Daniela Nitcheva

17 papers receiving 278 citations

Peers

Daniela Nitcheva
Comparison fields: 5 of 72
  • Statistics and Probability 52
  • Applied Microbiology and Biotechnology 9
  • Cancer Research 52
  • Management Science and Operations Research 37
  • Statistics, Probability and Uncertainty 18
Replace Xiaohong Qi with:
Xiaohong Qi China
C. L. Bird United States
Stéphane Lejeune Belgium
Martin Spendiff United Kingdom
Tetsuji Ohyama Japan
Giovanni Tafuri Italy
Byeong Yeob Choi United States
Valentina Aristarco Italy
Serena Mora Italy
Peter Kleist Germany
Daniela Nitcheva relative to Xiaohong Qi China Xiaohong Qi's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniela Nitcheva

Since Specialization
Citations

This map shows the geographic impact of Daniela Nitcheva'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 Daniela Nitcheva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Nitcheva more than expected).

Fields of papers citing papers by Daniela Nitcheva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela Nitcheva. 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 Daniela Nitcheva. The network helps show where Daniela Nitcheva may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniela Nitcheva, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniela Nitcheva Line = papers co-authored together Daniela Nitcheva links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 200956
2 200334
3 200734
4 200526
5 200425
6 200522
7 200718
8 200617
9 201613
10 200710
11 20089
12 20147
13 20056
14 20186
15 20032
16 20062
17 20101

About Daniela Nitcheva

Daniela Nitcheva is a scholar working on Management Science and Operations Research, Food Science, Statistics and Probability, Cancer Research and Pathology and Forensic Medicine, having authored 17 papers that have together received 288 indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (4 papers), Pesticide Residue Analysis and Safety (3 papers), Carcinogens and Genotoxicity Assessment (3 papers), Statistical Distribution Estimation and Applications (2 papers), Probabilistic and Robust Engineering Design (2 papers), Tea Polyphenols and Effects (2 papers), Phytoestrogen effects and research (2 papers) and Phytochemicals and Antioxidant Activities (1 paper). The work is most often cited by research in Statistics and Probability (52 citations), Applied Microbiology and Biotechnology (9 citations), Cancer Research (52 citations), Management Science and Operations Research (37 citations) and Statistics, Probability and Uncertainty (18 citations). Daniela Nitcheva has collaborated with scholars based in United States, Norway and Oman. Frequent co-authors include Walter W. Piegorsch, R. Webster West, Michael J. Wargovich, Suresh R. Volate, Ala Issa, Theresa J. Smith, Stephanie J. Muga, Joan E. Cunningham, James R. Hébert and Ralph L. Kodell. Their work appears in journals such as Biometrics, Carcinogenesis, Maternal and Child Health Journal, Journal of Statistical Computation and Simulation and Environmental and Ecological Statistics.

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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