Bachelor of Science in Computer Science and Engineering (CSE)
Institution: International University of Business, Agriculture, and Technology (IUBAT)
Duration: 2018 – 2022
CGPA: 3.60/4.00 (Ranked among the top 20% of graduates)

Achievements:

• Dean's List recognition for outstanding academic performance in two semesters.
• Developed a solid foundation in computer science, focusing on algorithms, programming, machine learning, and data analysis.

Key Courses and Skills Developed:

• Machine Learning and Artificial Intelligence: Hands-on projects in supervised and unsupervised learning, including ensemble methods.
• Advanced Programming: Proficiency in Python, C, and Java with strong problem-solving capabilities.
• Database Management: Expertise in MySQL and MongoDB for efficient data storage and retrieval.
• Software Development: Designed and deployed web applications using Django, Flask, and React.js.

Extracurricular Activities:

• Active participation in programming contests and hackathons, including the National Collegiate Programming Contest (NCPC), which honed his teamwork and algorithmic skills.

Supervised Ensemble Technique to Classify Cardiac Arrhythmia

• Lab: AISIP Lab, under the guidance of Professor Dr. Shamim Akter
• Role: Researcher and Thesis Author
• Duration: 2021–2022
• Conducted advanced research using machine learning algorithms to improve the detection of cardiac arrhythmias.
• Utilized the UCI Machine Learning Repository’s Cardiac Arrhythmia dataset for exploratory data analysis and feature engineering.
• Applied ensemble techniques such as Decision Tree, Bagging, and Boosting to enhance classification performance.
• The findings are being prepared for submission as a manuscript titled "Supervised Ensemble Technique to Classify Cardiac Arrhythmia" to a peer-reviewed journal.

Performance Evaluation of Chronic Kidney Disease (CKD)

• Collaborators: Khan, R.A.; Mim, R.A.; Afroz, R.; Das, K
• Publication Status: Under Review at Springer Nature Journal
• Investigated machine learning models to predict the likelihood of chronic kidney disease.
• Employed feature selection and cross-validation techniques to optimize model performance for medical diagnostics.

Research Interests:

• Machine Learning and Deep Learning applications in healthcare.
• Natural Language Processing and Computer Vision for solving real-world problems.

Machine Learning Engineer

Zoho Corporation
January 2024 – Present

• Developed and optimized AI-driven business solutions, including CRM tools with integrated machine learning features.
• Designed scalable machine learning pipelines and predictive models for enterprise applications.
• Collaborated with cross-functional teams to deliver innovative solutions in natural language processing and predictive analytics.

Machine Learning Engineer

Optimizely
May 2022 – December 2023

• Led the development of SmartChat, a large language model-based conversational AI application.
• Utilized advanced NLP tools, including Hugging Face, PyTorch, and Transformers, to enhance response accuracy.
• Deployed solutions using Docker and MongoDB, ensuring robust and scalable implementations for clients.
• Built frameworks for real-time data processing and automated decision-making using machine learning pipelines.

Machine Learning Engineer

Shadhin Lab LLC
January 2022 – April 2022

• Designed and implemented full-stack AI projects, such as:
  • Text Sentiment Pro: An NLP-based sentiment analysis tool.
  • ChatBot Pro: A customer service chatbot that reduced manual queries by 25%.
  • AutoSummarize: A text summarization tool for efficient information extraction.
• Applied MLOps techniques, including CI/CD, for optimized model deployment and monitoring.

Python Instructor

Knowledge IT, Dhaka, Bangladesh
2022

• Taught Python programming fundamentals to over 100 students, including key libraries like NumPy, Pandas, and Matplotlib.
• Designed hands-on exercises and real-world projects to enhance programming skills.

• 6th Place – BUP ICT Fest Hackathon (2018)
  • Developed a machine learning-based solution, securing a top position among numerous participants.
• 2nd Runner-Up – IUBAT Intra Programming Contest (2021)
  • Demonstrated advanced problem-solving and algorithmic skills, achieving third place in an intra-university programming competition.
• 2nd Runner-Up – JU IT Fest Hackathon (2019)
  • Collaborated with a team to develop a machine learning model for disease detection, earning recognition for innovative approaches.
• NCPC (National Collegiate Programming Contest) Participant (2018–2021)
  • Consistently ranked commendably in national-level programming contests, showcasing expertise in efficient algorithms and teamwork.
• Dean’s List Recognition (2018–2022)
  • Received recognition for outstanding academic performance in two semesters during his undergraduate studies.

Peer-Reviewed Journal Articles (Under Review)

1. Performance Evaluation of Chronic Kidney Disease (CKD)
   • Authors: Khan, R.A.; Mim, R.A.; Afroz, R.; Das, K
   • Submitted to Springer Nature Journal (2024)
   • This study evaluates machine learning models for predicting chronic kidney disease, focusing on feature optimization and classification accuracy.

Manuscripts in Preparation

2. Supervised Ensemble Technique to Classify Cardiac Arrhythmia
   • Authors: Khan, R.A.; Nishy, E.F.; Akter, S
   • Explores ensemble machine learning techniques, including Bagging and Boosting, for detecting cardiac arrhythmias.

Conference Papers and Poster Presentations

3. Machine Learning Solutions for Automated Disease Diagnosis
   • JU IT Fest Hackathon (2019)
   • Presented an AI-driven approach for disease detection using machine learning models.
4. Customer Support Automation Using AI Chatbots
   • IUBAT AI Symposium (2021)
   • Detailed the development and deployment of an AI chatbot for enhancing customer support efficiency.