Dr. Fanwang Meng (Heidar-Zadeh’s Group) has been awarded the prestigious John Charles Polanyi Prize for his research on machine learning for drug discovery with imperfect data. Read more at the Queen’s Gazette website.
A persistent challenge in biomedical research is data quality, including missing values, imbalanced or biased data structures, and data noise. This accounts for many practical factors, such as some compounds not being available for biological testing, leading to missing values, and publication bias favoring only positive results, leading to imbalanced or biased data. These factors weaken predictions. To address this, Dr. Meng trains his models to work effectively even when the data is imperfect. He evaluates them using highly biased benchmarks, including the blood-brain barrier permeability dataset developed during his PhD research. This testing helps ensure the models remain reliable under real-world research conditions. More dependable models can support a more efficient development process.
Since 2007, five researchers in the Department of Chemistry have received the honor, including Dr. Meng and his postdoctoral supervisor, Dr. Farnaz Heidar-Zadeh, reflecting the department’s long-standing strength in chemical research.