Jeffrey Mak
Departmental Lecturer
Uses interpretable machine and deep learning to predict CRISPR-Cas9 cleavage activity for safer genome editing.
Jeffrey Mak's lab at Oxford works on genomics & computational biology, trustworthy & safe ML and interpretability, evaluation & safety of LMs. 2 papers since 2023. Applications close .
At a glance
- papers, 2023–2026
- 1/ year
- at T1 venues
- 0%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 1 papers2025 · T1 0
- 0 papers2024 · T1 0
- 1 papers2023 · T1 0
T1 venuesOther
Research focuspaper titles that use each topic's words
- Genomics & computational biology0 papers
- Trustworthy & safe ML0 papers
- Interpretability, evaluation & safety of LMs0 papers
- predict0 papers
- genome0 papers
Paper list
From the lab homepage.
20251 paper
20231 paper
- Artificial Intelligence in the Life SciencespiCRISPR: physically informed deep learning models for CRISPR/Cas9 off−target cleavage prediction (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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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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- The lab homepage
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- Alumni
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