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Saguna Saguna
Saguna Saguna

Saguna Saguna

Senior Lecturer
Luleå University of Technology
Pervasive and Mobile Computing
Computer Science
Department of Computer Science, Electrical and Space Engineering
saguna.saguna@ltu.se
+46 (0)910 585385
A108 Skellefteå

Information

Assistant Professor in the Pervasive and Mobile Computing (PMC) research group

Program Coordinator: Master Programme in Information Security

Teaching and Supervision

At LTU, I am involved in teaching and supervsion in a number of courses, see details below:

Master Courses:

  • Applied Computer Security: A7010E, 7.5 credits, Lp 1
  • Internet Security: A7011N, 7.5 credits, Lp 2
  • Data Science Programming: D7054E, 7.5 credits, Lp 3
  • Internet of Things: M7023E, 7.5 credits, Lp 2
  • Cloud Computing: M7024E, 7.5 credits, Lp 2
  • Mobile Networks and Protocols: D7002D, 7.5 credits, Lp 3
  • Networks and Mobility: D0021E, 7.5 credits, Lp 3

These master courses are mainly part of the Master Programme in Computer Science and Engineering with specialization in Distributed Cloud Systems. But, students can also take them individually or part of some other linked programme. 

Undergraduate Courses:

  • Network and Mobility: D0021E, 7.5 credits, Lp 3

Project Course Supervision:

  • Project in Distributed Cloud Systems 1: M7025E, 15 credits, Lp 3-4
  • Project in Distributed Cloud Systems 2: M7026E, 15 credits, Lp 2

Master Thesis Supervision:

  • Master Thesis in Computer Science and Engineering, MSc in Technology: 
    • X7003E, 30 credits, Lp 3-4, Check entry requirements
  • PERCCOM Master Thesis
    • More details can be found at University of Lorraine website here and on Luleå University of Technology website here.

Ph.D. Supervision:

  • Co-supervision of Ph.D. Thesis, if you are enrolled in a Ph.D. program in LTU or another university and are interested to collaborate you can contact me with your proposal. Please note there is no funding currently available from LTU.

Ongoing Ph.D. Co-supervision

  • Zahra Khais Shahid: Activity Recognition using Machine Learning to Detect Anomalies in Elderly Behaviour for Single Resident Smart Homes (Started 2020) - Co-supervisor
  • Aditya Kumar Pathak: Applying Machine Learning to Detect Network Anomalies in IoT Systems (Started 2020) - Co-supervisor
  • Joo Chan Kim: Multimodal Interaction in IoT Systems with a focus on Augmented Reality (Started 2018) - Co-supervisor

Licentiate Supervision

  • Samuel Idowu: Forecasting Heat Load using Applied Machine Learning for Smart District Heating Systems (Completed Licentiate Thesis in 2018) -  - Co-supervisor

Ongoing Master Thesis Students:

  • New students start January 2021

Completed Master Thesis Students with co-supervision:

  • Orsola Fejzo: (Completed)
  • Meruyert Nurgazy: (Completed) 
  • Jeremy Facchetti: (Completed)
  • Adyasha Swain: (Completed)
  • Kubra Saeedi: (Completed)
  • Shabna Siraj: (Completed)
  • Victor Araujo: (Completed)
  • Aigerim Zhalgasbekova: (Completed)
  • Tamara Belyakhina: (Completed)
  • Giang Tran: (Completed)
  • Jean-Paul Bambanza: (Completed)
  • Haidar Chikh: (Completed)
  • Ngo Manh Khoi: (Completed)
  • Rohan Nanda: (Completed)
  • Baptiste Louis: (Completed)

Publications

Conference paper

CAVisAP (2019)

Context-Aware Visualization of Outdoor Air Pollution with IoT Platforms
Nurgazy. M, Zaslavsky. A, Jayaraman. P, Mitra. K, Saguna. S, Kubler. S
Part of: 2019 International Conference on High Performance Computing & Simulation (HPCS), s. 84-91, IEEE, 2019
Conference paper

MyAQI (2019)

Context-aware Outdoor Air Pollution Monitoring System
Schürholz. D, Nurgazy. M, Zaslavsky. A, Jayaraman. P, Kubler. S, Mitra. K, et al.
Part of: IoT 2019, Proceedings of the 9th International Conference on the Internet of Things, Association for Computing Machinery (ACM), 2019, 13
Article in journal

Performance evaluation of FIWARE (2019)

A cloud-based IoT platform for smart cities
Araujo. V, Mitra. K, Saguna. S, Åhlund. C
Journal of Parallel and Distributed Computing, Vol. 132, s. 250-261