Software engineer & AI enthusiast

Ricko Shaha.

Based in ChattogramBangladesh · UTC +06

I’m a software engineer focused on Web Experimentation and CRO (Conversion Rate Optimization) Development, with experience building dashboards and automating workflows.

I’m an AI enthusiast interested in model selection: comparing accuracy and error costs, especially when classes are imbalanced.

I studied computer science at CUET. My undergraduate work on landslide susceptibility led to a paper on relative model-selection metrics.

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City-level estimates · About this map

PhD applications

Applying for CS PhD programmes for Fall 2027, with broad interests in Artificial Intelligence, Machine Learning, and Software Systems.

Web Experimentation

From a visit to a conversion.

Follow visitors through two checkout designs. Watch completed orders collect, and see the results take shape.

How it works

This illustrative experiment sends 100 visitors to each checkout. A produces 52 completed orders and B produces 68. Enable JavaScript to watch visitors move through the pages and build the 3D result columns.

Selected work

Research & engineering

Rangamati Hill Tracts(a district within Chattogram division, Bangladesh)

5,067grid cells scored

Model scoreLow → High

Rangamati Hill Tracts (a district within Chattogram division, Bangladesh) mapped from lower susceptibility in green to higher susceptibility in red.

Undergraduate thesis · CUET

Landslide susceptibility in Rangamati Hill Tracts(a district within Chattogram division, Bangladesh)

A Flask application that compares seven ML models using eight environmental factors, assesses coordinates within Rangamati Hill Tracts (a district within Chattogram division, Bangladesh), and maps susceptibility across the district.

Python / scikit-learn / Flask / Leaflet

Project notes Code

Publication · IEEE RAAICON, 2021

TOS: a relative metric for model selection

R. Shaha, D. Talukder, M. A. Iqbal, M. M. Haque

A scoring rule that combines standardized accuracy and error across a candidate pool. The research notes explain the formula and how adding or removing a candidate can change the ranking.

Read the research Paper / DOI Interactive demo

Engineering · Client project

Workflow metrics dashboard

A React dashboard showing experiment release frequency, development hours, and team progress from Jira data. Built to help teams monitor their workflow and plan sprints.

React / Node.js / Express / Jira REST API

Dashboard notes

Production tooling / Data flow

AirtableJira

Webhook → Validate origin → Sync update
Idempotent writes. No echo loops.

Engineering · Client project

Airtable–Jira integration

A Python webhook service that keeps tasks, statuses, and timelines in sync between Airtable and Jira, reducing manual re-entry in experiment tracking.

Python / Airtable API / Jira REST API / Webhooks

Integration notes

All project notes

Research interests

Model evaluation

My thesis raised a question I’m still interested in: how should we compare models when false positives and false negatives have different consequences?

Research statement

Cost-sensitive model selection
How should a selection rule express the different consequences of false positives and false negatives?
Evaluation under class imbalance
What should we measure when the rare event matters most, and aggregate accuracy hides it?
Language model evaluation & routing
How do we choose between models when correctness, latency, and cost are separate objectives?

Background

Resume

I’m based in Chattogram, Bangladesh. At EchoLogyx, I work on Web Experimentation and CRO Development and have designed and analysed around 800 web experiments on production traffic.

My engineering projects include a workflow metrics dashboard and a two-way Airtable–Jira integration for experiment tracking.

Earlier interests included robotics and mathematics: a line-following robot competition win and a regional Mathematical Olympiad podium.

2022 — now: Software EngineerEchoLogyx Ltd.Web Experimentation and CRO Development
2025: Subject Matter ExpertWorkera · ContractWeb development assessment review
2016 — 2022: BSc, Computer Science & EngineeringChittagong University of Engineering & Technology

Technical skills

Languages: Python, JavaScript (ES6+), TypeScript, C, SQL
Frontend: React.js, HTML5/CSS3, SCSS, Shopify (Liquid), Web APIs, DOM Manipulation
Backend: Node.js, Express.js, Flask, REST APIs, Webhooks
Web Experimentation: ABLyft, Kameleoon, VWO, Dynamic Yield, Convert, ABTasty, Varify, Intelligems
Machine Learning: Scikit-Learn, NumPy, Pandas, Matplotlib, Seaborn, Model Selection & Evaluation, Cross Validation, Class Imbalance, Cost-Sensitive Metrics
Statistics & Experimentation: R, MATLAB, Experimental Design, Hypothesis Testing, Significance Testing, Sample-Size Planning, Statistical Analysis
Version Control: Git, GitHub
Project Management: Jira, ClickUp, Airtable
Scientific Writing: LaTeX, BibTeX, Matplotlib Figure Preparation

Contact

For research discussions, engineering work, or PhD opportunities:

ricko.shaha@gmail.com

+880 1850-785238

GitHub LinkedIn LeetCode Resume