Research Wing
From undergraduate curiosity to peer-reviewed publication.
The Research Wing mentors DIU students through literature reviews, experimental research, and submissions to top-tier venues in ML, HCI, systems, and theory.
Mentored by experts
Faculty-guided research groups with consistent supervision and feedback.
18
Papers published
6
Active research groups
9
Faculty supervisors
IEEE/ACM
Target venues
Paper Reading Groups
Weekly reading circles covering landmark and latest papers — from attention mechanisms to distributed consensus.
Mentored Projects
Supervised research tracks in ML, NLP, computer vision, and theoretical CS, culminating in publishable work.
Publication Pipeline
Guidance on writing, peer review, poster prep, and submission to IEEE, ACM, and Bangladeshi venues.
Research cycle
How ideas become credible publications
Research progress is structured with clear milestones, reproducibility requirements, and supervised writing loops.
Week 1
Problem Scoping
Identify a meaningful research question by surveying prior work, gaps, and practical impact.
Week 2–4
Experiment Design
Define hypotheses, baselines, datasets, and reproducible methodology before model training.
Week 5–6
Evaluation & Analysis
Run ablations, perform statistical checks, and validate claims with clear visual evidence.
Week 7–8
Paper & Submission
Draft the manuscript, iterate with peer review, and prepare for conference or journal submission.
Curriculum
A structured path from beginner to contributor.
Every wing runs a semester-long curriculum with weekly sessions, office hours and progression checkpoints.
Research Foundations
Scientific method for CS
Reading research papers
LaTeX & citation management
Python scientific stack
Data handling & reproducibility
Writing a literature review
Applied ML Research
PyTorch & experiment design
Datasets, benchmarks, ablations
NLP, vision, speech subfields
LLM evaluation methodology
Reproducing recent papers
Paper writing workshops
Thesis & Publication Track
Problem formulation & novelty
Experimental rigor & statistics
Working with supervisors
Conference & journal targeting
Peer review & rebuttals
Poster & oral presentations
Specialisation
Specialised labs with focused mentorship
Members join domain labs while sharing methods, tooling, and review practices across the research wing.
Machine Learning Lab
Model development, benchmarking, and robust evaluation for applied and theoretical ML studies.
NLP & LLM Lab
Language modelling, retrieval workflows, evaluation design, and multilingual research directions.
Vision & HCI Lab
Computer vision and interaction research with user studies and human-centred experimentation.
Systems & Theory Lab
Algorithmic rigor, systems performance studies, and mathematically grounded CS research.
Research standards
Every project is expected to be reproducible, evidence-backed, and ready for academic scrutiny.
Reproducible experiment pipelines with versioned artifacts
Baseline comparison and ablation coverage for key claims
Weekly supervisor sync and documented decision logs
Structured paper-review loops before external submission
Ethical and dataset-bias checks where applicable
Clear presentation readiness: poster, slides, and rebuttal notes
Outcome focus
Publish with confidence, not guesswork.
Members conclude each cycle with documented experiments, manuscript drafts, and venue-ready submission plans.
Research Wing
Ready to publish with the Research Wing?
Apply when recruitment opens, then join a lab with a faculty supervisor, a reading group, and a milestone plan.