{"692930":{"#nid":"692930","#data":{"type":"event","title":"CRA SEMINAR | Chen Chen | GT Alumni | Host: Jiapeng Gao","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E Chen Chen\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EHost: \u003C\/strong\u003EJiapeng Gao\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle: Title\u003C\/strong\u003E: Machine Learning Across Scales: From Hidden Exoplanets to Efficient Model Training\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\u003Cp\u003ENon-transiting planets can remain hidden while leaving dynamical signals in the transit timing variations (TTVs) of observed\u0026nbsp;planets. DeepTTV provides a machine learning (ML) approach to this inverse problem, using N-body simulations to generate training data for a neural network that combines recurrent and Transformer architectures to infer the mass and orbital properties of unseen planetary companions. In the first part of this talk, I will discuss DeepTTV. In the second part, I will introduce my current work in industry on improving the efficiency of large-scale ML training, including directions such as transfer learning and improving computational resource utilization.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u003C\/p\u003E\u003Cp\u003ENon-transiting planets can remain hidden while leaving dynamical signals in the transit timing variations (TTVs) of observed\u0026nbsp;planets. DeepTTV provides a machine learning (ML) approach to this inverse problem, using N-body simulations to generate training data for a neural network that combines recurrent and Transformer architectures to infer the mass and orbital properties of unseen planetary companions. In the first part of this talk, I will discuss DeepTTV. In the second part, I will introduce my current work in industry on improving the efficiency of large-scale ML training, including directions such as transfer learning and improving computational resource utilization.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"CRA SEMINAR | Chen Chen | GT Alumni | Host: Jiapeng Gao"}],"uid":"30957","created_gmt":"2026-09-30 12:15:04","changed_gmt":"2026-09-30 12:19:54","author":"Shaun Ashley","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-15T15:30:30-04:00","event_time_end":"2026-10-15T16:30:00-04:00","event_time_end_last":"2026-10-15T16:30:00-04:00","gmt_time_start":"2026-10-15 19:30:30","gmt_time_end":"2026-10-15 20:30:00","gmt_time_end_last":"2026-10-15 20:30:00","rrule":null,"timezone":"America\/New_York"},"location":"College of Computing Building (CCB) Rm:103","extras":[],"hg_media":{"681302":{"id":"681302","type":"image","title":"chenchen-10.15.26.jpg","body":null,"created":"1790770727","gmt_created":"2026-09-30 12:18:47","changed":"1790770727","gmt_changed":"2026-09-30 12:18:47","alt":"chenchen-10.15.26.jpg","file":{"fid":"265673","name":"chenchen-10.15.26.jpg","image_path":"\/sites\/default\/files\/2026\/09\/30\/chenchen-10.15.26.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/30\/chenchen-10.15.26.jpg","mime":"image\/jpeg","size":12120,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/30\/chenchen-10.15.26.jpg?itok=NTM6P1UB"}}},"media_ids":["681302"],"groups":[{"id":"126011","name":"School of Physics"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}