Md Tariqul Islam
tariqsaj [at] dca.fee.unicamp.br| mtarislam [at] gmail.com
I am currently enrolled in the PhD program under the supervision of Prof. Dr. Christian Esteve Rothenberg in the Department of Computer Engineering and Industrial Automation (DCA), School of Electrical and Computer Engineering (FEEC) at the University of Campinas (UNICAMP), Brazil. I am also part of the INTRIG as a graduate research assistant.
I received MSc in Computer Engineering from FEEC/UNICAMP, Brazil, in 2021 and BSc in Information and Communication Technology from Mawlana Bhashani Science and Technology University, Bangladesh, in 2018.
My current research interest is centered around enhancing network performance and Quality of Experience (QoE) for emerging eXtended reality (XR) services by incorporating 5G and Beyond networks, Edge Computing, OpenRAN architecture, and Machine Learning (ML) techniques. I am currently exploring 360-VR streaming use cases, investigating ML-based network-level measurement correlation and analysis with user QoE, and the feasibility of such correlation and analysis in the OpenRAN architecture or dataplane context. I am also interested in offloading XR computational tasks to network edge to optimize XR performance. My past work includes predicting traditional DASH video QoE metrics at the network edge using ML models for performance optimization.
- Machine Learning-Assisted Closed-Control Loops for Automated Healing in Multi-Domain Zero-Touch Networks. Nathan Saraiva, Md Tariqul Islam, Raza Ul Mustafa, Danny Lachos Perez, Christian Esteve Rothenberg, Pedro Henrique Gomes. In Journal of Network and Systems Management, 2022. [PDF]
- Predicting XR Services QoE with ML: Insights from In-band Encrypted QoS Features in 360-VR. Md Tariqul Islam, Christian Esteve Rothenberg, Pedro Henrique Gomes. To Appear In NetSoft, Technical Session, 2023. [PDF]
- EFFECTOR: DASH QoE and QoS Evaluation Framework For EnCrypTed videO tRaffic. Raza Ul Mustafa, Md Tariqul Islam, Christian Esteve Rothenberg, Pedro Henrique Gomes. To Appear In NOMS, Technical Session, 2023. [PDF]
- DASH QoE Performance Evaluation Framework with 5G Datasets. Raza Ul Mustafa, Md Tariqul Islam, Christian Esteve Rothenberg, Simone Ferlin, Darijo Raca, Jason J. Quinlan. In CNSM, Workshop, 2020. [PDF] [Video] [GitHub]
- HAS Based Empirical QoE Study over TCP and QUIC on Diverse Networks. Md Tariqul Islam, Christian Esteve Rothenberg. In VII Pre-IETF, Workshop, 2020. [Slides] [Video]
- Intent-based Control Loop for DASH Video Service Assurance using ML-based Edge QoE Estimation. Christian Esteve Rothenberg, Danny Lachos Perez, Nathan Saraiva, Raphael Rosa, Raza Ul Mustafa, Md Tariqul Islam Pedro Henrique Gomes. In NetSoft, Demo Session, 2020. [PDF] [Video]
- QoE Estimation by Virtual Probe at Edge Computing Facilities. Md Tariqul Islam, Christian Esteve Rothenberg. In XII EADCA Poster Session, 2019.
- MSc: A predictive DASH QoE approach based on machine learning at multi-access edge computing: Uma abordagem preditiva de DASH QoE baseada em aprendizado de máquina em multi-access edge computing. Md Tariqul Islam. 1 recurso online (108 p.) Dissertação (mestrado) – Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação, Campinas, SP. Disponível em: https://hdl.handle.net/20.500.12733/1641360, Acesso em: 10 nov. 2022.