Dr. Sajal Halder is a Research Fellow at RMIT University, Australia, where he works on AI-generated content analysis and misinformation detection on social media.
From February 2024 to August 2025, he served as a Research Fellow at Data61, CSIRO, Australia, where he contributed to a Google-funded project on software vulnerability standardization in critical infrastructures. Prior to that, he was a Postdoctoral Research Fellow at Charles Sturt University, Wagga Wagga, NSW (December 2022 – February 2024), focusing on adversarially robust machine learning for software supply chain security.
Earlier, Dr. Halder held research and applied data science roles, including Lead Developer/Data Scientist at Acciona (2022), Research Worker at CQ University (2022), and Research Assistant at RMIT University and Acciona GeoTeach. He completed his PhD in Computer Science at RMIT University in 2022, with a thesis on itinerary recommendation using deep learning.
Dr. Halder also has extensive academic experience in Bangladesh, where he served as a faculty member (Lecturer/Assistant Professor) in the Department of Computer Science and Engineering at Jagannath University from July 2016 to July 2018. Before that, he held faculty positions at Bangabandhu Sheikh Mujibur Rahman Science and Technology University (October 2013 – July 2016) and Dhaka International University (2011). Earlier in his career, he worked as a software developer at Neighbor System Ltd, South Korea (2011–2013).
He earned his Master of Engineering in Computer Engineering (Data Mining) from Kyung Hee University, South Korea (2013), and a B.Sc. (Hons.) in Computer Science and Engineering from the University of Dhaka, Bangladesh (2010).
Dr. Halder’s research interests span misinformation detection in social media, supply chain security, machine learning, deep learning, reinforcement learning, personalized itinerary recommendation systems, attrition analysis, and large-scale data analysis. He has published 35+ research articles in various prestigious journals and conferences, including Applied Soft Computing, Data Mining and Knowledge Discovery, Knowledge and Information Systems, Expert Systems with Applications, Multimedia Tools and Applications, Cybersecurity, and The Computer Journal. He has also presented at top-tier conferences, including The Web Conference (A*), ESORICS (A), and PAKDD (A).
In addition to his research contributions, Dr. Halder actively serves as a reviewer for high-impact journals such as Engineering Applications of Artificial Intelligence, Information Processing and Management, Applied Soft Computing, IEEE Transactions on Computational Social Systems, Transactions on Knowledge Discovery from Data, Expert Systems with Applications, IEEE Access, and World Wide Web.
Course Tutor / Lab Instructor (In Australia):
Algorithms and Analysis (Semester 1, 2019 and Semester 2, 2019), Software Engineering (Semester 2, 2019) \\
Course Teacher (in Bangladesh):
Computer Fundamentals, Discrete Mathematics, Programming with C / C++, Digital System,
Design and Analysis of Algorithms, Data Mining and Warehouse, Machine Learning, Big Data Analytics, Advanced Data Mining and Machine Learning
Artificial Intelligence in Cybersecurity; Large Language Models (LLMs) for Vulnerability and Threat Detection; Adversarial Machine Learning; Software Supply Chain Security; Generative and Explainable AI; Misinformation Detection and Analysis. Personalized Recommendation Systems using Machine Learning and Reinforcement Learning.
RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.
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