Evidence-bundle retrieval
Retrieving answer-ready bundles that combine text, visual, and structured signals.
Related publicationResearch program
Auditable multimodal AI for evidence-rich retrieval.
My research connects cross-modal information retrieval, evaluation discipline, and applied AI systems for domains where evidence quality matters as much as model performance.
Research spine
01
Cross-modal retrieval that keeps text, image, and structured evidence inspectable.
02
Evaluation gates that make progress measurable instead of anecdotal.
03
Healthcare and industrial AI contexts where trust, coverage, and auditability matter.
04
A thesis-to-publication path that connects early clustering work to current multimodal systems.
11research outputs
3thesis milestones
9research relationships
G0-G7evaluation discipline
Research focus
A compact map of the questions behind the work.
The page now separates broad interests from concrete research areas, so readers can quickly understand both the intellectual territory and the active problems.
Research interests
Multimodal retrievalCross-modal alignmentEvaluation and benchmarkingHealthcare AIKnowledge graphsInformation retrievalNatural language processing
Tri-modal alignment objectives
Studying how text, image, and tabular representations can be aligned for reliable retrieval.
Related publicationCoverage-aware evaluation
Making evaluation sensitive to missing evidence, weak coverage, and uneven modality support.
Direction-wise reporting
Separating retrieval directions so strengths and failures are visible instead of averaged away.
Semantic clustering
Using lexical and conceptual signals to improve textual document organization.
Related publicationScalable clustering
Earlier work on modified K-Means methods for large-scale data clustering.
Related publicationThesis lineage
From semantic clustering to tri-modal retrieval.
The research story becomes stronger when the doctorate, master's thesis, and early clustering work are shown as a progression of questions.
Bridging Modalities: Effective Information Retrieval from Cross-modal Data
This doctoral thesis addresses the 'Modal Gap' in information retrieval by introducing a tri-modal pipeline that aligns text, image, and structured data. The research focuses on establishing alignment prerequisites and reporting protocols to enable robust retrieval performance in high-stakes domains.
- Institution
- SIT-NVIDIA Joint AI Center (SNAIC)
- Supervision
- Dr. Daniel Wang Zhengkui, Associate Professor, Dr. Aik Beng Ng, Associate Professor, Prof. Dr. Simon See
- Contribution
- Developing a tri-modal pipeline for encounter bundles. Establishing a comprehensive reporting protocol for evaluation.
Accuracy of Textual Document Clustering with Semantic Approach
Investigated the enhancement of document clustering accuracy by integrating semantic knowledge from WordNet with standard statistical methods. The study focused on addressing the limitations of keyword-based clustering by incorporating conceptual relationships.
- Institution
- Al-Madinah International University
- Supervision
- Dr. Wael M. S. Yafooz, Professor
- Contribution
- Integrated WordNet synsets and lemmatization into the clustering pipeline to capture semantic meaning. Utilized COBWEB conceptual clustering for hierarchical organization of documents.
A Modified K-Means Algorithm for Big Data Clustering
Proposed an optimized K-Means algorithm capable of handling large-scale datasets more efficiently by reducing redundant calculations during the centroid update process.
- Institution
- IBAIS University
- Supervision
- Dr. Md. Mahbub Alam, Associate Professor
- Contribution
- Improved initial centroid selection to speed up convergence. Introduced interval-based 'feasible points' computation to drastically reduce recalculation steps during iterations.
Research network
Supervision, collaboration, and service in one place.
A stronger academic page should make the people and institutions around the work visible without overwhelming the reader.
Supervisors
Prof. Dr. Simon See
Industry Supervisor | Collaborator
Professor (Adjunct) - Macquarie University, University of Surrey; Chief Solution Architect; Global Head, NVIDIA AI Technology Center, NVIDIA Corporation
Prof. Dr. Simon See is the Global Head of the NVIDIA AI Technology Center (NVAITC) and a Professor at Shanghai Jiao Tong University. He leads global initiatives to bridge industrial AI needs with academic research.
Dr. Daniel Wang Zhengkui
Academic Supervisor | Collaborator
Associate Professor; Director, SIT x NVIDIA AI Centre (SNAIC); Director, Data Science & AI Lab (DSAIL), Singapore Institute of Technology
Dr. Daniel Wang Zhengkui is an Associate Professor at the Singapore Institute of Technology and Director of the SIT-NVIDIA AI Center. He drives impactful research in foundational AI models and real-world industrial challenges.
Dr. Aik Beng Ng
Industry Supervisor | Collaborator
Associate Professor, Singapore Institute of Technology; Senior Regional Manager, NVIDIA AI Technology Center, NVIDIA Corporation
Dr. Aik Beng Ng is an Associate Professor at Singapore Institute of Technology and Senior Regional Manager at the NVIDIA AI Technology Center (NVAITC). He specializes in accelerating AI adoption across the Asia Pacific South region.
Dr. Wael M. S. Yafooz
Master's Supervisor | Collaborator
Professor
Dr. Wael M. S. Yafooz is a Professor who supervised Fahad's Master's research on semantic textual document clustering and collaborates in AI, social media analytics, semantic analysis, and big data processing.
Dr. Md. Mahbub Alam
Bachelor's Supervisor
Associate Professor
Dr. Md. Mahbub Alam is an Associate Professor who supervised Fahad's bachelor's research on modified K-Means for big data clustering and works in big data systems and spatial data science.
Collaborators
Prof. Dr. Zainab Abu Bakar FASc
Collaborator
Adjunct Professor
Asia e University
Dr. Mithun Ahamed
Collaborator
Researcher
Al-Madinah International University
Dr. Abdulsamad Ebrahim Yahya
Collaborator
Associate Professor
Northern Border University
Asst. Prof. Nicholas Heng Loong Wong
Collaborator
Assistant Professor
Singapore Institute of Technology
Research service
Academic contribution beyond authored papers.
2026
Reviewer
ACM SIGIR 2026 Short Papers Track
Reviewer for ACM SIGIR 2026 short-paper submissions through OpenReview.
Aug 2020 . 1 mo
Reviewer
Hawaii International Conference on System Sciences, HICSS
A reviewer of 54th Hawaii International Conference on System Sciences (HICSS-54). Reviewed paper as experts in the respective field in the mini track "Data Analytics, Data Mining, and Machine Learning for Social Media"
Jul 2018 . 1 mo
Session Chairman
IEEE International Conference on Smart Computing and Electronic Enterprise
Session Chairman - Day (2) Number (18) Hall (Melati) - IEEE International Conference on Smart Computing and Electronic Enterprise. 11-12 July 2018, Kuala Lumpur, Malaysia. https://icscee2018.mediu.edu.my
Sep 2018 - Oct 2018 . 2 mos
TPC Member
International Conference on Industrial Internet of Things and Smart Manufacturing
TPC Member - International Conference on Industrial Internet of Things and Smart Manufacturing. 5-6 September 2018, London, United Kingdom. https://iotsm.org
Jun 2017 - Jan 2024 . 6 yrs 8 mos
Reviewer
Science Publication
Research Manuscript Reviewer -from June 2017 - Journal of Computer Science, Science Publication, U.S.A. http://thescipub.com/journals/jcs