Nidhi Simmons is a Lecturer and Royal Academy of Engineering (RAEng) Research Fellow at the Centre for Wireless Innovation (CWI), Queen’s University Belfast (QUB). Her research focuses on delivering ultra-reliable communications within 5G/6G networks using Machine Learning (ML) approaches.

She received her M.Sc. (Distinction) in Wireless Communications and Signal Processing from the University of Bristol, U.K., in 2012. Through funding from the Queen’s University Belfast studentship, she completed her PhD in Electrical Engineering in December 2018. From January 2019 to August 2020, she worked as a Research Fellow at CWI, QUB, where her research focused on wireless channel characterization and modeling.

In 2020, she secured the Royal Academy of Engineering Research Fellowship worth £500k (2020–2026) to pursue her research on devising ML solutions for ultra-reliable communications in future 5G+ networks. In addition, she has been awarded the EPSRC New Investigator Award (2025–2028), building on her recent results to further develop tailored ML solutions to shape the future of ultra-reliable 6G networks, bringing her total secured research funding to ~£900k.

Nidhi has authored several IEEE journal and conference papers and was a recipient of the Best Paper Award at IEEE ANTS in December 2023. She is an IEEE Senior Member and has served as an Organising Committee Member for IEEE ANTS 2024, a Co-Chair of the Recent Results Track at IEEE VTC Fall 2024, and a Technical Programme Committee (TPC) Member for IEEE GLOBECOM 2023 and 2025 (Machine Learning for Communications and Communications Theory tracks). She is an active member of IEEE Women in Engineering and the IEEE Communications Society and serves as a reviewer for several IEEE journals and letters.

Beyond research, Nidhi is deeply committed to mentoring early-career researchers and PhD students. She actively promotes Women in Engineering and STEM, participating in outreach initiatives such as open days, PhD induction events, and keynote talks at the Edinburgh Science Festival (2021) and Women in Tech Belfast (2022). As part of her commitment to diversity and inclusion, she serves as a mentor for the RAEng Graduate Engineering Engagement Programme (2024–2025), supporting engineering students from underrepresented backgrounds in securing employment.

Her research interests include physical-layer security, channel characterization and modeling, ultra-reliable communications, machine-learning for communications and machine learning for ultra-reliable 5G+/6G