Anton Rozhkov
Biographic Data
| ID | 6313019 |
|---|---|
| NAME | Anton Rozhkov |
| GIVEN NAMES | Anton |
| FAMILY NAME | Rozhkov |
| SIGNATURE | ROZHKOV A |
| AFFILIATIONS | University of Illinois Urbana-Champaign |
| ORCID | 0000-0002-7814-1538 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Who uses power, who gets microgrids? Uncovering regional trends in energy consumption and microgrid deployment in California
Identifying leverage points for sustainable transitions in urban – rural systems
Effectiveness variation of different census outreach activities
Harnessing European policies for energy planning in Illinois
A machine learning framework to assess the impact of the Covid-19 pandemic on electricity consumption patterns
Intrastate applicability of National Census Response Rate Models
For the 2020 Census, the U.S. Census Bureau developed the Low Response Score (LRS) to predict census self‐response participation. Based on a previous hard‐to‐count metric, which accounts for people who are difficult to survey or count, the LRS was undoubtedly an improvement over previous census effort. However, census response behaviour can be sensitive to inter‐ and intrastate locational and socioeconomic differences; in other words, geographic …
Intrastate applicability of National Census Response Rate Models
For the 2020 Census, the U.S. Census Bureau developed the Low Response Score (LRS) to predict census self‐response participation. Based on a previous hard‐to‐count metric, which accounts for people who are difficult to survey or count, the LRS was undoubtedly an improvement over previous census effort. However, census response behaviour can be sensitive to inter‐ and intrastate locational and socioeconomic differences; in other words, geographic …
Effectiveness variation of different census outreach activities
Harnessing European policies for energy planning in Illinois
A machine learning framework to assess the impact of the Covid-19 pandemic on electricity consumption patterns
Identifying leverage points for sustainable transitions in urban – rural systems
Who uses power, who gets microgrids? Uncovering regional trends in energy consumption and microgrid deployment in California
Economics (5 works) · Geography (4 works) · Artificial Intelligence (3 works) · Computer Science (3 works) · Population (3 works) · Sociology (3 works) · Business (2 works) · Census (2 works) · Cluster analysis (2 works) · Data-Driven Disease Surveillance (2 works)