{"681762":{"#nid":"681762","#data":{"type":"event","title":"Ph.D. Proposal Oral Exam - Wei Chun Wang","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003E\u003Cem\u003EEnergy and Area Efficient Analog Computing-in-Memory Systems: From Device-Circuit Co-Design to RF Signal Processing Applications\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDr. Mukhopadhyay, Advisor\u003C\/p\u003E\u003Cp\u003EDr. Datta, Chair\u003C\/p\u003E\u003Cp\u003EDr. Romberg\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis research explores advanced sensor array technologies, addressing the challenges of energy consumption and data processing in next-generation high-bandwidth RF arrays. It introduces an analog computing-in-memory (ACIM) framework utilizing advanced mixed-mode matrix multiplication to extract low-dimensional features directly from high-dimensional analog inputs, significantly reducing data rates while maintaining accuracy. At the circuit level, an SRAM-based ACIM architecture in 28nm CMOS is developed to perform current-domain multiply-and-accumulate (MAC) operations without requiring on-chip capacitors. Additionally, a separate study enhances ACIM design using 1-transistor Fe-FinFET cells with FinFET-based peripherals, improving linearity, reducing variations, and increasing power and area efficiency. Another research effort focuses on FinFET SRAM-based ACIM at cryogenic temperatures, leveraging higher on-to-off current ratios and improved transconductance characteristics to enhance power efficiency and reduce energy-delay product (EDP). At the system level, an adaptive ACIM framework incorporating a modified Oja\u2019s algorithm dynamically optimizes the compression matrix based on real-time signal subspace estimates. This approach successfully compresses signals from 1024 antenna elements into 64 channels while maintaining accuracy, marking a significant step toward practical, power-efficient, high-resolution sensing platforms.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Energy and Area Efficient Analog Computing-in-Memory Systems: From Device-Circuit Co-Design to RF Signal Processing Applications"}],"uid":"28475","created_gmt":"2025-04-14 11:58:53","changed_gmt":"2025-04-14 12:00:24","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-04-14T11:30:00-04:00","event_time_end":"2025-04-14T13:30:00-04:00","event_time_end_last":"2025-04-14T13:30:00-04:00","gmt_time_start":"2025-04-14 15:30:00","gmt_time_end":"2025-04-14 17:30:00","gmt_time_end_last":"2025-04-14 17:30:00","rrule":null,"timezone":"America\/New_York"},"location":"Room 1315, Klaus","extras":[],"groups":[{"id":"434371","name":"ECE Ph.D. Proposal Oral Exams"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"},{"id":"1808","name":"graduate students"}],"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":""}}}