Riyad Bin Rafiq

Riyad Bin Rafiq Email and Phone Number

CSE PhD Candidate at UNT @ Biomedical AI Lab at UNT
Riyad Bin Rafiq's Location
Denton, Texas, United States, United States
Riyad Bin Rafiq's Contact Details

Riyad Bin Rafiq work email

Riyad Bin Rafiq personal email

n/a
About Riyad Bin Rafiq

As a Ph.D. candidate in Computer Science and Engineering, I am dedicated to using my expertise to make a positive impact on society. My current research focuses on developing a wearable sensor-based hand gesture recognition system for speech-impaired individuals, specifically those who lack fine motor skills. By utilizing transfer learning, continual learning, and meta-learning, I am exploring new and innovative ways to customize gesture learning for these individuals.With a passion for using technology to solve real-world problems, I bring a unique combination of technical knowledge and empathy to my work. My experience with deep learning and Python, as well as my familiarity with data science techniques, enables me to effectively communicate my findings and insights.I am always looking for new opportunities to collaborate with others who share my passion for using technology to make a difference, and I am eager to bring my skills and experience to bear in innovative and impactful projects.

Riyad Bin Rafiq's Current Company Details
Biomedical AI Lab at UNT

Biomedical Ai Lab At Unt

View
CSE PhD Candidate at UNT
Riyad Bin Rafiq Work Experience Details
  • Biomedical Ai Lab At Unt
    Graduate Research Assistant
    Biomedical Ai Lab At Unt Jan 2021 - Present
    Denton, Texas, United States
    • Gesture Recognition System: Currently, working to build a customized hand gesture recognition system using accelerometer data to generate audible responses, particularly for those who lack fine motor skills. The primary focus is enhancing the custom gesture learning strategy through the implementation of transfer learning and continual learning techniques.• PROMIS: This study aimed to assess the feasibility of employing computerized adaptive testing (CAT) on a tablet computer for administering patient-reported outcome measures in rehabilitation inpatients, while also examining the workload impact on staff and identifying the prevalence of elevated T-scores across six PROMIS measures.• ML Validation in Medicine: Presented an overview of the common limitations of machine learning model validation methods in the field of medicine, followed by solutions aimed at addressing these limitations. Our focus was on enhancing the reliability of machine learning models specifically tailored for medical applications.
  • University Of North Texas
    Graduate Teaching Assistant
    University Of North Texas Aug 2021 - Present
    Denton, Texas, United States
    • CSCE 5280 AI for Wearables and Healthcare (Fall'22 & 24): Provided guidance to students throughout the entire project process, from brainstorming ideas to final implementation. Additionally, I assisted instructors in creating exam questions and graded student assignments.• CSCE 5218 Deep Learning (Spring'22): Utilized minitorch to prepare assignments and provided assistance to students in completing and understanding them. Additionally, I graded assignments and offered explanations for any topics that students may have missed during class.• CSCE 1030 Computer Science I (Fall'21): Spent three hours instructing a lab class where I helped freshman students solve programming problems utilizing C++. Also, provided assistance to students in completing their projects.• NSF-ReU Summer Research: During a 10-week summer research program, I provided guidance to undergraduate and graduate students, facilitating their research activities and assisting in the implementation of ideas. Additionally, I offered explanations on relevant topics essential for their research endeavors.• Other courses: CSCE 5215 Machine Learning (Spring’22), CSCE 4110 Algorithms (Spring’22).
  • Jmj Code
    Software Engineer
    Jmj Code Oct 2020 - Dec 2020
    Dhaka, Bangladesh
    Contributed to developing different modules of a web application for online vendors.

Riyad Bin Rafiq Skills

Artificial Neural Networks Python Data Analysis Machine Learning Algorithms Recurrent Neural Networks Long Short Term Memory Cluster Analysis Convolutional Neural Networks Machine Learning Deep Learning C++ Computer Vision Object Oriented Programming Data Visualization Logistic Regression Sql

Riyad Bin Rafiq Education Details

Frequently Asked Questions about Riyad Bin Rafiq

What company does Riyad Bin Rafiq work for?

Riyad Bin Rafiq works for Biomedical Ai Lab At Unt

What is Riyad Bin Rafiq's role at the current company?

Riyad Bin Rafiq's current role is CSE PhD Candidate at UNT.

What is Riyad Bin Rafiq's email address?

Riyad Bin Rafiq's email address is ri****@****unt.edu

What schools did Riyad Bin Rafiq attend?

Riyad Bin Rafiq attended University Of North Texas, University Of North Texas, Chittagong University Of Engineering & Technology.

What skills is Riyad Bin Rafiq known for?

Riyad Bin Rafiq has skills like Artificial Neural Networks, Python, Data Analysis, Machine Learning Algorithms, Recurrent Neural Networks, Long Short Term Memory, Cluster Analysis, Convolutional Neural Networks, Machine Learning, Deep Learning, C++, Computer Vision.

Free Chrome Extension

Find emails, phones & company data instantly

Find verified emails from LinkedIn profiles
Get direct phone numbers & mobile contacts
Access company data & employee information
Works directly on LinkedIn - no copy/paste needed
Get Chrome Extension - Free

Aero Online

Your AI prospecting assistant

Download 750 million emails and 100 million phone numbers

Access emails and phone numbers of over 750 million business users. Instantly download verified profiles using 20+ filters, including location, job title, company, function, and industry.