Dr Sham Puthiya Parambath
- Research Associate (School of Computing Science)
Biography
I, Shameem Ahamed Puthiya Parambath, am a member of the Knowledge & Data Engineering Systems (KDES) under the research group Information, Data and Analysis (IDA) in the School of Computing Science, University of Glasgow, working with Dr Christos Anagnostopoulos and Prof. Roderick Murray-Smith.
I hail from the small, picturesque coastal town of Thalassery in the state of Kerala, India, where I have spent the majority of my life. My home is situated next to the splendid Government Brennen College in Dharmadom, near a river. I cherish the memories of the two remarkable years I spent at Brennen College.
I completed PhD in Machine Learning from the University of Technology Compiegne (Sorbonne University Association) France. Throughout this academic journey, I had the privilege of being mentored by Dr. Nicolas Usunier and Dr. Yves Grandvalet. During my Masters at Umea University, I had the opportunity to collaborate with Dr. Sihem Amer-Yahia.
Prior to joining the University of Glasgow, I served as a Postdoctoral Researcher at the Qatar Computing Research Institute, Doha, Qatar. In my current role, I focus on enhancing sequential algorithms for various applications such as dynamic pricing, federated learning, and edge computing. At QCRI,I specialized in Recommender Systems, Knowledge Graphs, and Anomaly Detection. Notably, my research on group recommendation and cold-start recommendation received recognition through publications in AAAI and ECML conferences. Furthermore, my work on quantifying bias in knowledge graphs was published in UAI. During my doctoral studies, my research revolved around multi-objective learning algorithms for multi-class/multi-label classification and personalized recommendations, with publications in prestigious venues. such as NeurIPS and RecSys.
Research interests
- Learning with feedback
- Mutli-Armed Bandits
- Recommender Systems
- Federated Learning
Google Scholar: [link]
Supervision
- Alfahad, Saleh Abdullah M
Engineering Edge Computing with Predictive Intelligence - Wang, Qiyuan
Resource-aware & Adaptive Novelty Detection in Edge Computing Environments
Teaching
Database Theory & Applications
Additional information
Reviewer for AAAI 2024, 2021, 2020, 2019; AISTATS 2023, 2022; CIKM 2020; SDM 2020