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Bakhtawar Saeed

Bakhtawar Saeed

Lecturer
  • Department Of Computer Engineering
  • bakhtawar.saeed@nu.edu.pk
  • (041) 111-128-128
  • Ext: 301

Introduction

I am a dedicated and skilled Computer Engineering professional with a strong foundation in software development, cybersecurity, and digital transformation. I completed my B.Sc. and MS in Computer Engineering from the University of Engineering and Technology (UET) Taxila, where I also served as a research scholar at the Deep Packet Inspection (DPI) Lab. At GHQ, I worked as an ERP Expert from August 2023 to August 2024, utilizing Oracle APEX along with SQL and PL/SQL to design and implement digital solutions for Organization. My work involved developing user-friendly interfaces, integrating databases, and streamlining documentation processes to support digitization. Currently, I am working as a Lecturer at FAST-NUCES, Chiniot-Faisalabad Campus, where I am committed to fostering innovation, technical growth, and academic excellence among students.


Research Interests:

  • Machine learning and its applications 
  • Federated learning and privacy-preserving machine learning
  • Internet of Things (IoT) security and attack detection
  • Deep learning for network traffic analysis and anomaly detection
  • Generative models (e.g., GANs) for handling data imbalance
  • Data analytics, preprocessing, and visualization using Python

Education

  • M.Sc (Computer Engineering) UET Taxila 2024
  • B. Sc (Computer Engineering) UET Taxila 2021

Publications

1. B. Saeed, S. Arshad, S. M. U. Saeed, M. A. Azam, A. Akram, and S. Gul,
“Intelligent Internet of Things Attack Detection: Novel Approaches and Technologies,”
in Proc. 2023 International Conference on IT and Industrial Technologies (ICIT), Oct. 2023, pp. 1–6. IEEE.

2. B. Saeed, S. Arshad, S. M. U. Saeed, and M. A. Azam,
“Enhancing IoT Security: Federated Learning with GANs for Effective Attack Detection,”
in Proc. 2023 20th International Bhurban Conference on Applied Sciences and Technology (IBCAST), Aug. 2023, pp. 570–575. IEEE.

3. S. Gul, S. Arshad, S. M. U. Saeed, A. Akram, B. Saeed, and M. A. Azam,
“Improving Botnet Detection with a Generative Adversarial Network-Based Technique,”
in Proc. 2023 20th International Bhurban Conference on Applied Sciences and Technology (IBCAST), Aug. 2023, pp. 564–569. IEEE.

Collaborations at National and International Level

Detail of Funded Projects