Hi, I'm Shohanur Islam Sobuj
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.
Experience
Work Experience
Machine Learning Engineer
December 2024 - Present
Anymate Me GmbH, Germany
- Developed and deployed MLOps-driven ML solutions to streamline business processes
Machine Learning Engineer
November 2023 - October 2024
Business Automation Ltd., Dhaka, Bangladesh
- Developed and deployed MLOps-driven ML solutions to streamline business processes
- Built scalable ML infrastructure and microservices for production environments
- Managed CDC with MySQL using Debezium, Kafka, and Zookeeper
- Delivered SmartRemarks for automated comment suggestions
- Built OCR-based TIN certificate validation system
Machine Learning Engineer
May 2022 - October 2023
Anchorblock Technology LLC, Dhaka, Bangladesh
- Developed large-scale distributed machine learning systems
- Implemented MLOps principles including CI/CD for ML
- Built diverse bots: Monty, Arthur, Finix, and Magic Bookkeeping
- Designed APIs for ML/AI model integration
Education
Electrical and Electronic Engineering
Hajee Mohammad Danesh Science and Technology University, Bangladesh
- Thesis: Diagnosis of Diabetic Retinopathy Based on CNNs Using OCT Images
Publications
2024
Parameter-efficient fine-tuning of large language models using semantic knowledge tuning
Scientific Reports
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
2023
Contrastive Learning for Universal Zero-Shot NLI with Cross-Lingual Sentence Embeddings
EMNLP, Multilingual Representation Learning (MRL) Workshop, December 2023
2022
An Enhanced Neural Word Embedding Model for Transfer Learning
Applied Sciences journal by MDPI 2022
In Preparation
Diagnosis of Diabetic Retinopathy Based on Convolutional Neural Networks Using Optical Coherence Tomographic Images
Master's Thesis - Hajee Mohammad Danesh Science and Technology University
Featured Projects
L-TUNING: Synchronized Label Tuning
A novel approach for prompt and prefix tuning in Large Language Models with synchronized label optimization.
Rice Leaf Disease Classification
Leveraging Pre-trained CNNs for efficient feature extraction in rice leaf disease classification with high accuracy.
Contrastive Learning for NLI
Universal Zero-Shot Natural Language Inference with Cross-Lingual Sentence Embeddings using contrastive learning.
Latest News
"L-TUNING: Synchronized Label Tuning for Prompt and Prefix in LLMs" accepted at Tiny Papers @ ICLR 2024.
"Leveraging Pre-trained CNNs for Efficient Feature Extraction in Rice Leaf Disease Classification" accepted @ iCACCESS 2024.
"Contrastive Learning for Universal Zero-Shot NLI with Cross-Lingual Sentence Embeddings" accepted at EMNLP-2023.
Received Reviewer Certificate from Springer Nature.
Paper about Word Embedding Model for Transfer Learning accepted to MDPI Applied Science 2022.
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
Achievement and Awards
Academic Services
Conference Reviewer
- Information Sciences Elsevier (IF 8.1) - 1 paper
- BMC Medical Informatics and Decision Making (IF 3.3) - 1 paper
- Journal of Infrastructure, Policy and Development (IF 0.7) - 1 paper