Bo Wang
Associate Professor
Develops machine learning for computational biology and medicine, including single-cell foundation models.
Bo Wang's lab at Toronto works on genomics & computational biology, medical imaging & healthcare AI and generative & foundation models. 23 papers since 2023, 8 at top venues, mostly NeurIPS and MICCAI. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 35%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 8 papers2025 · T1 4
- 8 papers2024 · T1 1
- 7 papers2023 · T1 3
T1 venuesOtherVenues: NeurIPS, MICCAI, npj Digit. Medicine, CVPR, Findings of EMNLP
Research focuspaper titles that use each topic's words
- Generative & foundation models7 papers
- Medical imaging & healthcare AI6 papers
- Genomics & computational biology0 papers
- computational biology0 papers
- single-cell0 papers
Paper list
From DBLP.
20258 papers
- NeurIPS (T1)BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model (opens in a new tab)
- npj Digit. MedicineEVA-X: a foundation model for general chest x-ray analysis with self-supervised learning (opens in a new tab)
- MICCAI (T1)Exploring the Design Space of 3D MLLMs for CT Report Generation (opens in a new tab)
- Trans. Mach. Learn. Res.FraGNNet: A Deep Probabilistic Model for Tandem Mass Spectrum Prediction (opens in a new tab)
- ICML (T1)MedRAX: Medical Reasoning Agent for Chest X-ray (opens in a new tab)
- ICLR (T1)MorphoDiff: Cellular Morphology Painting with Diffusion Models (opens in a new tab)
- Nat. Mac. Intell.Moving towards genome-wide data integration for patient stratification with Integrate Any Omics (opens in a new tab)
- Nat. Mac. Intell.Transformers and genome language models (opens in a new tab)
20248 papers
- Quant. Biol.Current opinions on large cellular models (opens in a new tab)
- npj Digit. MedicineImproving prognostic accuracy in lung transplantation using unique features of isolated human lung radiographs (opens in a new tab)
- NeurIPS (T1)MassSpecGym: A benchmark for the discovery and identification of molecules (opens in a new tab)
- Nat. Mac. Intell.Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging (opens in a new tab)
- Nat. Mac. Intell.Tandem mass spectrum prediction for small molecules using graph transformers (opens in a new tab)
- ML4H@NeurIPSTowards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologies (opens in a new tab)
- ClinicalNLP@NAACLWangLab at MEDIQA-CORR 2024: Optimized LLM-based Programs for Medical Error Detection and Correction (opens in a new tab)
- ClinicalNLP@NAACLWangLab at MEDIQA-M3G 2024: Multimodal Medical Answer Generation using Large Language Models (opens in a new tab)
20237 papers
- CVPR (T1)MAESTER: Masked Autoencoder Guided Segmentation at Pixel Resolution for Accurate, Self-Supervised Subcellular Structure Recognition (opens in a new tab)
- SIPAIMMoment-alignment domain adaptation in the few-shot and low-resource context (opens in a new tab)
- Findings of EMNLPOpen Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval (opens in a new tab)
- MICCAI (T1)Pre-trained Diffusion Models for Plug-and-Play Medical Image Enhancement (opens in a new tab)
- Nat. Mac. Intell.Reusability report: Evaluating reproducibility and reusability of a fine-tuned model to predict drug response in cancer patient samples (opens in a new tab)
- NeurIPS (T1)Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning (opens in a new tab)
- ClinicalNLP@ACLWangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TorontoFall 2027
Computer Science MSc/PhD
- Round
- Single round (Dec 1)
- Opens
- —
- GRE
- optional
- English
- TOEFL/IELTS if applicable
- Fee
- CAD 135
Confirmed on the program page.
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Data
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- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
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