Sandi Baressi Šegota: h-index, Total Citations, and Citation Map
Sandi Baressi Šegota's h-index is 20 (39 i10-index, 1,676+ total citations across 153+ publications) according to Google Scholar as of June 2026. Sandi Baressi Šegota is affiliated with Faculty of Informatics, Juraj Dobrila University of Pula.
Sandi Baressi Šegota is a researcher affiliated with Faculty of Informatics, Juraj Dobrila University of Pula, specializing in Robotics, Artificial Intelligence, Machine Learning. Their work has been cited 1,676 times. This profile visualizes their global influence, highlighting strong citation networks in Croatia.
Sandi Baressi Šegota's Citation Metrics
Bibliometric impact based on 153 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 20
- i10-Index
- 39
- Total Citations
- 1,676
- Citing Countries
- 45
As of June 2026.
Sandi Baressi Šegota has an h-index of 20 and 1,676 total citations across 153 publications, with research cited by institutions in 45 countries.
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Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron
2020285
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
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Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher developed a multilayer perceptron model to simulate COVID-19 infection spread, establishing a computational framework that has garnered significant independent academic attention.
The researcher developed evolutionary algorithm-based path planning optimization methods for six-degree-of-freedom robotic manipulators, establishing a foundational approach widely adopted by independent scholars.
The researcher developed a hybrid forecasting model integrating stationary wavelet transform with bidirectional LSTM to address stock price volatility during the COVID-19 pandemic.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Sandi Baressi Šegota's research
Sandi Baressi Šegota is a researcher in Robotics, Artificial Intelligence and Machine Learning at Faculty of Informatics, Juraj Dobrila University of Pula. Their work has been cited 1,676 times across 153 publications (h-index 20), according to Google Scholar.
Their most-cited work, “Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron” (2020), has accumulated 285 citations. Other influential works include “Path planning optimization of six-degree-of-freedom robotic manipulators using evolutionary algorithms” (2020) with 107 citations and “Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory” (2020) with 100 citations.
Citations of Sandi Baressi Šegota's research come primarily from Croatia, India and United States, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
