{"624956":{"#nid":"624956","#data":{"type":"event","title":"GVU Center Brown Bag: Polo Chau \u0022Towards Secure and Interpretable AI...\u0022","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EWe have witnessed tremendous growth in Artificial Intelligence (AI) and machine learning (ML) recently. However, research shows that AI and ML models are often vulnerable to adversarial attacks, and their predictions can be difficult to understand, evaluate and ultimately act upon.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDiscovering real-world vulnerabilities of deep neural networks and countermeasures to mitigate such threats has become essential to successful deployment of AI in security settings. We present our joint works with Intel which include the first targeted physical adversarial attack (ShapeShifter) that fools state-of-the-art object detectors; a fast defense (SHIELD) that removes digital adversarial noise by stochastic data compression; and interactive systems (ADAGIO and MLsploit) that further democratize the study of adversarial machine learning and facilitate real-time experimentation for deep learning practitioners.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFinally, we also present how scalable interactive visualization can be used to amplify people\u0026rsquo;s ability to understand and interact with large-scale data and complex models. We sample from projects where interactive visualization has provided key leaps of insight, from increased model interpretability (Gamut with Microsoft Research), to model explorability with models trained on millions of instances (ActiVis deployed with Facebook), increased usability for non-experts about state-of-the-art AI (GAN Lab open-sourced with Google Brain; went viral!), and our latest work Summit, an interactive system that scalably summarizes and visualizes what features a deep learning model has learned and how those features interact to make predictions. We conclude by highlighting the next visual analytics research frontiers in AI.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESpeaker Bio:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EPolo\u0026nbsp;Chau\u0026nbsp;is an Associate Professor of Computing at Georgia Tech. He co-directs Georgia Tech\u0026#39;s MS Analytics program. His research group bridges machine learning and visualization to synthesize scalable interactive tools for making sense of massive datasets, interpreting complex AI models, and solving real world problems in cybersecurity, human-centered AI, graph visualization and mining, and social good. His Ph.D. in Machine Learning from Carnegie Mellon University won CMU\u0026#39;s Computer Science Dissertation Award, Honorable Mention. He received awards and grants from NSF, NIH, NASA, DARPA, Intel (Intel Outstanding Researcher), Symantec, Google, Nvidia, IBM, Yahoo, Amazon, Microsoft, eBay, LexisNexis; Raytheon Faculty Fellowship; Edenfield Faculty Fellowship; Outstanding Junior Faculty Award; The Lester Endowment Award; Symantec fellowship (twice); Best student papers at SDM\u0026#39;14 and KDD\u0026#39;16 (runner-up); Best demo at SIGMOD\u0026#39;17 (runner-up); Chinese CHI\u0026#39;18 Best paper. His research led to open-sourced or deployed technologies by Intel (for ISTC-ARSA: ShapeShifter, SHIELD, ADAGIO, MLsploit), Google, Facebook, Symantec (Polonium, AESOP protect 120M people from malware), and Atlanta Fire Rescue Department. His security and fraud detection research made headlines. Website:\u0026nbsp;\u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/~dchau\/\u0022\u003Ehttps:\/\/www.cc.gatech.edu\/~dchau\/\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.gvu.gatech.edu\/events\/upcoming\u0022\u003ESchedule of Brown Bag Speakers Fall 2019\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis seminar will present joint works with Intel that\u0026nbsp;democratizes the study of adversarial machine learning and facilitates real-time experimentation for deep learning practitioners.\u0026nbsp;We conclude by highlighting the next visual analytics research frontiers in AI.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"This seminar will present real-time experimentation for deep learning practitioners and highlight the next visual analytics research frontiers in AI."}],"uid":"33749","created_gmt":"2019-08-21 20:56:49","changed_gmt":"2019-08-26 14:55:00","author":"Dorie Taylor","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-08-29T12:30:00-04:00","event_time_end":"2019-08-29T14:00:00-04:00","event_time_end_last":"2019-08-29T14:00:00-04:00","gmt_time_start":"2019-08-29 16:30:00","gmt_time_end":"2019-08-29 18:00:00","gmt_time_end_last":"2019-08-29 18:00:00","rrule":null,"timezone":"America\/New_York"},"extras":["free_food"],"hg_media":{"356941":{"id":"356941","type":"image","title":"Polo Chau compressed","body":null,"created":"1449245762","gmt_created":"2015-12-04 16:16:02","changed":"1475895091","gmt_changed":"2016-10-08 02:51:31","alt":"Polo Chau compressed","file":{"fid":"201424","name":"polo-chau.jpg","image_path":"\/sites\/default\/files\/images\/polo-chau_0.jpg","image_full_path":"http:\/\/www.tlwarc.hg.gatech.edu\/\/sites\/default\/files\/images\/polo-chau_0.jpg","mime":"image\/jpeg","size":12506,"path_740":"http:\/\/www.tlwarc.hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/images\/polo-chau_0.jpg?itok=tq_pML_R"}}},"media_ids":["356941"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"1299","name":"GVU Center"},{"id":"69599","name":"IPaT"},{"id":"50876","name":"School of Interactive Computing"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:gvu@cc.gatech.edu\u0022\u003Egvu@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E\r\n","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}