Rafia Inam
I am a researcher and passionate to transfer research results to business. Currently working as:
Head of Trustworthy AI |Senior Research Manager, at Ericsson AB (Nov 2021 - todate)
Adjunct Professor, at KTH Royal Institute of Technology (May 2022 - todate)
Senior Project Manager at Ericsson AB (Feb 2019 - Oct 2021)
Senior Researcher at Ericsson AB (Nov 2017 - Feb 2019).
Experienced Researcher at Ericsson AB (Jan 2015 - Nov 2017)
Short bio:
Rafia Inam Rafia Inam is a senior research manager at Ericsson Research and Adjunct Professor at KTH in research area Trustworthy Artificial Intelligence, Sweden. She has conducted research for Ericsson since 2015 on 5G for industries, 5G network slices and management, using AI for automation, service modeling for Intelligent Transport Systems. She is specialized in automation and safety for CPS and collaborative robots, trustworthy AI, explainable AI, explainable RL, risk assessment and mitigations using AI methods, reusability of real-time software. She won Ericsson Top Performance Competition 2021 on her work on AI for 5G network slice assurance, and was awarded Ericsson Key Impact Award 2020, and Key contributor award 2020.
Rafia received her Ph.D. from Mälardalen University, Sweden, in 2014 on predictable real-time embedded software. She is a Program Committee member, referee, guest editor for several international conferences and journals. Rafia has co-authored 40+ refereed scientific publications and 55+ patent families. She has won best paper awards on her two papers: “Towards automated service-oriented lifecycle management for 5G networks”, at the IEEE’s 9th International Workshop on Service Oriented Cyber-Physical Systems in Converging Networked Environments (SOCNE) in 2015, and “Support for Hierarchical Scheduling in FreeRTOS” in 16th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA’11), September 2011.
My areas of Interest are:
Trustworthy AI
Explainable AI, Explainable RL
Automation, safety and Trustworthy AI for Collaborative robots using Machine Learning and AI algorithms
5G Management for industries specially automotive, and smart manufacturing
Real-time embedded systems.
Hierarchical scheduling for unicore and multicore platforms.
Intelligent Transport Systems.
Education
Ph.D. Computer Science and Engineering, 2014, Mälardalen University, Västerås, Sweden.
Licentiate. Computer Science and Engineering, 2012, Mälardalen University, Västerås, Sweden.
Masters. Networks and Distributed Systems, 2010, Chalmers University of Technology, Gothenburg, Sweden.