{"689337":{"#nid":"689337","#data":{"type":"event","title":"PhD Defense by Veronica Margot Paez","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESchool of Civil and Environmental Engineering\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EPh.D. Thesis Defense Announcement\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECHARACTERIZING AND MODELING ENERGY FLEXIBILITY AND DECARBONIZATION POTENTIAL THROUGH METRICS, HEURISTICS, AND FORECASTING IN CRYPTOCURRENCY AND HIGH-PERFORMANCE DATA CENTERS\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBy\u003C\/strong\u003E \u003Cstrong\u003EVeronica Margot Paez\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAdvisor:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. John E. Taylor\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee Members:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. John E. Taylor (CEE), Dr. Susan Burns (CEE), Dr. Joe F . Bozeman III (CEE), Dr. Neda\u0026nbsp; Mohammadi (CEE), Dr. Troy Cross (Reed College)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;\u003Cstrong\u003E April, 20, 2026, 1PM\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ELocation: \u0026nbsp;SEB 122 \/\u0026nbsp;\u003C\/strong\u003E\u003Ca href=\u0022https:\/\/shorturl.at\/slOVK\u0022\u003Ehttps:\/\/shorturl.at\/slOVK\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003EAcross three complementary studies, an empirically grounded, multi-scale\u003Cbr\u003Eframework is developed to measure and reduce the energy and emissions impacts\u003Cbr\u003Eof flexible high-performance computing (HPC) and cryptocurrency data center\u003Cbr\u003E(CDC) loads. Using novel hourly electricity data from 21 North American\u003Cbr\u003Ecryptocurrency data centers matched to locational marginal emissions, the analysis\u003Cbr\u003Eshows that emissions outcomes depend not simply on whether facilities curtail, but\u003Cbr\u003Eon when, how often, and how deeply they do so, quantified through engineered\u003Cbr\u003Emetrics of curtailment dynamics and emissions alignment. A data-light behavioral\u003Cbr\u003Esignature\u2014a Kneedle-derived knee-threshold\u2014is then introduced that separates\u003Cbr\u003Eboth HPC and CDC facilities into statistically distinct operational types and provides a practical proxy for benchmarking flexibility and mitigation performance using only time-series energy data. Finally, site-level behavior is connected to system-level drivers through a block-level cryptocurrency network simulator that endogenizes miner economics, hardware profitability, difficulty adjustment, and halving dynamics to hindcast and forecast hashrate, revenue, and energy under alternative scenarios. While the empirical case studies focus on cryptocurrency data centers, the broader framework speaks to a wider class of flexible compute loads, including emerging HPC and AI facilities whose power demand is increasingly shaping grid planning, emissions accounting, and infrastructure investment. Together, the studies link operational heterogeneity, behavioral signatures, and protocol-driven market incentives, showing that the energy and climate impacts of large-scale compute are not fixed properties of demand, but emergent outcomes of facility behavior, grid conditions, and system design. This framework provides a stronger foundation for emissions measurement, scenario analysis, and policy design for lower-carbon flexible compute loads.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ECHARACTERIZING AND MODELING ENERGY FLEXIBILITY AND\u003Cbr\u003EDECARBONIZATION POTENTIAL THROUGH METRICS, HEURISTICS, AND\u003Cbr\u003EFORECASTING IN CRYPTOCURRENCY AND HIGH-PERFORMANCE DATA\u003Cbr\u003ECENTERS\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"CHARACTERIZING AND MODELING ENERGY FLEXIBILITY AND DECARBONIZATION POTENTIAL THROUGH METRICS, HEURISTICS, AND FORECASTING IN CRYPTOCURRENCY AND HIGH-PERFORMANCE DATA CENTERS"}],"uid":"27707","created_gmt":"2026-04-01 16:00:46","changed_gmt":"2026-04-01 16:01:30","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-04-20T13:00:00-04:00","event_time_end":"2026-04-20T15:00:00-04:00","event_time_end_last":"2026-04-20T15:00:00-04:00","gmt_time_start":"2026-04-20 17:00:00","gmt_time_end":"2026-04-20 19:00:00","gmt_time_end_last":"2026-04-20 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"SEB 122","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}