Dr Siva Chandrasekaran

Biography

Siva Chandrasekaran is a Senior Lecturer (Computer and Software Engineering), and Software Engineering Discipline lead, Academic Senate (Elected for the years 2021-2022 and 2023-2024) in the School of Science, Computing, and Engineering Technologies at the Swinburne University of Technology.  Siva has been awarded as a Fellow of the Institution of Engineers Australia (FIE Aust) and he is a Chartered Professional Engineer (CPEng) in the practice area of Information, Telecommunications and Electronics, Project Management, and Systems Engineering. Siva also served as an Academic Director (Curriculum & Quality) for the School of Science, Computing, and Engineering Technologies. He graduated BEng (CSE) in India and an MEng, MEng Sci (Electronics) from Victoria University, and a PhD (Engineering Education) from Deakin University respectively. 

Siva Chandrasekaran has been bestowed as a senior member (SMIEEE) of the Institution of Electrical and Electronics Engineers (IEEE) and also a member of the Australian Computer Society (ACS). Siva is an Associate Editor of the IEEE Education Society IEEE Access Section. He is the lead of the Internet of Things (IoT) Training Academy at Swinburne. Siva has made significant contributions to engineering education research and published more than 140 scholarly articles in national/international peer-reviewed journals and conference proceedings.

Siva Chandrasekaran is an active researcher and his research is in Artificial Intelligence, Machine Learning/Deep Learning, and Industrial IoT. Siva conducts world-class research and fosters cross-disciplinary collaboration and his research is supported by Australian government funding agencies and commercial partners (DFAT, DATA61, CSIRO, Australian Academy of Science, and the Department of Industry, Science, Energy, and Resources) around Australia. His education philosophy is founded on the Project-Oriented Design-Based Learning (PODBL) approach at Deakin University. Siva has facilitated workshops and seminar training on pedagogical approaches in the Asia Pacific educational sectors.

Siva Chandrasekaran led and continued the DFAT Australia-India Council grant project ‘Workshop to Establish India-Australia Internet of Things (IoT) Training Academy’ where academics, Industry representatives, and STEM educators in Australia and India collaborated to strengthen STEM awareness, industry partnerships, and higher education and research. The major industry partners are Siemens Australia, Nexans Olex, Sutton Tools, SAP, Arduino, Pepper + Fuchs, CSIRO, IoTA, Institution of Engineers Australia, DATA61, Brim Bank Council, and Catholic Education Services. https://www.swinburne.edu.au/research/centres-groups-clinics/internet-of-things-training-academy/

Siva Chandrasekaran continues his extensive involvement in collaborative teaching/research activities with Australasian Universities 'Plenary Talk Speaker at Tsinghua University, CHINA; Workshop Facilitator at WUHAN University of Science and Technology, WUHAN, CHINA; Sastra Deemed University & Manipal University, India, Universiti Teknologi Malaysia and the American University of Dubai.

Siva Chandrasekaran led a learning and teaching project 'Empowering Indigenous Australians' knowledge for first-year STEM students to connect People with Technology'. He designed, developed, and implemented the unit ‘Technology in an Indigenous Context Project’ and engages students through a community project that deepens their understanding of the plurality and diversity of Indigenous Australians' knowledge systems, worldviews, standpoints, and culture in relation to STEM technologies. Siva and his team were awarded the 2023 Vice-Chancellor's Reconciliation Award.

1. Doctor of Philosophy – Artificial Intelligence-based Framework for Industrial Asset Management Using Real-Time Series Data
2. Doctor of Philosophy – Stock Price Prediction for Time-Series Data using Hybrid Deep Learning
3. Doctor of Philosophy – Virtual Reality Training for Micro-Robotic Cell Injection 
4. Master by Research – Real-time Control of a Mobile Robot using EEG AND EOG-based Eye Tracking System
5. Master by Research – Machine learning for predictive maintenance of industrial machines using IoT
6. Master by Research – Artificial Intelligence-based Smart Tele-Assisting Technology for Students Using Augmented Reality Smart Glasses 
7. Doctor of Philosophy – Catering for Individual Learning Styles to Improve the Effectiveness of Online Web Delivery of Engineering Education