About Me

Hello! I’m Ashaduzzaman, a dedicated and technically adept professional with a deep passion for Artificial Intelligence, Data Science, and Machine Learning. My expertise spans Large Language Models (LLMs), Generative AI, Natural Language Processing (NLP), Computer Vision, and Multimodal Vision-Language Models. I aim to apply my skills to create innovative and impactful solutions in AI/ML research and real-world applications.

Experience

Research Assistant
BRAC University

Conducted research on Bangladesh’s RMG industry, focusing on supply chain visibility, ESG indices, sustainability practices, and renewable energy adoption.

Key projects include:

Mapping export-oriented factories in Bangladesh (MiB) – Link Map
Exploring Adoption of Renewable Energy Technology (RET) among Apparel Exporters – Link
Addressing Climate Change and Plastic Waste in Bangladesh’s Garment Industry – Link

Research Interest

Large Language Models (LLMs), Natural Language Processing (NLP), Generative AI, Computer Vision, Vision Language Models (VLMs)

Academic Background

Bachelor of Science (BSc) in Electrical and Electronic Engineering
BRAC University, Dhaka, Bangladesh | Year: 2021

Higher Secondary Certificate (HSC)
Cantonment Public School and College, Rangpur, Bangladesh | Year: 2014

Certifications

IBM AI Engineering Specialization

Certified by IBM & Coursera

Mastered machine learning, deep learning, neural networks, and key ML algorithms including classification, regression, clustering, and dimensional reduction.
Implemented supervised and unsupervised models using SciPy and Scikit-Learn.
Deployed machine learning algorithms and pipelines on Apache Spark.
Built deep learning models with Keras, PyTorch, and TensorFlow for various applications.
Skills Gained: Machine Learning, Deep Learning, Neural Networks, Python Programming, Computer Vision, Applied ML, ML Algorithms, Regression, Mathematical Analysis.

Building LLM-Powered Applications

Certified by Weights & Biases

Build LLM-powered applications with entire process of designing, experimenting, evaluating and deploying LLM-based apps using LLM APIs, LangChain and W&B Prompts.
Skills Gained: MLOps, Weights & Biases, Large Language Models, LangChain, Prompt Engineering

Training and Fine-tuning Large Language Models (LLMs)

Certified by Weights & Biases

Gained hands-on experience in building, training and fine-tuning Large Language Models (LLMs) from scratch to enhancing their performance.
Skills Gained: MLOps, Weights & Biases, Large Language Models (LLMs), LLM Training, Fine-tuning LLMs, LoRA (Low-Rank Adaptation)

Deep Learning Specialization

Certified by DeepLearning.AI & Coursera

Built and trained deep neural networks, implementing vectorized architectures for real-world applications.
Developed CNNs for detection and recognition tasks, utilizing neural style transfer for creative image generation.
Constructed RNNs and applied NLP techniques using Hugging Face transformers for Named Entity Recognition and Question Answering.
Skills Gained: Machine Learning, Deep Learning, Artificial Neural Networks, Machine Learning Algorithms, Applied ML, Python Programming, Network Modeling, Computer Vision, Network Architecture, and Human Learning.

Machine Learning Specialization

Certified by Stanford Online & DeepLearning.AI

Designed and trained machine learning models with NumPy and scikit-learn, mastering supervised learning for prediction and binary classification.
Developed decision trees and ensemble methods, employing best practices for model development.
Built recommender systems using collaborative filtering and deep reinforcement learning techniques.
Skills Gained: Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Deep Learning, Artificial Neural Networks, Human Learning, Python Programming, Regression, Mathematics, Critical Thinking, and Network Modeling.

IBM Data Science Specialization