Olgica Milenkovic
Professor
Studies machine learning and coding theory, including machine unlearning, graph and hypergraph neural networks and federated learning for computational biology.
Olgica Milenkovic's lab at UIUC works on learning theory & optimization and trustworthy & safe ML. 35 papers since 2023, 10 at top venues, mostly ISIT and NeurIPS. 7 PhD students and 1 master's student. 21 alumni. Applications close .
At a glance
- papers, 2023–2026
- 9/ year
- at T1 venues
- 29%
- PhD students
- 7
- MS students
- 1
- alumni listed
- 21
Papers by yearfrom DBLP, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 9 papers2025 · T1 2
- 9 papers2024 · T1 2
- 15 papers2023 · T1 6
T1 venuesOtherVenues: ISIT, NeurIPS, ICLR, AISTATS, ICML
Research focuspaper titles that use each topic's words
- unlearning4 papers
- Learning theory & optimization3 papers
- coding theory1 paper
- machine unlearning1 paper
- Trustworthy & safe ML0 papers
Paper list
From DBLP.
20262 papers
- IEEE Trans. Inf. TheoryFederated Aggregation of Full Mallows Rankings via Borda and Lehmer Coding (opens in a new tab)
- Trans. Mach. Learn. Res.WaveletDiff: Multilevel Wavelet Diffusion For Time Series Generation (opens in a new tab)
20259 papers
- NeurIPS (T1)DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform (opens in a new tab)
- IEEE J. Sel. Areas Inf. TheoryDNA Tails for Molecular Flash Memory (opens in a new tab)
- NeurIPS (T1)Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness (opens in a new tab)
- ISITFragmentation in Data Deduplication Systems I: The Stretch Metric (opens in a new tab)
- ISITFragmentation in Data Deduplication Systems II: The Jump Metric (opens in a new tab)
- EntropyGeneralized Orthogonal de Bruijn and Kautz Sequences (opens in a new tab)
- ISITGeneralized Orthogonal De Bruijn Sequences (opens in a new tab)
- Des. Codes Cryptogr.Perturbation-resilient sets for dynamic service balancing (opens in a new tab)
- IEEE Trans. Inf. TheoryReducing Fragmentation in Data Deduplication Systems via Partial Repetition and Coding (opens in a new tab)
20249 papers
- ISITA Multi-Sequence Prophet Inequality Under Observation Constraints (opens in a new tab)
- Dagstuhl ReportsCoding Theory and Algorithms for Emerging Technologies in Synthetic Biology (Dagstuhl Seminar 24511) (opens in a new tab)
- IEEE Trans. Commun.DNA-Based Data Storage Systems: A Review of Implementations and Code Constructions (opens in a new tab)
- Trans. Mach. Learn. Res.Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls (opens in a new tab)
- NeurIPS (T1)FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning (opens in a new tab)
- PLoS Comput. Biol.Interpretable online network dictionary learning for inferring long-range chromatin interactions (opens in a new tab)
- AISTATS (T1)Online Distribution Learning with Local Privacy Constraints (opens in a new tab)
- J. Appl. Probab.Optimal stopping methodology for the secretary problem with random queries (opens in a new tab)
- BMC Bioinform.Semi-quantitative group testing for efficient and accurate qPCR screening of pathogens with a wide range of loads (opens in a new tab)
202315 papers
- ITWA Combinatorial Proof for the Dowry Problem (opens in a new tab)
- IEEE Trans. Inf. TheoryCoding for Polymer-Based Data Storage (opens in a new tab)
- NeurIPS (T1)Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection (opens in a new tab)
- ICLR (T1)Efficient Model Updates for Approximate Unlearning of Graph-Structured Data (opens in a new tab)
- ISITFinding a Burst of Positives via Nonadaptive Semiquantitative Group Testing (opens in a new tab)
- JMLR (T1)Higher-Order Spectral Clustering Under Superimposed Stochastic Block Models (opens in a new tab)
- ICLR (T1)Machine Unlearning of Federated Clusters (opens in a new tab)
- ISITOn Constant-Weight Binary B2-Sequences (opens in a new tab)
- J. Appl. Probab.Optimal Stopping Methodology for the Secretary Problem with Random Queries - ADDENDUM (opens in a new tab)
- ICML (T1)PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation (opens in a new tab)
- Knowl. Inf. Syst.Provably accurate and scalable linear classifiers in hyperbolic spaces (opens in a new tab)
- Theor. Comput. Sci.Query-based selection of optimal candidates under the Mallows model (opens in a new tab)
Where alumni went21 listed
Apply to UIUCFall 2027
UIUC Siebel Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- optional
- English
- TOEFL iBT / IELTS
- Fee
- USD 90
Not yet confirmed for this intake.
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