Rik Sarkar
Reader
Researches machine learning and optimisation, private and secure data science, analysis of generative models and AI for drug design.
Rik Sarkar's lab at Edinburgh works on generative & foundation models and data management & big data. 7 papers since 2023, 3 at top venues, mostly NeurIPS and AAAI. 4 PhD students. 7 alumni, most often to Google and Google DeepMind.
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 43%
- PhD students
- 4
- MS students
- 0
- alumni listed
- 7
Papers by yearfrom DBLP, 2023–2026
- 1 papers2026 · T1 0 · collecting
- 2 papers2025 · T1 1
- 3 papers2024 · T1 2
- 1 papers2023 · T1 0
T1 venuesOtherVenues: NeurIPS, AAAI
Research focuspaper titles that use each topic's words
- Generative & foundation models2 papers
- Data management & big data1 paper
- private0 papers
- secure0 papers
- drug0 papers
Paper list
From DBLP.
20261 paper
20252 papers
20243 papers
- NeurIPS (T1)Metric Space Magnitude for Evaluating the Diversity of Latent Representations (opens in a new tab)
- NeurIPS (T1)Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms (opens in a new tab)
- Epi UAITowards Understanding the Interplay of Generative Artificial Intelligence and the Internet (opens in a new tab)
Where alumni went7 listed, 33% to industry
Industry 2Academia 4
Most often to
- Google DeepMind
Also to
- National Central University
- University of Birmingham
- University of Copenhagen.
Apply to EdinburghFall 2027
Not announced yet
Informatics PhD
- Round
- Rolling (funding consideration)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- none
Not yet confirmed for this intake.
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