Machine Learning Researcher
(Graph Neural Nets, Medical AI, Human-centric AI & NLP)
Kaggle Grandmaster | Explorer | Looking for research opportunities
About :
- Experienced in Programming, Machine Learning, Artificial Intelligence, Inter-disciplinary Research, IT Automation, Project - Product Management and Analytics.
- Actively involved in several Machine Learning Research. My research interests include Graph Neural Networks, Human-Centered AI, and Natural Language Processing, mainly focusing on medical problems. I am working on Data Intelligence Lab, HYU, KR. Additionally, I have founded Computational Intelligence and Operations Lab - CIOL, SUST, BD, to mentor young researchers and bridge the gap between Industrial Engineering and AI. I'm also the 3rd Kaggle Grandmaster of BD.
- My research has been published in prestigious venues such as LREC-COLING'24, ICLR'24 Tiny Papers Track, Workshops of CHI'24, AAAI'24 and NeurIPS'23, with ongoing reviews in ECCV'24, IEEE TCBB, ACL ARR, among others.
- Passionate about learning new things, sharing my knowledge, improving myself regularly, experimenting with acquired skills and challenging my capabilities. Building all-in-one free AI/ML resources collection here.
- Serving as reviewer in top ML conferences and journals like ACL ARR, ICLR, IDC; and program chair in multiple ACL'24 workshops.
- Actively looking for research opportunities focusing on different Types of GNN Learning and NLP (Theoretical or Applied) or Healthcare (Drugs, Bioinformatics, Biomedical Engineering or Neuroscience and AI) domains with conjunction to any of my research interests.
Research :
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💠 Graph Neural Networks (GNN): I am exploring Graph Neural Network or Geometric Machine Learning Theories, applying and improving GNN models and resources in Healthcare (Drugs, Proteins and Molecules) DDI, Knowledge Graphs BanglaAutoKG (COLING'24), and Supply Chains SupplyGraph (AAAI'24W).
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🧬 Medical AI: In Medical AI, I am working on developing AI systems for Healthcare, mainly focusing on Computational Molecular Biology - Neuroscience, Bioinformatics, Computational Drug Discovery CADGL, and Healthcare Optimization Glucose level control (ICLR'24).
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🧑💻 Human-Centered AI (HAI): Despite extensive coursework in ergonomics, Human Factors Engineering (HFE), behavior studies, and psychology within our IPE curriculum, there's a notable gap in inter-disciplinary research between IPE and AI. Motivated by this, I am working on integrating HFE AI Ownership, Individuality (CHI'24W), Computational Social Science (CSS) Social Biases (CHI'24W), Fairness and Reliability ARBEx into AI systems, focusing on HAI perspectives of IPE.
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📝 Natural Language Processing (NLP): In Natural Language Processing, I am developing Knowledge Graphs (COLING'24) and Bangla Knowledge Systems; motivated by NLP + GNNs. I am also working on inter-disciplinary CSS, Climate, and BioMedNLP Molecules+NLP (ICLR'24).
Skills :
- Programming: Python (Advanced), C (For Contests), R, SQL.
- ML Techniques : Deep Learning, NLP, Graph Neural Networks, GANs.
- DS & ML Tools (Python) : NumPy, Pandas, Matplotlib, Seaborn, Stats-models, Scikitlearn, Keras, Tensorflow, PyTorch.
- Data Analysis: MS Excel, SAS, Tableau, Power BI.
- IT Automation:
- Automation in MS Word, Powerpoint, Excel, Google Sheets, Adobe Photoshop, Illustrator using Python, built-in toolkits and ML;
- Photo Manipulations at large scale using OpenCV and Pillow;
- NLP and CV-based ML models to detect error in textuala and visual contents.
- Product Development, Project Management, Business Development and Strategic Planning and Analysis.