Machine Learning Engineer & Researcher
Specializing in AI, NLP, Computer Vision, and Biomedical Image Processing
About Me
Hi, I'm Md. Shohanur Islam Sobuj! 👋 A Machine Learning Engineer with experience in developing and deploying ML solutions for real-world problems.
I am currently working as a Machine Learning Engineer at Anymate Me. My research interests include Biomedical Image Processing, Machine Learning, and Natural Language Processing.
I also serve as a Research Associate with prestigious journals and conferences such as ICLR, EMNLP, MDPI, and IEEE. I am always open to collaboration and new opportunities in AI research and development.
Feel free to reach out to me at shohanur.ai@gmail.com or connect with me on LinkedIn.
Work Experience
Machine Learning Engineer
- Developed and deployed MLOps-driven ML solutions to streamline business processes and enhance decision-making.
- Built scalable ML infrastructure and microservices for efficient model training, deployment, and monitoring in production.
- Managed CDC with MySQL using Debezium, Kafka, and Zookeeper for real-time data streaming.
- Delivered SmartRemarks for automated comment suggestions and feedback organization via historical data analysis.
- Built APIs for seamless integration, including an OCR-based TIN certificate validation system.
- Led intelligent automation tools like SDG data chatbots and AI-driven decision support systems.
- Implemented secure digital signature solutions to ensure document authenticity.
- Automated process status selection with sentiment analysis of desk remarks.
Machine Learning Engineer
- Developed and integrated large-scale distributed machine learning systems throughout their lifecycle, utilizing cutting-edge technology.
- Implemented MLOps principles, including CI/CD for ML, infrastructure management, and scalability optimization.
- Developed and deployed machine learning models using best practices for production environments.
- Designed and created APIs for ML/AI models, facilitating easy integration with other applications.
- Built diverse bots, including Monty (Discord and Telegram) for spam filtering, Arthur (knowledgeable bot), Finix (banking chatbot), and Magic Bookkeeping (AI-powered transaction categorization).
Education
Hajee Mohammad Danesh Science and Technology University
Dinajpur, Bangladesh
Degree: Electrical and Electronic Engineering
Thesis: Diagnosis of Diabetic Retinopathy Based on Convolutional Neural Networks Using Optical Coherence Tomographic Images
Research Interests
Natural Language Processing
Text classification, sentiment analysis, language modeling
Machine Learning
Deep learning, reinforcement learning, transfer learning
Computer Vision
Object detection, image segmentation, medical imaging
Bioinformatics
Biomedical image processing, disease diagnosis, healthcare AI
Latest News
February 2024
"L-TUNING: Synchronized Label Tuning for Prompt and Prefix in LLMs" accepted at Tiny Papers @ ICLR 2024.
February 2024
"Leveraging Pre-trained CNNs for Efficient Feature Extraction in Rice Leaf Disease Classification" accepted @ iCACCESS 2024.
October 2023
"Contrastive Learning for Universal Zero-Shot NLI with Cross-Lingual Sentence Embeddings" accepted at EMNLP-2023.
October 2022
Received the prestigious Reviewer Certificate from Springer Nature, recognizing contributions in upholding scientific research quality and integrity.
March 2022
Paper about Word Embedding Model for Transfer Learning accepted to MDPI applied science 2022.
Publications
Leveraging Pre-trained CNNs for Efficient Feature Extraction in Rice Leaf Disease Classification
2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS)
L-TUNING: Synchronized Label Tuning for Prompt and Prefix in LLMs
Tiny Papers @ ICLR 2024
Contrastive Learning for Universal Zero-Shot NLI with Cross-Lingual Sentence Embeddings
EMNLP, Multilingual Representation Learning (MRL) Workshop, December 2023
An Enhanced Neural Word Embedding Model for Transfer Learning
Applied Sciences journal by MDPI 2022
BERT to CNN-BiLSTM: A Hybrid Contextual Transfer Learning for Large Scale Imbalanced and Multi-label Document Classification
Knowledge-Based Systems, Elsevier, 2022
An Integrated Deep Framework of CNN-BiLSTM with Attention Mechanism for Diagnosing Heart Disease
Journal of King Saud University - Computer and Information Sciences, 2022