Hi there! I'm
Ehsan Ul Haque
I'm a Software Engineer at Meta with a passion for learning, building, and problem-solving. My journey began in computer science, where I discovered the transformative power of programming and developed confidence through hands-on projects like a GUI-based Tic-Tac-Toe game and a 3D model of the Taj Mahal.
In my career, I explored both academia and industry. My research in usable security and privacy combines my technical skills with a human-centered approach, exploring how people interact with security and privacy tools.
I'm excited by new challenges and driven to keep pushing the boundaries of what I can achieve. Feel free to reach out if you want to collaborate, have a question, or just want to connect — ashik.buet10@gmail.com
Featured Projects
A selection of projects I've built. For a complete list, see projects page.
Fullstack Job Application Tracker
A fullstack web application to track job applications. Backend includes a robust REST API service built with Go to manage job applications, resumes, and related resources...
Smart-on-FHIR Client Portal
This client portal application is designed to support [FHIR (Fast Healthcare Interoperability Resources) standards](https://www.hl7.org/fhir/overview.html), integrating various essential resources like *Practitioner*, *Patient*, and *Patient Observations*. On the backend, it supports secure authentication with [Logica EHR sandbox](https://sandbox.logicahealth.org/dashboard), ensuring reliable access to health data...
Amazon Product Review Scraping and Parsing Toolkit
This application streamlines the retrieval of user reviews for Amazon products, offering flexible options to filter reviews by multiple criteria supported by Amazon. Additionally, it enables targeted review searches based on specific keywords...
Featured Research
Recent research contributions in usable security and privacy. For a complete list, see research page.
Do Technical Level and Trust in Service Providers Inform Consumers' Privacy Control Adoption?
As tech companies increasingly collect user data, understanding how users perceive and respond to privacy controls is crucial. This study examines the trust gap between technical and non-technical users in service providers' data collection...
How to Efficiently Detect Anime Faces Leveraging Combined Cascade Classifiers?
Anime face detection poses unique challenges due to its stylized nature. We address these challenges by training a cascade of classifiers, each focused on a specific facial feature...
How do Users' Calculate Tradeoff between Privacy and Money at IoT Purchase Time?
As the 'pay for privacy' model gains momentum, we investigated how users weigh data privacy against monetary benefits. Our study, using an incentive-compatible lottery on Prolific, uncovers the subtle calculations that drive user choices in privacy-focused IoT purchases..
Contact Me
I'm always open to discussing new projects, creative ideas, or opportunities to be part of your visions. Feel free to reach out!