Hi, I'm Harun-Ur-Rashid Entrepreneurial Engineer | Software Engineer | AI/ML Mentor

"I believe no problem is beyond human inventiveness."

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About Me

Harun-Ur-Rashid - Software Engineer

Biography

Current Role & Expertise I'm Harun-Ur-Rashid. Currently, I'm working as a Software Engineer at উপায় (upay). I've profound knowledge in Machine Learning, Deep Learning, Natural Language Processing, Fintech and Software Development.

Education & Research Interests I hold a B.Sc. in Computer Science and Engineering from Daffodil International University. I'm interested in doing research on Deep Learning & Computer Vision related problems.

Mission & Vision Dedicated to advancing Deep Learning, Computer Vision and building robust software systems. I bring a worldwide perspective to solving localized challenges through international research collaboration. As a former Co-Founder, I am committed to engineering excellence—advancing the AI landscape in Bangladesh and empowering the next generation of AI/ML enthusiasts through mentorship and the transformation of research into real-world solutions.

Interests

Machine/Deep Learning Data Analysis NLP Computer Vision Agriculture Imaging

Education

BSc in Computer Science and Engineering, 2019

Daffodil International University

Technical Skills

Python Django TensorFlow PyTorch NLP Computer Vision Scikit-learn Flask SQL

Work Experience

Software Engineer (Python)

উপায় (upay) - UCB Fintech Company Limited

  • Built and maintained MFS systems using Django REST Framework, improving request handling efficiency

Software Engineer (Machine Learning)

Syntech Solution Ltd.

  • Built a microservice-based company name clearance search system using DRF, Whisper, PyTorch, Elasticsearch, and Word2Vec
  • Improved search accuracy by combining NLP and speech models
  • Containerized services using Docker and deployed to an Ubuntu server
  • Built a data analysis report system using Flask, pandas, and matplotlib

Software Engineer

Giga Tech Limited

  • Built and maintained face verification and recognition systems using CNN, Flask, and REST APIs for eKYC platforms
  • Improved OCR and Transliteration microservices performance by 30%
  • Re-engineered the NID verification workflow into a stateless architecture
  • Led the migration to a distributed RPA architecture, reducing verification time by 40%
  • Integrated with EC, CBS, AD, and Porichoy
  • Contributed to eKYC deployments for BRAC, MTBL, Basic Bank, IFIC, TAP, bKash, FSIBL
  • Acquired foundational knowledge and practical skills in Machine Learning and NLP through a structured training program
  • Developed proficiency in analyzing complex datasets from industrial and social media sources using advanced natural language processing techniques

Featured Projects

Fraud Detection Model

Building a predictive model for credit card frauds in R

Machine Learning R Fraud Detection

Get In Touch

Feel free to reach out for collaborations, opportunities, or just to say hello!