What is she best known for?
The fields of study she is best known for:
- Algorithm
- Statistics
- Algebra
Olgica Milenkovic mostly deals with Algorithm, Low-density parity-check code, Decoding methods, Discrete mathematics and Block code.
Her Algorithm research includes elements of Theoretical computer science, Mathematical optimization and Coding.
Her Low-density parity-check code research is multidisciplinary, incorporating elements of Forward error correction and Optical communication.
Her study looks at the intersection of Decoding methods and topics like Dna storage with Computer hardware, Database, Markov process and DNA sequencing.
As a member of one scientific family, she mostly works in the field of Discrete mathematics, focusing on Tanner graph and, on occasion, Idempotence, Simple and Structure.
Her studies deal with areas such as Computational complexity theory, Sparse approximation and Signal reconstruction as well as Compressed sensing.
Her most cited work include:
- Subspace Pursuit for Compressive Sensing Signal Reconstruction (1862 citations)
- Combinatorial constructions of low-density parity check codes for iterative decoding (252 citations)
- Subspace Pursuit for Compressive Sensing: Closing the Gap Between Performance and Complexity (192 citations)
What are the main themes of her work throughout her whole career to date?
Olgica Milenkovic mainly focuses on Algorithm, Discrete mathematics, Combinatorics, Decoding methods and Theoretical computer science.
Her Algorithm study frequently involves adjacent topics like Mathematical optimization.
Her Mathematical optimization study combines topics from a wide range of disciplines, such as Quadratic equation and Matrix completion.
The study incorporates disciplines such as Tanner graph, Block code, Linear code and Low-density parity-check code in addition to Discrete mathematics.
Her Combinatorics course of study focuses on Cluster analysis and Graph.
Her work in Decoding methods covers topics such as Code which are related to areas like Metric.
She most often published in these fields:
- Algorithm (28.35%)
- Discrete mathematics (25.23%)
- Combinatorics (20.56%)
What were the highlights of her more recent work (between 2018-2021)?
- Algorithm (28.35%)
- Combinatorics (20.56%)
- Discrete mathematics (25.23%)
In recent papers she was focusing on the following fields of study:
Olgica Milenkovic focuses on Algorithm, Combinatorics, Discrete mathematics, Computer data storage and DNA.
Her work deals with themes such as Basis, Discriminative model and Convergence of random variables, which intersect with Algorithm.
Olgica Milenkovic usually deals with Combinatorics and limits it to topics linked to Upper and lower bounds and Distributed data store, Bandwidth, Steiner system and Order.
Olgica Milenkovic combines subjects such as Class and Pairwise comparison with her study of Discrete mathematics.
Her Computer data storage research incorporates elements of Image processing and Topology.
She works mostly in the field of Constraint, limiting it down to topics relating to Distribution and, in certain cases, Mathematical optimization, as a part of the same area of interest.
Between 2018 and 2021, her most popular works were:
- Detecting topological variations of DNA at single-molecule level (24 citations)
- DNA punch cards for storing data on native DNA sequences via enzymatic nicking (18 citations)
- Coded Trace Reconstruction (16 citations)
In her most recent research, the most cited papers focused on:
- Algorithm
- Statistics
- Algebra
Her main research concerns Algorithm, Topological graph theory, PageRank, DNA sequencing and DNA.
The Algorithm study combines topics in areas such as Multiset, Heuristics and Binary number.
Decoding methods and Error detection and correction is closely connected to Code rate in her research, which is encompassed under the umbrella topic of Multiset.
The various areas that Olgica Milenkovic examines in her Decoding methods study include Asymptotically optimal algorithm, Factorization and Discrete mathematics, Time complexity.
Her PageRank study also includes
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Theoretical computer science, Approximation algorithm, Cluster analysis and Correlation clustering most often made with reference to Graph,
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Data mining which intersects with area such as SIMPLE and Group testing.
Her DNA sequencing study also includes
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genomic DNA that intertwine with fields like Restriction enzyme, Computational biology and Computer data storage,
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Topology together with Electrophoresis, DNA damage, Sequence and Membrane.
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