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Human-Centered Research

Research that
puts people first.

Readime is an independent research collective exploring the intersection of human behavior, technology, and the structures that shape our world.

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Tools built for researchers.

Free, browser-based tools that make research work faster, clearer, and more accessible. No account required.


What we do for you.

We partner with organizations, institutions, and independent researchers to design and conduct rigorous, human-centered research.

01
Literature Review

Comprehensive, systematic reviews of existing research. We map the landscape of a field, identify gaps, and synthesize findings into clear, actionable summaries that anchor your work.

02
Survey Design

From question construction to sampling strategy and statistical analysis, we design surveys that yield reliable, meaningful data and help you interpret what it all means.

03
Data Analysis

Qualitative coding, thematic analysis, regression, and mixed-methods approaches. We work with your existing data or help you design collection instruments from scratch.

04
Research Consulting

End-to-end research partnership, from defining your research question through methodology selection, ethics review, fieldwork, and final reporting tailored for your audience.


Recent Publications

Agriculture Technology

An Efficient Deep Learning Based Mobile Application for Pigeon Pea Disease Classification

P. K. Chaudhary et al., ICTP, Kathmandu, Nepal, 2026, pp. 1-6, doi: 10.1109/ICTP67998.2026.11485179.

About 65 percent of Nepal's population depends on agriculture, with pigeon pea ('Rahar') being a key legume crop. This study presents an end-to-end mobile application for real-time pigeon pea disease classification. A self-collected dataset of 7,930 leaf images was used to train a VGG16-based deep learning model, achieving 98 percent accuracy and an F1-score of 94 percent.

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Embedded Systems

An AI-Driven CNN-LSTM Framework for Multi-Stage Driver Drowsiness Detection with Real-Time Mobile Alerts

R. K. Yadav, P. K. Chaudhary et al., ICTP, Kathmandu, Nepal, 2026, pp. 1-6, doi: 10.1109/ICTP67998.2026.11485404.

This paper proposes "DrowsyDriveNet," a hybrid deep learning architecture classifying driver alertness into four stages: Alert, Slight, Moderate, and Severe. The architecture combines a frozen MobileNetV2 feature extractor with CNN and Bidirectional LSTM networks for spatial-temporal analysis.

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AI & ML

Multi-Class Fault Type Classification Using Sequence Components and Wavelet Features

S. K. Chaudhary, P. K. Chaudhary et al., ICTP, Kathmandu, Nepal, 2026, pp. 1-5, doi: 10.1109/ICTP67998.2026.11485076.

A reliable fault classification system for transmission lines using a hybrid approach combining symmetrical components and wavelet transform time-frequency analysis. A comparative study of machine learning models and neural networks is presented.

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Embedded Systems

A Novel Approach in Sanitary Pad Vending Machine using Image Processing and Internet of Things

Biplov Paneru, Prabhat Kumar Chaudhary. TechRxiv. January 2024. DOI: 10.36227/techrxiv.170629334.48523426/v1

A prototype that dispenses sanitary pads based on female student IDs stored in a CSV file, with cloud integration and remote health monitoring via IoT. The system aims to improve menstrual hygiene access in workplaces and public institutions.

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We study the world
through a human lens.

At Readime, every question we ask begins and ends with people. We believe rigorous inquiry, when grounded in empathy and curiosity, can illuminate paths toward a more equitable and thoughtful world.

Independent by Design

Our research agenda is set by questions, not funding pressures. We operate without institutional bias so findings remain honest and actionable.

Open by Default

We publish our work openly and welcome scrutiny. Knowledge only grows through sharing, critique, and collaboration across disciplines.

Interdisciplinary

The hardest problems resist single-discipline thinking. Our researchers bring together sociology, cognitive science, technology, and ethics.

Globally Situated

Human experience is not uniform. Our research is rooted in diverse geographic, cultural, and socioeconomic contexts, not just dominant narratives.


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Start a collaboration.

We welcome questions from readers, researchers, journalists, and institutions. Whether you want to discuss our findings, propose a joint research topic, or simply get in touch, drop us a line.

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