Efa Mushtaq

Director of Studies for Master’s Degree Projects in Computer Science

Efa Wafaa A.H. holds a Ph.D. in Computer Science (2008) and a Master’s degree in Computer Systems (2000), both built upon a strong engineering background. She has over 15 years of experience in higher education, where a big part of it was at the University of Science Malaysia (USM), which ranked #37 in the QS Asia University Rankings in  2025, known as a strong collaborator with the Kyushu Institute of Technology in Japan.

Her teaching in English has enabled her to effectively engage with students from diverse backgrounds. She has published several scientific papers, supervised master’s and doctoral students, and coordinated computer science courses. Her academic achievements have been recognized with national innovation awards and a fellowship from the Asia Pacific Advanced Networks in South Korea.

A founding member of the Internet Society Chapter (ISOC) in Malaysia and a key contributor to the National Advanced IPv6 Centre of Excellence (Nav6), she has gained valuable experience working with industry partners on applied research projects.

She began collaborating with KTH in 2021 as an external supervisor, leading master’s research groups, and is currently serving as a lecturer (universitetsadjunkt) and Director of Studies for the Master’s Degree Project in Computer Science at EECS.

Some of her supervisions in multi-disciplinary Master's theses at KTH include:

Georgiou, N. (2023). Using ARM TrustZone for secure resource monitoring of IoT devices running Contiki-NG (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:814. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-342923

Massy, V. (2023). Enhancing privacy in cookieless web advertising: A comparative study of Multi-Party Computation and Trusted Execution Environment solutions for private attribution reporting (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:614. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-337380

Zapata, L. (2023). Recommendation of text properties for short texts with the use of machine learning: A comparative study of state-of-the-art techniques including BERT and GPT-2 (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:203. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-335149

Couturou, T. (2023). UCov: A static analysis tool for API usage coverage validation (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:854. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-343218

Larsson, M. (2023). Customizable contraction hierarchies for mixed fleet vehicle routing: Fast weight customization when not adhering to triangle inequality (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:554. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-333079

Escandón Álvarez, C. (2023). Cell tower localization using crowdsourced measurements (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:590. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-335220

Alevärn, M. (2023). Simplifying software testing in microservice architectures through service dependency graphs (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:552. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-333075

Löv, J. (2023). The impact of demand patterns and pathfinding strategies on payment channel networks (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:551. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-332439

Petersson, J. (2023). Comparative study of the inference of an image quality assessment algorithm: Inference benchmarking of an image quality assessment algorithm hosted on cloud architectures (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:245. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-330743

Tennander, M. (2023). Energy consumption of micro frontends (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:29. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-324038

Forsberg, A. (2023). Can you get consultants to update their CV more often by asking them how they are doing?: A design study on how behavior changing design can impact consultant CV writing (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:7. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-324012

Mellberg, R. (2022). Deep learning for predicting electrical power in 5G (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2022:660. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-321999

Asegehegn, N. T. (2022). Evaluation of Rust and WebAssembly when building a Progressive Web Application: An analysis of performance and memory usage (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2022:199. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-313941

Hovmark, O. (2022). Visualizing issue tracking data using a process mining tool to support the agile maturity assessment within the Scaled Agile Framework: A case study (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2022:533. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-320931

Olander Ålund, S. (2022). Design of an algorithm for edge-node resource orchestration within an Operator Platform (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2022:806. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-321946

Wessman, N. (2022). Improve game performance tracking tools: Heatmap as a tool (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2022:840. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-323522

Manousian, J. (2022). Investigating differences in performance between monolithic and serverless based architectures (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2022:248. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-317043

Diaz, A. (2022). A performance evaluation of concurrent programming with the Swift actor model (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2022:834. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-323492

Williams, S. (2022). Utility library performance compared to native solutions: JavaScript as a case study (Master’s thesis, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology). TRITA-EECS-EX; 2023:210. https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-330724