Tanveer Kader

Graduate Research Assistant, Full-Stack Developer

Graduate Research Assistant working in computer vision, with a parallel interest in full-stack software development.

Photo of Tanveer Kader
About

I am an intermediate researcher developing expertise in Computer Vision and Natural Language Processing. Through my effective academic writing, I have published some of my work in Scopus-indexed journals and conferences, demonstrating my capacity to articulate complex technical concepts and contribute valuable insights to these evolving fields.

My research focuses on multiple object tracking and human activity recognition. I also work with 3D Image Processing, Depth Images, and Point Clouds, using tools like CloudCompare for segmentation and labeling in applied computer vision projects. During my Bachelor's thesis on Bangla language dialect and gender classification using machine learning, I built a strong foundation in Natural Language Processing that continues to shape my research today.

Alongside research, I build full-stack software using React, Node.js, NestJS, and PostgreSQL. I develop AI-powered software by integrating machine learning into the systems I build. This hands-on development work helps me turn research ideas into working systems.

Research Interests

What I work on

Multiple Object Tracking

Detection, re-identification, and tracking pipelines for human activity recognition.

Computer Vision

Visual tracking systems, transformers, depth images, and 3D point clouds.

Natural Language Processing

Vectorization, document parsing, and applied NLP research.

Machine & Deep Learning

Building customized pipelines and frameworks for seamless experimentation.

Experience

Work experience

2024 - PRESENT

Graduate Research Assistant

Data Science & Simulation Modelling Research Group, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Pahang, Malaysia

2024 - PRESENT

Teaching Assistant

Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah

Education

Academic background

2024 - PRESENT

MSc in Computing (by research)

Institution: Universiti Malaysia Pahang Al-Sultan Abdullah MY

Supervisor: Dr. Ahmad Fakhri bin Ab Nasir

Thesis: "Formulation of Deep Learning Pipeline for Human Activity Recognition and Tracking"

2017 - 2022

BSc in Computer Science and Engineering

Institution: International Islamic University Chittagong BD

Supervisor: Prof. Dr. AKM Masum

Thesis: "Bangla Language Dialect and Gender Classification using Machine Learning"

Skills

Technical skills

Programming

C/C++PythonData StructuresAlgorithms

Computer Vision

Visual TrackingTransformersDepth Images3D Point Clouds

Machine Learning

Scikit-LearnPyTorchTensorFlowKerasUltralytics (YOLO)

NLP

Vectorizers (TF-IDF, Word2Vec)Document Parsing (LLM APIs)FastAPI

Data Analytics

NumPyPandasMatplotlibSeabornPower BI

Web Development

HTML/CSS/JSNode.jsNestJSReactExpressTailwind

Database

PostgreSQLMySQLMongoDBPrisma ORM

OS & Tools

Git/GitHubDockerLinuxLaTeXCloudCompare
Publications

Research papers

View on Google Scholar

Human Detection and Tracking with YOLO and SORT Tracking Algorithm

Tanveer Kader, AF Ab Nasir, MZ Toh, MN Aiman Shapiee, AF Abdul Razak · International Journal of Advanced Computer Science & Applications · 2025

The Inspection of Various Input Transformations Towards Human Detection and Tracking

Tanveer Kader, AF Ab Nasir, APP Abdul Majeed, MZ Toh, NM Ali · Journal of Theoretical and Applied Information Technology · 2025

Towards Optimised SORT Tracking Algorithm: Tuning the Feature Extractor BaseModel

Tanveer Kader, MZ Toh, Suryanti Awang, APP Abdul Majeed, AF Ab Nasir · International Conference on Software Engineering & Computer Systems · 2025

A Deep Learning Approach: The Impact of Sentiment Analysis of Bangladeshi Workers over the World

MRI Tomal, Tanveer Kader, K Moorthy, MA Majid · Baghdad Science Journal · 2025

Bangla Language Dialect Classification using Machine Learning

MRI Tomal, Tanveer Kader, AKM Masum, MKA Chy · International Conference on Electrical, Computer & Telecommunication Engineering · 2022

Contact

Get in touch

Open to conversations about research, collaboration, or new opportunities.