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Biography Md Zia Ullah is a Lecturer in the School of Computing, Engineering & Built Environments at Edinburgh Napier University. He received his PhD degrees in the Department of Computer Science and Engineering from the Toyohashi University of Technology, Japan in 2016. His PhD thesis focused on Bipartite Graph based Ranking Models and its Application to Information Retrieval and Bioinformatics.

After his PhD, he was appointed as a Post-doctoral researcher at Universite Toulouse - Paul Sabatier, CNRS, and Universite de Toulouse - Jean Jaures, Toulouse, France from 2017 to 2022 where he worked in Information retrieval, Natural language processing, and Applied machine learning (Deep learning). During his Post-doc, he also worked on the EU H2020 Project PREVISION on Machine learning applications and lectured Data analytics at the Université Toulouse I Capitole, France.

He also received his B.Sc. (Hons.) degree from the University of Chittagong, Bangladesh in 2010 and his M.Eng. degree from the Toyohashi University of Technology in 2013.


His research interests lie primarily in
- Information retrieval (IR),
- Natural language Processing (NLP),
- Applied machine learning (ML), and
- Deep learning

His research has focused on
- Adaptive information retrieval,
- Query performance prediction (QPP),
- Search Intent mining and diversification,
- Check-worthiness prediction,
- Statistical analysis of IR parameters, and
- Deep learning-based histopathological image recognition.


He has co-patented an adaptive IR technique and published his research outcomes in the international journals and conferences, including

* ACM Transactions on Information Systems (TOIS),
* ACM Transactions on Intelligent Systems and Technology (TIST),
* ACM Special Interest Group on Information Retrieval (SIGIR),
* ACM Conference on Information and Knowledge Management (CIKM),
* European Conference on Information Retrieval (ECIR), and
* IEEE Engineering in Medicine and Biology Society (EMBS).

He actively participated in evaluation forums such as TREC, CLEF, and NTCIR for obtaining the benchmark datasets, evaluating his research ideas, and comparing with the related methods.


He is actively involved as a Program committee (PC) member for the following international conferences:

* ACM Special Interest Group on Information Retrieval (SIGIR), (2018~),
* ACM Conference on Information and Knowledge Management (CIKM), (2019~),
* ACM International Conference on Web Search and Data Mining (WSDM), (2020~),
* ACM Special Interest Group on Knowledge Discovery in Data (SIGKDD), (2020~),
* European Conference on Information Retrieval (ECIR), (2019~),
* European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), (2022~),
* Conference and Labs of the Evaluation Forum (CLEF), (2017~).


* False webs: Network to address the misinformation pandemic (2023 -- 2025), Royal Society Edinburgh, Co-PI

PAST PROJECTS (Involved as a researcher)

* PREVISION (EU Horizon 2020), 2019 -- 2021, 28 Partners, 9.4M)
* FabSpace 2.0 (EU Horizon 2020), 2015 --2018, 7 Partners, 3.4M)
Research Interests Information Retrieval (IR)
Natural Language Processing (NLP)
Machine Learning
Deep Learning
Teaching and Learning Advanced Machine Learning, Module leader (ML), 2023~
Machine Learning for Conversational AI, 2023~
Data Wrangling, 2022~
Data Wrangling - GA, ML, 2022~
Scripting for Data Science, ML, 2022~
Data Processing and Management, ML, 2022~
arXiv ID zuacubd
PhD Supervision Availability Yes
PhD Topics -- Query Performance Prediction for Sparse and Dense Retrieval Models
-- Response Estimation for Conversational Search using Query Performance Prediction
-- Retrieval-enhanced Large Language Models
-- False Web: Network to Address Misinformation Pandem