Dr. Mohammad Saiedur Rahaman
PhDLecturer - Information & Communications Technology
School of Engineering and Technology
Centre for Intelligent Systems
Dr. Saiedur Rahaman's research sits in the cross-cutting areas of data science (analytics, machine learning and deep learning), intelligent sensing (mobile, wearables, IoT), and human-centred computing. His work has been applied to different industry verticals and pervasive environments, including classrooms, smart cities, transport, renewable energy, health & wellbeing, and assistive technologies. He has published in top-tier outlets, including IoT Journal, Information Sciences, TIST, IJHCS, Pervasive and Mobile Computing, Neurocomputing, IMWUT/UbiComp, Percom, and CIKM. He has served as a PC member of premier data science and AI conferences, including IJCAI, Percom, KDD, WSDM, CIKM and as program co-chair of IEEE PerAwareCity'20.
He is the winner of IMWUT/Ubicomp 'Distinguished Paper Award-2021' (A*), as well as RMIT's 'ROSE-2019 teaching award', 'Teaching and Learning Incentive Grant 2019' and 'Certificate of Outstanding Teaching-2017'. He is a DAAD AINet fellow, has a rich history of multi-disciplinary collaboration with Microsoft USA, Arup, Mornington Peninsula Shire, Northern Health, Memko, Sutton Tools and the Victorian state government. He has a track record of securing nationally competitive grants as a CI and named research fellow, notably contributing to grant successes such as C4NET and VHESIF. As part of these successful high-impact projects, he not only generated new knowledge but also led the development and delivered system prototypes for industry partners, underscoring his academic excellence, leadership, and practical proficiency in achieving real-world project goals.
Background
Dr. Saiedur Rahaman earned his PhD in Computer Science from the School of Computing Technologies at RMIT University, Australia, supported by an ARC linkage grant. Following this, he served as a level-B research fellow at the Data Science discipline within RMIT's School of Computing Technologies. His research primarily centered on developing technologies for sensing and connecting the physical world, and employing machine/deep learning techniques for analyzing multi-modal time-series data in pervasive environments. He has successfully supervised PhD students to completion and currently involved in research supervision in the field of Data Science and AI. As a recognized ICT educator, he taught data science and AI at RMIT and University of Adelaide before joining CQUniversity. Additionally, he held a lecturer (assistant professor) position at the School of Computer Science, AIUB, Bangladesh, before moving to Australia.
Universities Studied At
- PhD in Computer Science, RMIT University, Australia
- MSc in Computer Science, AIUB, Bangladesh
- BSc in Computer Science & Engineering, AIUB, Bangladesh
Universities Worked At
- RMIT University, Australia
- University of Adelaide, Australia
- AIUB, Bangladesh
Awards
- AInet fellowship, DAAD Germany 2022-2023
- Distinguished paper award, Proc. of the ACM IMWUT/ Ubicomp (A*), 2021
- Recognition of outstanding student experience (ROSE) teaching award, RMIT University, Australia, 2019
- Learning and Teaching Incentive grant, School of Science, RMIT University, 2019
- Second runner-up, Smart Cities Tech Competition, City of Melbourne, 2020
- Publication grant award, School of Science, RMIT University, Australia, 2018
- Certificate of recognition for outstanding teaching score, RMIT University, Australia, 2017
- Outstanding student award -Leadership and Communication, ATN-LEAP, QUT, 2015.
- First place, National networking skills competition 2009, CISCO.
- Second runner-up, Asia-Pacific Netriders 2009, CISCO.
- Summa Cum Laude academic excellence award in graduate class, AIUB, 2009.
- Summa Cum Laude academic excellence award in undergraduate class, AIUB, 2007
Media Citations
Previous teaching
- Practical data science
- Social media and network analytics
- Case studies in data science
- AI and data science professional
- Human and ethical factors in computer science
- Introduction to programming
- Data mining and knowledge discovery
- Algorithms and analysis
- Theory of computation
- Concrete mathematics
- User-centred design
- Professional computing practice
Professional Experience
- Program Co-chair: IEEE PerAwareCity 2020, March 23–27, Austin, Texas, USA
- TPC Member: KDD’22, BuildSys'22, IJCAI'19, CIKM'22, IEEE Percom’20-21 (industry track), WSDM’22, SmartComp’19-20 (industry track), DATA’19, AusDM'18-'20, TI@WSDM'19, IEEE PerAwareCity’19-20
- Reviewer: Elsevier JNCA, Elsevier PMC, VLDB Journal, IEEE IoT Journal, IEEE Systems Journal, Springer Cognitive Computation, WSDM, IJCAI, AusDM, SMARTCOMP, IEEE PerCom, ACM IMWUT
Professional Memberships
- Member, Australian Computer society (ACS)
- Member, IEEE
- Member, ACM
Industry Reports
M.S. Rahaman, F.D. Salim, M. Hamilton, A. Bouguettaya, X. Li, X. Yu, et.al, Integrated Smart Airport Services: An Industry White Paper, Arup, December 2018.
Accreditation
I am currently accredited for supervision in the following:
- 4602 Artificial intelligence
- 4605 Data management and data science
- 4608 Human-centred computing
- 4611 Machine learning
At the level of Principal Supervisor
Current Capacity
Data management and data science - Data mining and knowledge discovery
Data management and data science - Information extraction and fusion
Data management and data science - Stream and sensor data
Human-centred computing - Pervasive computing
Machine learning - Deep learning
