Nevena Lazic

41 total papers · 973 total citations
15 papers, 398 citations indexed

About

Nevena Lazic is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nevena Lazic has authored 15 papers receiving a total of 398 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Management Science and Operations Research and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nevena Lazic's work include Reinforcement Learning in Robotics (5 papers), Data Quality and Management (4 papers) and Advanced Bandit Algorithms Research (3 papers). Nevena Lazic is often cited by papers focused on Reinforcement Learning in Robotics (5 papers), Data Quality and Management (4 papers) and Advanced Bandit Algorithms Research (3 papers). Nevena Lazic collaborates with scholars based in United States, Canada and United Kingdom. Nevena Lazic's co-authors include Parham Aarabi, Brendan J. Frey, Dani Yogatama, Daniel Gillick, Fernando Pereira, Amarnag Subramanya, Inmar E. Givoni, Amir Globerson, Soumen Chakrabarti and Csaba Szepesvári and has published in prestigious journals such as Fusion Engineering and Design, Transactions of the Association for Computational Linguistics and arXiv (Cornell University).

In The Last Decade

Nevena Lazic

15 papers receiving 373 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Nevena Lazic	255	84	82	45	36	15	398
Haoran Tang	270 1.1×	63 0.8×	51 0.6×	59 1.3×	36 1.0×	21	377
Teck Wee Chua	204 0.8×	95 1.1×	61 0.7×	52 1.2×	14 0.4×	12	382
Saeed Masoudnia	213 0.8×	125 1.5×	58 0.7×	22 0.5×	23 0.6×	18	432
Niao He	196 0.8×	48 0.6×	40 0.5×	62 1.4×	38 1.1×	29	379
Ronnie Johansson	168 0.7×	51 0.6×	61 0.7×	35 0.8×	30 0.8×	19	342
Shuxia Lu	196 0.8×	114 1.4×	48 0.6×	48 1.1×	57 1.6×	18	342
B.W. Schmeiser	97 0.4×	44 0.5×	145 1.8×	37 0.8×	17 0.5×	17	359
Yaxin Liu	318 1.2×	31 0.4×	84 1.0×	56 1.2×	18 0.5×	28	409
Fernando Gaxiola	245 1.0×	43 0.5×	59 0.7×	108 2.4×	12 0.3×	23	407
Emilio Corchado	173 0.7×	59 0.7×	25 0.3×	39 0.9×	18 0.5×	24	352

Countries citing papers authored by Nevena Lazic

Since Specialization

Citations

This map shows the geographic impact of Nevena Lazic's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nevena Lazic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nevena Lazic more than expected).

Fields of papers citing papers by Nevena Lazic

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nevena Lazic. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nevena Lazic. The network helps show where Nevena Lazic may publish in the future.

Co-authorship network of co-authors of Nevena Lazic

This figure shows the co-authorship network connecting the top 25 collaborators of Nevena Lazic. A scholar is included among the top collaborators of Nevena Lazic based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nevena Lazic. Nevena Lazic is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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