Arthur is currently a PhD student in Electrical Engineering at University of Melbourne. He holds a Bachelor of Engineering (Research and Development) with First Class Honours from the Australian National University (ANU). His research interests are optical communication, optoelectronic/ photonic devices and related decision intelligence. He has particular interest in photonic solutions to AI infrastructure. He is also an active secondary market investor with enthusiasm for the financial markets.
Feel free to contact via email: arthur.zhao@student.unimelb.edu.au.
News
Jul 25: I have officially enrolled and started my PhD journey at University of Melbourne.
Apr 25: I have received the Master offers from Cornell University (ECE), Rice University (MSNE with fellowship), and University of Michigan (ECE) for Fall 2025!
Feb 25: I have received the PhD offer with univeristy’s scholarship from University of Melbourne, commencing in S2 2025.
Research Experiences
Nano-Electro-Mechanical System (NEMS) Lab, ANU
[1] Design, simulation and fabrication of qBIC metasurface in telecom-band (Ongoing)
[2] Fabrication of 2D heterostructures with precise twist angle alignment
Department of Material Science and Engineering, Monash University
[3] Correlative in-situ EBSD and DIC dataset with explainable machine learning for mechanical stability analysis of iron alloy
- Granted Monash Summer Research Scholarship
ANU-Optus Bushfire Research Centre of Excellence
[4] Bushfire detection using environmental monitoring sensing and deep anomaly detection approach.
- Accepted by ANU Student Research Conference and selected for poster highlight and oral presentation. [Certificate]
[5] Transferring bushfire gas wireless sensor networks (WSN) systems to volcano monitoring
Honors & Awards
- Melbourne Research Scholarship, University of Melbourne, starting from 07/2025
- Monash Summer Vacation Research Scholarship, Monash University, 11/2024
- HEX Singapore Summer Program Scholarship, ANU School of Computing, 09/2023
Educations
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Bachelor of Engineering (Research and Development) (Honours), Australian National Univerisity, Canberra, Australia, 02/2022 - 06/2025,
Major: Electronic and Communication Systems
Minor: Computer Science
WAM: 83 (H1, First Class Honours)
GPA: US Equivalent (WES/Scholaro): 3.97/4
Highlight: Academic Highlights: Electronic Systems and Design (98), Signals and Systems (96), Information Theory (96), Introduction to Electronics/ Mechanics (Both 95), Digital Communication/ Mathematics 2 (94), Mechanical System (91), Digital Systems& Microprocesscors (88), Computer Systems & Organisation (87), Wireless Communication (86),
Teaching & Services
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07/2023 - 06/2025, Academic Tutor, School of Engineering, Australian National Univerisity, Canberra, Australia.
Academic tutor for 3 consecutive years:
ENGN2218: Electronic Systems and Design (2024, 2025)
- Get fully trained for TA position through ANU EXPLORING LEARNING AND TEACHING program. [Certificate]
- Course Representative for 12 courses across all semesters.
- Mentor of official SET4ANU program.
- Career Director of Australia-China Youth Association (ACYA), ANU for 2025
Experiences
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02/2024 - 07/2025, Undergraduate Research Student, NEMS Lab, Australian National Univerisity, Canberra, Australia.
Supervisor: Prof. Yuerui Lu
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11/2024 - 02/2025, Summer Research Student, Faculty of Engineering, Monash University, Melbourne, Australia.
Supervisor: Dr. Yuxiang Wu and Prof. Michael Preuss
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06/2024 - 07/2024, Study Australia Industry Experience Program, Australian Government, Remote. [Certificate]
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11/2023 - 02/2024, Network Department Internship, China Mobile Group Jiangsu Co. LTD Nanjing Branch, Nanjing, China.
Experience accredited by ANU Engineering degree Practical Experience requirement.
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02/2023 - 11/2023, Undergraduate Research Student, ANU-Optus Bushfire Research Centre of Excellence, Australian National Univerisity, Canberra, Australia.
Supervisor: Prof. Xiangyun Zhou and Prof. Salman Durrani
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05/2023 - 07/2023, Summer Workshop, School of Computing, National University of Singapore, Singapore [Certificate]
Track: Deep learning and robotics