About
Online Optimization & Applications Research Group
The lead, the staff who do the science, and the alumni who've moved on.
Lead
RO
Group Lead · Professor
Renat Ostrovsky
Renat works at the intersection of online convex optimization and adversarial learning. His group’s recent focus is on parameter-free methods — algorithms that need no hand-tuned step size and still match the regret of the best tuning in hindsight.
Office hours: Tuesdays 14:00–16:00, Building 4 / 312.
Staff
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Postdoctoral Fellow
Maya Singh
Adaptive regret, mirror descent geometry.
AD
Postdoctoral Fellow
Aylin Demir
Online query optimization, learned databases.
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PhD Student · Y4
Leila Aydın
Heavy-tailed bandits, second-order online learning.
JP
PhD Student · Y3
Jihoon Park
Calibrated cardinality, distribution-free inference.
SV
PhD Student · Y3
Sasha Volkov
Bandit feedback for systems software.
NE
PhD Student · Y2
Noor El-Amin
Online saddle-point methods, game-theoretic learning.
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PhD Student · Y1
Kenji Tanaka
Adaptive index structures under drift.
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PhD Student · Y1
Elena Marchetti
Open-vocabulary decision-making, contextual bandits.