Shadi Abpeikar

Dr. Shadi Abpeikar is a Research Fellow at the School of Engineering and Technology, University of New South Wales (UNSW) Canberra. She holds a PhD in Computer Science from AmirKabir University of Technology (2019) and a Master's in Computer Science (2013), with her Bachelor's degree in Applied Mathematics from Iran University of Science and Technology (2011).

• Education: PhD Computer Science (2019), MSc Computer Science (2013), BSc Applied Mathematics (2011)

Her research focuses on machine learning, swarm robotics, and swarm intelligence algorithms, with applications in collective motion tuning, intelligent transportation systems, and decision support systems. Recent work explores deep reinforcement learning for swarming skills and deep learning/CFD integration for battery safety.

Key trends in her publications include transfer learning for robotic platforms, collective motion recognition via neural networks, and swarm coverage problems in unknown environments. Notable grants include $45,000 for Li-ion battery fire risk mitigation (2024) and $68,645 for heterogeneous robot swarms (2023).

• Scientific Awards: IEEE TenSYMP Best Paper (2023), AFHEA Fellowship (2021), highest bachelor's score (2011), best master's thesis (2013)

She supervises PhD students Mahtab Mohtasham Khani, Ryan Locke, and Hadha Afrisal. Professional activities include IEEE ACT Young Professional Committee (2023), Publicity Chair for ACRA 2023, and leadership roles in YoWIE and ECAN.