Melike Erol-Kantarci

Also known as Melike Erol-Kantarcı, Mel Erol-Kantarci

Melike Erol-Kantarci is a computer scientist at the University of Ottawa who applies machine learning to the design of 5G and 6G wireless networks. Raised in Istanbul, she earned three computer engineering degrees at Istanbul Technical University, finishing with a PhD in 2009, and taught at Clarkson University before returning to Ottawa in 2016. In 2018, she began bringing AI and machine learning into her wireless research, and in 2019 she received a Tier 2 Canada Research Chair in AI-enabled next-generation wireless networks. Her work uses deep reinforcement learning to train the algorithms inside digital twins of 5G and 6G networks, and she was named an IEEE Fellow in 2025. Today she is a full professor at uOttawa and Strategic Product Manager for AI in RAN at Ericsson.

Now at: University of Ottawa, Vector Institute and Ericsson
Works: 335
Citations: 8,784
h-index: 48

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

By 2009

Computer engineering in Istanbul

She grows up in Istanbul and, in her second undergraduate year, finds her subject in a discrete mathematics course. At Istanbul Technical University, she earns a bachelor's degree in computer engineering in 2001, a master's in 2004 and a PhD in 2009 under Sema Oktuğ, including a year as a visiting student at UCLA with Mario Gerla.
2014–2016

Assistant professor at Clarkson

After postdoctoral research at the University of Ottawa, she becomes an assistant professor at Clarkson University in 2014.
2016–2018

Machine learning back in Ottawa

She returns to the University of Ottawa as an assistant professor in 2016. From 2018, she brings AI and machine learning techniques into her research on wireless networks.
2019–2020

A Canada Research Chair

In 2019, she gains tenure as an associate professor and receives a Tier 2 Canada Research Chair in Artificial Intelligence-Enabled, Next-Generation Wireless Networks, which is renewed in 2024. In June 2020, uOttawa announces the chair, which supports her work applying machine learning to resource allocation in 5G networks and designing 6G algorithms.
2020

Digital twins and reinforcement learning

In 2020, she becomes a Vector Institute Faculty Affiliate, is named an IEEE Communications Society Distinguished Lecturer, and receives the TCGCC Distinguished Service Award for the second time. She builds digital twin 5G and 6G networks from real network data and uses deep reinforcement learning to train the algorithms that route and schedule traffic at wireless base stations.
2022–2024

Data scientist at Ericsson

She joins Ericsson in 2022 as Chief Cloud RAN AI/ML Data Scientist, and the University of Ottawa promotes her to full professor in 2023. In April 2024, she gives the fourth lecture in McMaster University's ECE Distinguished Research Lecture Series, “Paving the AI-native way in B5G and 6G”.
2025

IEEE Fellow and WICE award

She is named to the 2025 class of IEEE Fellows for contributions to AI-enabled wireless networks and smart grid communications. She also receives the 2025 IEEE Women in Communications Engineering (WICE) Outstanding Achievement Award, which recognizes her research on AI-enabled wireless networks and her leadership in emerging 6G technologies.
As of October 2026

Professor and Ericsson product manager

In 2024, she becomes Strategic Product Manager for AI in RAN at Ericsson, a role she holds alongside her full professorship and Tier 2 Canada Research Chair at the University of Ottawa. She is the founding director of the Networked Systems and Communications Research (NETCORE) laboratory and a Faculty Affiliate at the Vector Institute. In May 2026, she moderates a session at the 6G Global Summit in Ottawa.

Career

Since 2022EricssonChief Cloud RAN AI/ML Data Scientist, Strategic Product Manager for AI in RAN
Since 2020Vector InstituteFaculty Affiliate
Since 2016University of OttawaAssistant professor, Full professor
2014–2016Clarkson UniversityAssistant professor
University of California, Los AngelesVisiting student