Articulated Research Institute for Scientific Excellence

A.R.i.S.E. is an applied machine learning research lab based in Bangladesh. We work wherever rigorous ML methodology meets real-world complexity — from financial markets and satellite imagery to regional languages, medical imaging, explainability, and beyond.

Our research spans the full arc from early-stage ideas to published results. Some projects are foundational explorations; others carry peer-reviewed contributions and public datasets. What ties them together is a commitment to methodologically sound, reproducible science — with a focus on problems that matter in South Asian and low-resource contexts.

We are affiliated with the Department of Computer Science and Engineering, Southeast University, Bangladesh.

🌐 ariserl.org  ·  💼 LinkedIn  ·  📘 Facebook

What We Work On

Our portfolio is intentionally broad. Past and ongoing work has touched:

• Financial ML — structural break detection, coverage bias, regime analysis, and time series forecasting in emerging markets
• Remote Sensing — satellite and aerial image analysis
• Regional Language NLP — dialect-aware datasets and models for Bengali and related varieties
• Medical & Biomedical Imaging — retinal disease detection, ocular health, and physics-informed vision
• Explainable AI — gradient-based and attention-based interpretability on image models
• Multimodal & Fusion Architectures — combining heterogeneous inputs for robust prediction

This list grows. If something is in our pipeline, it will eventually surface here.

What You'll Find Here

• Datasets — annotated and benchmark datasets released alongside our publications
• Model Checkpoints — fine-tuned and adapter-based models from our research pipelines
• Reproducibility Artifacts — configs, notebooks, and scripts to reproduce key results

Get in Touch

We welcome collaboration with researchers working on applied ML problems, particularly in low-resource, domain-specific, or underrepresented settings.

Reach us at ariserl.org or connect on LinkedIn.