le, and Haruo Yokota,"Centralized Trust Scheme for Cluster Routing of Wireless Sensor Networks", The 2019 International Workshop on IoT Big Data and Blockchain (IoTBB’2019) in conjunction with The 2019 IEEE International Conference on Big Data (IEEE Big Data 2019), pp. 5239-5248, Dec. 2019. Link

  3. 2018

    1. 3. Nesrine Berjab, Hieu Hanh Le, and Haruo Yokota,"Hierarchical Abnormal-node Detection using Fuzzy Logic for ECA Rule-based Wireless Sensor Networks", The 23rd IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2018), pp. 289-298, Dec. 2018. Link


    2. 4. Nesrine Berjab, Hieu Hanh Le, Chia-Mu Yu, Sy-Yen Kuo, and Haruo Yokota,"Abnormal-node Detection Based on Spatio-temporal and Multivariate-attribute Correlation in Wireless Sensor Networks", The 16th IEEE International Conference on Dependable, Autonomic and Secure Computing (DASC 2018), pp. 568-575, Aug. 2018. Link

  4. 2017

    1. 5. Nesrine Berjab, Chia-Mu Yu, Sy-Yen Kuo, and Haruo Yokota,"Impact Analysis for DoS and Integrity Attacks on IoT Systems", The 7th IEEE International Conference on Information Systems and Technologies (ICIST 2017), pp. 1-8, Mar. 2017. Link

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