Peng-Hung Tsai Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

University of Arkansas at Little Rock

faculty

2 h-index 10 pubs 27 cited

Research Areas

Technology Forecasting Trend Extrapolation Space Exploration Satellite Lifetime Prediction Advanced Neural Network Applications Health Disparities and Outcomes Cancer-related molecular mechanisms research

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OverviewAI-generated summary

Peng-Hung Tsai's research focuses on quantitative technology forecasting and trend extrapolation methods, particularly as applied to the lifespan and development of space exploration technologies. He has investigated methods for predicting future satellite lifetimes using historical data and explored the integration of recent data to analyze trends in areas such as kidney cancer survival. His work also examines the nature of technological progress, questioning whether it follows a random walk pattern, using data from space travel as a case study.

Tsai has published on the forecasting of technology using satellite lifetime data and the application of Long Short-Term Memory (LSTM) neural networks for analyzing trends in space exploration vessels. His scholarship metrics include an h-index of 2, with 10 total publications and 27 total citations. He has established collaborative relationships with researchers including Daniel Berleant (10 shared publications), Richard S. Segall (7 shared publications), Michael Howell (4 shared publications), and Michael Bauer (1 shared publication).

Metrics

h-index: 2
Publications: 10
Citations: 27

Selected Publications

Start Time End Time Integration (STETI): Method for Including Recent Data to Analyze Trends in Kidney Cancer Survival (2025) DOI
Predicting Future Participation of Women in Space by Analyzing Past Trends (2024) DOI
Quantitative Technology Forecasting: A Review of Trend Extrapolation Methods (2023) DOI
Future Satellite Lifetime Prediction From the Historical Trend in Satellite Half-Lives (2022) DOI
Future Satellite Lifetime Prediction From the Historical Trend in Satellite Half-Lives (2022) DOI
Is technological progress a random walk? Examining data from space travel (2021) DOI
Spacecraft for Deep Space Exploration: Combining Time and Budget to Model the Trend in Lifespan (2021) DOI