I am Azmine Toushik Wasi, a 4th year undergrad in Industrial and Production Engineering at Shahjalal University of Science and Technology, Bangladesh. My primary research interests lie in Graph Neural Net-based Medical AI applications.

My primary research focus is exploring Graph Neural Networks (GNNs) in Bio-Medical AI, mainly focusing on neuro, biomedical and molecular domains. In addition to my GNN research, my other research interests include Natural Language Processing (NLP) and Human-Centered AI for interdisciplinary works. I am looking forward to pursue a PhD in Fall 2025 to continue working on my research interests.

I am currently working with Prof. Dong-Kyu Chae, Hanyang University. Additionally, I have founded CIOL, to mentor young researchers and bridge the gap between Industrial Engineering and AI. Although my expertise lies in ML Research, I have work experience in AI-integrated IT Automation, Product and Project Management roles.

My research has been published in prestigious venues such as COLING'24, ICLR'24, and workshops of AAAI'24, NeurIPS'23 and CHI'24. I regularly serve as reviewer for top ML conferences (*CL ARR, ICLR, IDC) and as program chair for workshops in top conferences. I am also a Kaggle Grandmaster (3rd Kaggle GM in Bangladesh).
I am actively seeking research opportunities in theoretical or applied GNNs in medical domains (molecular/biomedical/neuroscience). I love to learn new things, share my knowledge, improve existing skills, experiment with acquired skills and challenge my capabilities.

View my Curriculum Vitae →
Feel free to email me (azminetoushik.wasi@gmail.com) if you're interested in collaboration or discussing research. I'm open to new ideas and collaborations.

🔍 Research Interests

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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)] .
• 🧬 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)].
• 🧑‍💻 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.
• 📝 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)] .

📰 News and Updates

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📄 Selected Publications

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• BanglaAutoKG: Automatic Bangla Knowledge Graph Construction with Semantic Neural Graph Filtering
  Azmine Toushik Wasi, Taki Hasan Rafi, Raima Islam, Dong-Kyu Chae
  COLING'24 ▪ Accepted ▪ NLP ▪ Bangla
  [arXiv]

• Neural Control System for Continuous Glucose Monitoring and Maintenance
  Azmine Toushik Wasi
  ICLR'24 ▪ Tiny Papers Track ▪ Accepted ▪ Optimization ▪ Medical AI
  [OpenReview] ▪ [arXiv]

• When SMILES have Language: Drug Classification using Text Classification Methods on Drug SMILES Strings
  Azmine Toushik Wasi, Karlo Serbetar, Raima Islam, Taki Hasan Rafi, Dong-Kyu Chae
  ICLR'24 ▪ Tiny Papers Track ▪ Accepted ▪ NLP ▪ Medical AI
  [OpenReview] ▪ [arXiv]

View All Publications →

📜 Other Ongoing Works

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• Towards Reliable Facial Expression Learning : Making FER systems more reliable with geometry. In Review

• Drug Discovery using Generative Graph Neural Networks : Application of Graph Neural Network in Drug Development. In Review

• Incorporating Gaussian Process in Neural Graph Learning : Strengthening Graph Neural Networks with Statistical methods. In Review

• Examining Cultural Bias in LLMs : Investigating cultural bias in LLMs. In Review

• Adaptive Optimal Oxygen Level Controller for Critical Patients : Developing an optimal oxygen level controller for critical patients. In Progress

🗣️ Talks and Training Workshops

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• Research in IPE and ML: The Beginning | April 04, 2024 | Webinar
• Pie & AI: Sylhet - ML Research for Engineering Undergrads: A Pathway | Oct 23, 2023 | Workshop
• Introduction to Research (IPE and ML Focused) | Sept 8, 2023 | Workshop
• Navigating the Digital Frontier | Building the Basics on ML and AI | Aug 25, 2023 | Guest Talk
• Building AI and Machine Learning Model: How to Start? | Jul 23, 2023 | Workshop
• Pie & AI: Sylhet - Use of ChatGPT and Generative AIs | Mar 3, 2023 | Guest Lecture
• Pie & AI: Sylhet – Machine Learning for Engineering Students | Jan 25, 2023 | Talk
• Pie & AI: Sylhet - Introduction to Python for AI | Oct 15-22, 2023 | Workshop

💼 Recent Services

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• Conference or Journal Reviewer
  • ACL ARR February, April 2024 [View in official reviewer list].
  • IDC 2024 (International Conference on Interaction Design & Children).
  • ICLR Tiny Papers Track (2024).
  • Complex & Intelligent Systems. [Impact factor 5.8 (2022)].
• Workshop Program Committee
  • TextGraphs-17, Graph-based Methods for Natural Language Processing co-located with ACL 2024.
  • ClimateNLP, Natural Language Processing meets Climate Change Workshop co-located with ACL 2024.
• Workshop Reviewer
  • AI4Science, AI for Science: Scaling in AI for Scientific Discovery Workshop, co-located with ICML 2024.
  • SMM4H, Social Media Mining for Health Applications Workshop, co-located with ACL 2024.
  • Language + Molecules Workshop, co-located with ACL 2024.
  • KALLM, Knowledge Graphs And Large Language Models Workshop, co-located with ACL 2024.