🧑 Career Summary

I am Azmine Toushik Wasi, a 4th year undergrad (only thesis defense remaining) in Industrial and Production Engineering at Shahjalal University of Science and Technology, Bangladesh.

My core research focuses on exploring AI4Science, Biomedical AI, Graph Neural Networks (GNNs), AI Agents and Reasoning, with an emphasis on structural biology, therapeutic, clinical, and molecular ML domains. In addition to that, my other research interests include interdisciplinary research in AI agents and Human-Centered AI (HCI, HAI) with NLP (Multilinguality, Bias and Fairness) and AI in Industrial Engineering. I am looking forward to pursue a PhD in Spring/Fall 2026 to continue my research.

I'm collaborating with Riashat Islam (Microsoft Research) on molecular ML, generative AI, and reasoning, and with Prof. Alshehri (KSU) on health informatics, GNNs, AI Agents, and GenAI as a visiting researcher. Previously, I have worked with Prof. Chae (HYU) on GNNs, Drug Discovery, and NLP-HCI-HAI and Prof. Min Xu (CMU) on biomolecules. I also collaborate actively with researchers from Cohere Labs (formerly, Cohere for AI) and Harvard University. I'm a dedicated participant in HTGAA 2025 (MIT Media Lab), with regular assignments and final projects (protein engineering). In CIOL, I collaborate with Prof. AMM Mukaddes (SUST), Prof. Ahsan (OU) and Prof. Bappy (LSU) on GNNs, AI Agents and digital twins for industrial and medical applications.

My research has been published in prestigious venues such as ICLR, WWW, COLING, DASFAA, ACCV, CSCW, and workshops of NeurIPS, ICLR, ICML, AAAI, ACL, EMNLP, NAACL and CHI, with ongoing reviews in several A*/A conferences and Q1 Journals. I regularly serve as reviewer and program chair/committee member for workshops in top AI-ML conferences. I am also a Kaggle Grandmaster (3rd GM in Bangladesh). Additionally, I have 3 years of experience in AI-integrated product/content automation, and product and project management.

I am a quick learner and highly adaptable, capable of leading projects and teams. I enjoy exploring new topics, sharing knowledge, refining existing skills, experimenting with new techniques, and challenging my capabilities.

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

🔍 Research Interests

---

• 🧬 Exploring Computational Biology and Biomedical AI Applications
  • Working on Computational Molecular Biology, Bioinformatics, and Computational Drug Discovery (CADGL). Exploring problems like molecular properties prediction, protein discovery, binder design and affinity, molecular interactions, structural biology, and healthcare optimization (ICLR'24).
  • Currently, exploring Digital Twins, clinical reasoning and Agentic LLMs for Clinical and Biomedical AI Applications.
  • Worked with de novo protein generation models and experienced with RL-inspired/energy-guided geometric/sequential structural biology modeling tools with GNNs, Flow Matching, GFLowNets and Diffusion models.
  • Working with Prof. Chae (HYU), Dr. Islam (Mila Quebec), Prof. Alshehri (KSU), Prof. Xu (CMU) and Prof. Ahsan (OU) on this area.
• 💠 Understanding and Applying Graph Neural Networks (GNN)
  • Engaged in Geometric Machine Learning, focusing on GNN theories and applications, with an emphasis on biomedical AI applications as described above.
  • Additionally, applying GNNs to industrial engineering, specifically in supply chain optimization (GNNs in SCM) and manufacturing.
  • Interested in application of knowledge graphs (extending GNNs) across diverse systems and domains ( COLING'24, ACL'24W, EMNLP'24W).
  • Working with Prof. Chae (HYU), Dr. Islam (MSR NYU), and Prof. Xu (CMU), Prof. Alshehri (KSU), Prof. AMM Mukaddes (SUST), Prof. Bappy (LSU), and CIOL researchers on this area.
• 🧑‍💻 Interdisciplinary Research on Humans, AI, and Language
  • My recent work develops trustworthy AI reasoning by integrating RAG, reward-based RL fine-tuning, Digital Twins, and structured reasoning to enhance model reliability. I'm working on multilinguality and reasoning in LLMs, focusing on self-verification, uncertainty estimation, and agentic decision-making in generative models, with AI4Good applications.
  • Additionally, in AI for Good, I've worked on accessibility, evaluation and improvement of human factors and ergonomics (ICML'24W and EMNLP'24W), religious/cultural values ( CSCW'24, CHI'24W, COLING'25 - 1, 2), into AI systems, mainly Generative AI and LLMs (ICLR'25).
  • Working with Cohere Labs (formerly, Cohere for AI) Community, Prof. Chae (HYU), Prof. Alshehri (KSU), and CIOL researchers on this area.

📰 News and Updates

---

🧑‍🔬 Research Experiences

---

• Visiting Researcher, AI4CHEMIA Research Group, King Saud University | Apr, 2025 - Present

• Global Committed Listener, How to Grow Almost Anything (HTGAA) 2025, Community Biotechnology Initiative, MIT Media Lab | Feb, 2025 - Present

• Participant, Brown University Dept. of Physics presents the AI Winter School 2025 | Jan, 2025

• Student Research Assistant, Mila Quebec AI Institute | May, 2024 - Present

• Contributor, Cohere Labs (formerly, Cohere for AI) | Aug, 2024 - Present

• Research Assistant, Computational Intelligence and Operations Laboratory, Shahjalal University of Science and Technology | 2021 - Present

• Research Intern, Xu Lab, Carnegie Mellon University | Jul, 2024 - December, 2024

• Visiting Researcher, Data Intelligence Lab, Hanyang University | Nov, 2023 - July, 2024

• Computational Neuroscience Summer School (Research Student), Neuromatch Academy | Jul, 2024

• CCAI Summer School (Research Student), Climate Change AI | Jun - Aug, 2024

📄 Selected Publications

---

• INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
  Angelika Romanou, ... , Azmine Toushik Wasi, ... , Sara Hooker, Antoine Bosselut
  ICLR'25 (Spotlight, Top 5.1%) ▪ [OpenReview] ▪ Dataset ▪ NLP ▪ LLM

• Gaussian Regularization in Neural Graph Learning
  Azmine Toushik Wasi, Taki Hasan Rafi, Dong-Kyu Chae
  DASFAA'25 (Full Paper, Short Oral) ▪ GNN

• GReFEL: Geometry-Aware Reliable Facial Expression Learning under Bias and Imbalanced Data Distribution
  Azmine Toushik Wasi*, Taki Hasan Rafi*, Raima Islam, Karlo Šerbetar, Dong-Kyu Chae (*Equal Contribution)
  ACCV'24 ▪ [CVF] ▪ [LNCS] ▪ [arXiv] ▪ CV

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

• 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 ▪ [OpenReview] ▪ [arXiv] ▪ [GitHub] ▪ Medical AI

• CADGL: Context-Aware Deep Graph Learning for Predicting Drug-Drug Interactions
  Azmine Toushik Wasi, Taki Hasan Rafi, Raima Islam, Serbetar Karlo, Dong-Kyu Chae
  TCBB In Review ▪ [arXiv] ▪ Medical AI ▪ GNN

• Dialectal Bias in Bengali: An Evaluation of Multilingual Large Language Models Across Cultural Variations
  Azmine Toushik Wasi, Raima Islam, Mst Rafia Islam, Farig Sadeque, Taki Hasan Rafi, Dong-Kyu Chae
  WWW'25 (TheWebConf) (Short Paper) ▪ NLP ▪ LLM ▪ HAI

• Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset and Benchmarks
  Azmine Toushik Wasi, MD Shafikul Islam Sohan, Adipto Raihan Akib, Mahathik Muhammad Bappy
  In Review ▪ [arXiv] ▪ [GitHub] ▪ Dataset and Benchmarks ▪ Supply Chains ▪ GNN

View All Publications and Ongoing Works →

📜 Selected Projects

---

• CIOL Presents Winter ML Bootcamp
  I am the lead organizer and instructor of the ML bootcamp, with more than 50 participants. I prepared materials and took live sessions on EDA, Tabular Data Modeling, Hyperparameter Tuning, ANNs - Deep Learning, NLP, Computer Vision, LLM Agents and mentored 6 research teams in the bootcamp.
  [Website] ▪ [GitHub] (Check Session Notebboks) ▪ [Youtube] (Check Recordings)
• AyaFestPe: A multi-lingual and multi-cultural festival exploration guide
  The pipeline starts by collecting festival data from HF and translating it with AyaExpanse for multilingual access. We then gather user queries, use M-RAG to embed data and queries, rerank results, and combine relevant context with the query to generate output.
  [GitHub] ▪ [Colab] (using Cohere API) ▪ [Kaggle] (Using released model weights, with quantization)
• 🏫 Online ML University: Free AI resource collection for everyone! Currently ~150⭐ in GitHub!
• 📑 Paper Organization and Collection
  
  • ICML 2024 Graph Paper Collection : List of all graph and/or GNN papers accepted at ICML'24. Currently ~160⭐ in GitHub!
  • ICLR 2024 Graph Paper Collection : List of all graph papers accepted at ICLR'24. Currently ~70⭐ in GitHub!
  • ICLR 2024 LLM Paper Collection : List of all LLM papers accepted at ICLR'24. Currently ~35⭐ in GitHub!

👩‍💻 Technical Skills

---

• Programming Languages: Python (Advanced), R, SQL, C
• DS & ML Tools (Python): NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, Keras, Tensorflow, Pycaret, PyTorch.
• ML Techniques: Normal ML Methods, Deep Learning, NLP, Computer Vision, Graph Neural Networks, Explainable AI, Robust Modeling, etc.
• DS Techniques: EDA, Hypothesis Testing, Sampling, Statistical Testing, Corelation Analysis and Inference.
• Data Analysis: MS Excel, SAS, Tableau, Power BI
• IT Automation: Automation in MS Word, Powerpoint, Excel, Google Sheets, Adobe Photoshop, Illustrator, Python based Photo Manipulations
• Computational Biology and Bio-molecules: Molecular Networks, Classification, Molecular Interaction Detection and Classification, Generative Modeling with Flow Matching and Graph Diffusion
• Human-Computer Interaction: LLM Customization, Survey Design, UI/Framework Design and Development, Data Collection and Analysis
• Others: Product Development, Project Management, Business Development and Strategic Planning and Analysis.

💼 Academic Services

---

• Conference or Journal Reviewer
  • AI/ML: ICLR'25, ICLR'24 Tiny Papers.
  • NLP: ACL ARR Feb (ACL), Apr, Jun (EMNLP), Aug 2024 [View in official reviewer list]; COLING'25.
  • HCI/HAI: CHI'25, CSCW'24, '25, UbiComp/ISWC'24, TEI'25, ICMI'24, IDC'24.
  • Journals: Complex & Intelligent Systems (Springer Nature).
  • Total conference or journal paper reviewed: 67
• Workshop Program Committee and Reviewer
  • ICLR'25: AI4MaterialsDiscovery Re-Align, LMRL
  • NAACL'25: DravidianLanTech, CLPsych, In2Writing
  • AAAI'25: Social Impact of AI,
  • CHI'25: STAIG, HEAL
  • NeurIPS'24: Behavioral ML, AI4MaterialsDiscovery, EvalEval, Military AI, MusIML
  • EMNLP'24: NLP for Positive Impact, Multulingual Represent Learning
  • ICML'24: AI4Science, LLMs & Cognition
  • ACL'24: TextGraphs-17, ClimateNLP, SMM4H, Language + Molecules, GenderBiasNLP, WASSA.
  • MICCAI'24: Fairness in Medical Imaging, GRaphs in biomedicAl Image anaLysis.
  • Total top conference workshop paper reviewed: 61
• Organizer
  • NeurIPS'24 Muslims in ML Affinity Workshop