{"id":8,"date":"2017-03-28T15:38:36","date_gmt":"2017-03-28T19:38:36","guid":{"rendered":"https:\/\/suchisaria.jhu.edu\/?page_id=8"},"modified":"2023-01-08T17:48:05","modified_gmt":"2023-01-08T22:48:05","slug":"home","status":"publish","type":"page","link":"https:\/\/suchisaria.jhu.edu\/","title":{"rendered":"Home"},"content":{"rendered":"<p><title>Suchi Saria \u2013 Machine Learning, Computational Health Informatics<\/title><\/p>\n<style>\n\t*{\n\t\tpadding: 0;\n\t\tmargin: 0;\n\t\tfont-family: Georgia, \"Times New Roman\", Times, serif;\n\t}\n\t.container{\n\t\tmax-width: 1024px;\n\t\tmargin: 0 auto;\n\t}\n\t.main_s1{\n\t\tdisplay: flex;\n\t\tjustify-content: space-between;\n\t}\n\t.main_s1 img{\n                object-fit: cover;\n\t\twidth: 100%;\n\t}\n\t.main_s1_right{\n\t\tpadding-left: 20px;\n\t}\n\t.s1_title{\n\t\tfont-size: 28px;\n\t\tfont-weight: bold;\n\t}\n\t.s1_subtitle{\n\t\tfont-size: 20px;\n\t\tfont-weight: bold;\n\t}\n\t.s1_uni{\n\t\tfont-size: 18px;\n\t\tpadding: 5px 0;\n\t}\n\t.summary_link{\n\t\tpadding: 10px 0;\n\t}\n\t.main_s1_right a{\n\t\ttext-decoration: none;\n\t}\n\tspan{\n\t\tfont-weight: bold;\n\t}\n\t.other{\n\t\tpadding: 30px 0;\n\t}\n\ta{\n\t\ttext-decoration: none;\n\t\tcolor: #0000EE;\n\t}\n\ta:hover{\n\t\tcolor: #E6AC27;\n\t}\n\t.formal{\n\t\tpadding-bottom: 30px;\n\t}\n\t.research div{\n\t\tpadding-bottom: 30px;\n\t}\n\t.honor_title{\n\t\tfont-size: 20px;\n\t\tfont-weight: bold;\n\t}\n\t.honor_item{\n\t\tpadding: 10px 0;\n\t\tdisplay: flex;\n\t}\n\t.honor_year{\n\t\tpadding-right: 20px;\n\t}\n\t.public_title{\n\t\tfont-size: 20px;\n\t\tpadding: 10px 0;\n\t}\n\t.public_item{\n\t\tpadding: 8px 0;\n\t}\n\t.green_txt{\n\t\tcolor: lawngreen;\n\t}\n\t.red_txt{\n\t\tcolor: red;\n\t}\n\t.public_intend{\n\t\tpadding-left: 50px;\n\t}\n\t.national{\n\t\tpadding: 40px 0;\n\t}\n\t.youtube iframe{\n\t\twidth: 100%;\n\t\theight: 500px;\n\t}\n\t.machine_title, .alumni_title{\n\t\tfont-size: 20px;\n\t\tfont-weight: bold;\n\t\tpadding: 20px 0;\n\t}\n\t.machine_item, .alumni_item{\n\t\tpadding: 5px 0;\n\t}\n\t.news_title{\n\t\tfont-weight: bold;\n\t\tpadding: 20px 0;\n\t}\n\t.teach_title{\n\t\tfont-weight: bold;\n\t\tpadding: 20px 0;\n\t}\n\t.teach_item{\n\t\tpadding: 5px 0;\n\t}\n\t.faq_title{\n\t\tfont-size: 20px;\n\t\tfont-weight: bold;\n\t\tpadding: 20px 0;\n\t}\n\t.faq_item{\n\t\tpadding: 5px 0;\n\t}<\/p>\n<p>\tfooter{\n\t\tfont-size: 12px;\n\t\tpadding: 10px;\n\t\theight: 50px;\n\t\tmargin-top: 50px;\n\t\tdisplay: flex;\n\t\tjustify-content: center;\n\t\talign-items: center;\n\t\tcolor: #AAAAAA;\n\t\tbackground-color: #131211;\n\t\tborder-color: rgba(255,255,255,.1);\n\t}\n\tfooter a{\n\t\tcolor: #BF4D28;\n\t\tpadding: 0 5px;\n\t\ttext-decoration: none;\n\t}\n\tfooter a:hover{\n\t\tcolor: #E6AC27;\n\t}<\/p>\n<p>\t@media(max-width: 1024px){\n\t\t.container{\n\t\t\tpadding: 0 20px;\n\t\t}\n\t}\n\t@media(max-width: 1024px){\n\t\t.main_s1{\n\t\t\tflex-direction: column;\n\t\t\talign-items: center;\n\t\t}\n\t\t.main_s1_right{\n\t\t\tpadding-left: 0;\n\t\t}\n\t}\n\t@media(max-width: 560px){\n\t\t.main_s1 img{\n\t\t\twidth: 100%;\n\t\t}\n\t\t.youtube iframe{\n\t\t\theight: 200px;\n\t\t}\n\t}\n<\/style>\n<div class=\"main\">\n<div class=\"container\">\n<div class=\"main_s1\">\n\t\t\t\t<img decoding=\"async\" src=\"https:\/\/suchisaria.jhu.edu\/wp-content\/uploads\/2023\/01\/JHU9406_b-300x200.jpg\" alt=\"Suchi Saria\"><\/p>\n<div class=\"main_s1_right\">\n<div class=\"s1_title\">Suchi Saria<\/div>\n<div class=\"s1_subtitle\">John C. Malone Associate Professor<\/div>\n<div class=\"s1_uni\">Johns Hopkins University<\/div>\n<div class=\"summary_link\">\n\t\t\t\t\t\t<a href=\"http:\/\/www.cs.jhu.edu\/research\">Department of Computer Science<\/a><\/div>\n<div class=\"summary_link\">\n\t\t\t\t\t\t<a href=\"https:\/\/engineering.jhu.edu\/ams\/\">Department of Applied Math &amp; Statistics<\/a><\/div>\n<div class=\"summary_link\">\n\t\t\t\t\t\t<a href=\"http:\/\/www.jhsph.edu\/about\/\">Department of Health Policy &amp; Management<\/a><\/div>\n<div class=\"s1_uni\">\n\t\t\t\t\t\tResearch Director, Malone Center for Engineering and Healthcare<\/div>\n<div class=\"s1_uni\">\n\t\t\t\t\t\t<span>Contact<\/span>: prefix@suffix where prefix=ssaria and suffix=cs.jhu.edu<\/div>\n<div class=\"s1_uni\">\n\t\t\t\t\t\t<span>Twitter<\/span>: Follow @suchisaria<\/div>\n<\/div>\n<\/div>\n<div class=\"other\">\n\t\t\t\t<span>Other Affiliations:<\/span><a href=\"https:\/\/www.minds.jhu.edu\/\"> Mathematical Institute for Data Science (MINDS),<\/a><a href=\"http:\/\/www.icm.jhu.edu\/\">Institute for Computational Medicine,<\/a><a href=\"https:\/\/www.lcsr.jhu.edu\/Main_Page\">Laboratory for Computational Sensing and Robotics, <\/a><a href=\"http:\/\/www.hopkinsmedicine.org\/armstrong_institute\/\">Armstrong Institute for Patient Safey and Quality,<\/a><a href=\"http:\/\/www.jhsph.edu\/research\/centers-and-institutes\/johns-hopkins-center-for-population-health-information-technology\/\">Center for Population Health Information Technology,<\/a>and <a href=\"http:\/\/www.clsp.jhu.edu\/\">Center for Language and Speech Processing<\/a><\/div>\n<div class=\"formal\">\n\t\t\t\t<span>Formal Bio:<\/span>See <a href=\"https:\/\/suchisaria.jhu.edu\/?page_id=179\">here<\/a><\/div>\n<div class=\"research\">\n<div>\n\t\t\t\t\t<span>Research Interests<\/span>: At Hopkins, I direct the Machine Learning and Healthcare Lab at Johns Hopkins University. We are interested in enabling new classes of diagnostic and treatment planning tools for healthcare\u2014tools that use artificial intelligence and statistical machine learning techniques to tease out subtle information from \u201cmessy\u201d observational datasets, and provide reliable inferences for individualizing care decisions. My work spans the continuum from machine learning foundations and theory to demonstrating novel applications in the real-world to informing policy around safe ML adoption.<\/div>\n<div>\n\t\t\t\t\tPrior to joining Johns Hopkins, I did my PhD at Stanford with the brilliant Dr. Daphne Koller.  I also spent a year at Harvard University collaborating with wonderful healthcare informatics researchers Dr. Ken Mandl and Dr. Zak Kohane as a NSF Computing Innovation Fellow.  Prior to that, I did research with reinforcement learning pioneers Dr. Sridhar Madhavan and Dr. Andy Barto at UMass. While in the valley, I also spent time as an early employee at <a href=\"http:\/\/www.teradata.com\/Teradata-Aster\/overview\/\">Aster Data Systems<\/a> , a big data startup acquired by Teradata.<\/div>\n<div>\n\t\t\t\t\tAt the end of 2018, we spun out <a href=\"https:\/\/www.bayesianhealth.com\/\">Bayesian Health<\/a>, a health AI startup focused on dramatically improving health outcomes and provider experience. I also sit on advisory boards of several organizations focused on innovative uses of AI or analytics to bring significant societal benefit (see <a href=\"https:\/\/www.linkedin.com\/in\/suchisaria\/\">LinkedIn<\/a>  for a partial list).<\/div>\n<div>\n\t\t\t\t\tExample press on our lab\u2019s work:<br \/>\nRecent: <a href=\"https:\/\/www.bayesianhealth.com\/press-coverage\/\">Press list<\/a><br \/>\n2018 and prior: <a href=\"http:\/\/www.nsf.gov\/news\/special_reports\/science_nation\/predictivemedicine.jsp\">NSF Science Nation<\/a>, <a href=\"http:\/\/www.baltimoresun.com\/health\/bs-hs-predicting-sepsis-20150806-story.html\">Baltimore Sun<\/a>, <a href=\"http:\/\/spectrum.ieee.org\/tech-talk\/biomedical\/diagnostics\/a-computer-that-can-sniff-out-septic-shock?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+IeeeSpectrum+%28IEEE+Spectrum%29\">IEEE Spectrum<\/a>, <a href=\"http:\/\/hub.jhu.edu\/magazine\/2015\/spring\/individualized-health-through-big-data\">Hopkins Magazine<\/a>, <a href=\"http:\/\/news.sciencemag.org\/health\/2010\/09\/new-model-predicts-complications-preemies\">Science<\/a>, <a href=\"http:\/\/eng.jhu.edu\/wse\/magazine-winter-14\/item\/engineering-a-smarter-icu\/\">Hopkins Engineering Magazine<\/a>, <a href=\"http:\/\/www.healthcareitnews.com\/news\/electronic-tool-accurately-assesses-disease-risk-preterm-infants\">Healhcare IT News<\/a>, <a href=\"http:\/\/www.popsci.com\/predictive-model-identifies-patients-who-might-go-septic-shock\">Popular Science<\/a>, <a href=\"http:\/\/www.nsf.gov\/cise\/csbytes\/newsletter\/vol2\/vol2i2.html\">NSF Bits and Bytes<\/a>, <a href=\"https:\/\/med.stanford.edu\/news\/all-news\/2010\/09\/researchers-design-more-accurate-method-of-determining-premature-infants-risk-of-illness.html\">Stanford Medicine<\/a>, <a href=\"http:\/\/www.post-gazette.com\/business\/tech-news\/2016\/10\/14\/Nation-s-leading-thinkers-gather-at-Frontiers-Conference-at-Pitt-CMU\/stories\/201610120195\">Pittsburgh Post-Gazette on the Frontiers meeting<\/a>, <a href=\"http:\/\/www.thetalkingmachines.com\/blog\/2016\/3\/10\/ivpi7nd68oln8kk9lz2o4nyibvfyqd\">Talking Machines podcast<\/a>, <a href=\"http:\/\/www.popsci.com\/brilliant-10-2016\"> Popular Science<\/a>, and <a href=\"https:\/\/tedxboston.org\/speaker\/saria\">TEDxBoston<\/a>.<\/div>\n<div>\n\t\t\t\t\t<span>PhD applicants:<\/span><br \/>\nIf you\u2019re interested in working with me, please apply to the Hopkins program and call me out as a potential advisor explaining why. I get a very high volume of emails from students so I cannot respond to each one individually. If you haven\u2019t heard from me, please don\u2019t assume it to mean lack of interest. <a href=\"http:\/\/engineering.jhu.edu\/academics\/admissions\/\">Apply here<\/a>.<br \/>\n<span>Postdoc applicants<\/span>: Over the last 4 years, the lab has done very exciting work in ML\/AI Safety. It has led to 15+ papers (at NeurIPS\/ICML\/AISTATS\/Nature Medicine\/NEJM) describing new methods for learning, evaluation, and real-world monitoring. Further, this work has been referenced by several regulatory bodies including the FDA in designing frameworks for AI-based medical devices. I\u2019m accepting postdocs who are interested in advancing the theory, practice and policy around real-world monitoring. If you\u2019re interested, please send me a note.<\/div>\n<\/div>\n<div class=\"honor\">\n<div class=\"honor_title\">Selected Honors, Awards and Notable Events (only lists awards prior to 2018):<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2018<\/div>\n<div class=\"honor_txt\">Honored to be named a Sloan Research Fellow. To read more about this highly competitive award, see <a href=\"https:\/\/www.cs.jhu.edu\/2018\/02\/15\/suchi-saria-sloan-research-fellow\/\">here<\/a>, <a href=\"https:\/\/hub.jhu.edu\/2018\/02\/15\/sloan-research-fellows-2018\/\">here<\/a>, and <a href=\"https:\/\/sloan.org\/fellowships\/2018-Fellows\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2018<\/div>\n<div class=\"honor_txt\">Selected as one of World Economic Forum\u2019s Young Global Leader. To learn more about this recognition, see <a href=\"https:\/\/sloan.org\/fellowships\/2018-Fellows\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2017<\/div>\n<div class=\"honor_txt\">In National Science Foundation (NSF) Director Dr. France Cordova\u2019s testimony to the Commerce, Justice and Science Appropriations Committee, our lab\u2019s work was one of four pieces of research presented across all areas of NSF (two from CISE) on discussing the NSF budget. It\u2019s a privilege be able to help make the case for increased funding for scientific innovation and research.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2017<\/div>\n<div class=\"honor_txt\">Invited tutorial at Uncertainty in Artificial Intelligence (UAI) on machine learning and counterfactual reasoning for \u201cPersonalized\u201d Decision-Making in Healthcare. More <a href=\"http:\/\/www.auai.org\/uai2017\/tutorials.php\">here<\/a>. <a href=\"https:\/\/www.dropbox.com\/s\/mfps08muedkpyp9\/uai2017_tutorial_saria_soleimani.pdf?dl=0\">Slides<\/a>. <a href=\"https:\/\/drive.google.com\/file\/d\/0BySbB7fujjskSlR4aXFDWk91cG8\/view?usp=sharing\">Video<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2017<\/div>\n<div class=\"honor_txt\">Excited to speak on \u201cMachines that Learn to Spot Diseases\u201d at the <span>National Academy of Engineering<\/span> Frontier\u2019s of Engineering Meeting. More <a href=\"https:\/\/www.naefrontiers.org\/\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2017<\/div>\n<div class=\"honor_txt\">Honored to be included in MIT Technology Review\u2019s 35 Innovators Under 35 (<span>TR35<\/span>). More <a href=\"https:\/\/hub.jhu.edu\/2017\/08\/17\/suchi-saria-mit-tech-review-list\/\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2017<\/div>\n<div class=\"honor_txt\">Excited to speak on Machine Learning and its Impact at the upcoming <span>National Academy of Sciences<\/span> Annual Meeting. More <a href=\"http:\/\/www.nasonline.org\/about-nas\/events\/annual-meeting\/nas154\/symposium.html\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2016<\/div>\n<div class=\"honor_txt\">Invited Tutorial at NIPS on \u201cML Methods for Personalization with Application to Medicine.\u201d <a href=\"https:\/\/nips.cc\/Conferences\/2016\/Schedule?type=Tutorial\">More here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2016<\/div>\n<div class=\"honor_txt\"><span>DARPA Young Faculty Award<\/span>.  More <a href=\"http:\/\/www.darpa.mil\/work-with-us\/for-universities\/young-faculty-award\">here<\/a> and <a href=\"http:\/\/www.cs.jhu.edu\/2016\/09\/22\/saria-schulman-darpa-young-faculty-award\/#.WDh4u-ErIdU\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2016<\/div>\n<div class=\"honor_txt\">Excited to speak on AI and Healthcare at the <span>White House Frontiers Meeting<\/span> in the National Track.  More <a href=\"http:\/\/www.frontiersconference.org\/tracks\/national\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2016<\/div>\n<div class=\"honor_txt\">Selected to <span>Popular Science\u2019s \u201cBrilliant 10\u201d<\/span>.  More <a href=\"http:\/\/www.popsci.com\/brilliant-10-2016\">here<\/a> and <a href=\"http:\/\/hub.jhu.edu\/2016\/09\/07\/suchi-saria-popular-science-brilliant\/\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2016<\/div>\n<div class=\"honor_txt\">Excited to speak at the CCC, AAAI and White House\u2019s Office of Science and Technology Policy (OSTP) workshops on the <a href=\"https:\/\/www.whitehouse.gov\/blog\/2016\/05\/03\/preparing-future-artificial-intelligence\">Future of Artificial Intelligence<\/a>.  I gave a talk at the <span>AI for Social Good<\/span> meeting held in DC on making \u201cmeaningful use\u201d of healthcare data using machine learning.  More <a href=\"http:\/\/cra.org\/ccc\/events\/ai-social-good\/#overview\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2015<\/div>\n<div class=\"honor_txt\"><span> AI\u2019s 10 to Watch<\/span>. Selected by the IEEE Intelligent Systems once every two years to celebrate \u201cyoung stars\u201d in the field of artificial intelligence (AI).  Selected for research on \u201cReasoning Engine for Individualizing Healthcare\u201d <a href=\"https:\/\/www.dropbox.com\/s\/lyiyfce3gpk5vh6\/IEEE-AI-10-to-Watch.pdf\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2016<\/div>\n<div class=\"honor_txt\"><span>IJCAI\u2019s Early Career Spotlight<\/span>.  Invited by IJCAI to the \u201cearly career spotlight\u201d. <a href=\"http:\/\/ijcai-16.org\/index.php\/welcome\/view\/early_career_spotlight\">Here<\/a> are the other spotlight presenters.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2015<\/div>\n<div class=\"honor_txt\"><span>Science Transtional Medicine Cover article<\/span> for work on early detection of patients at high risk for septic shock using routinely collected EHR data.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2015<\/div>\n<div class=\"honor_txt\"><span>Discovery Award<\/span> Our work received two (!) of the Hopkins Discovery awards, the first on a new computational framework for large-scale discovery of autoimmune regulators in rheumatic diseases and the second for translating<br \/>\n\t\t\t\t\t\tour models for sepsis.  These are highly competitive awards and ours were 2 of the 23 that were selected from a pool of 230 submissions.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2014<\/div>\n<div class=\"honor_txt\"><span>National Science Foundation<\/span> Smart and Connected Health Research Grant award for developing computational models for prediction in complex, chronic conditions.  More <a href=\"http:\/\/hub.jhu.edu\/magazine\/2015\/spring\/individualized-health-through-big-data\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2014<\/div>\n<div class=\"honor_txt\"><span>Google Research Award<\/span> for developing machine learning tools for extracting information from electronic health records.  More <a href=\"http:\/\/www.cs.jhu.edu\/2014\/03\/07\/saria-and-van-durme-of-computer-science-honored-with-google-faculty-research-awards\/#.VDBiRvmwIvg\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2014<\/div>\n<div class=\"honor_txt\"><span>Annual Scientific Award<\/span> given to the top submission by the Society of Critical Care for our work on early detection of sepsis (selected from 1000+ submissions).<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2013<\/div>\n<div class=\"honor_txt\"><span>Betty and Gordon Moore Foundation<\/span> Research award on building safer ICUs.  More <a href=\"http:\/\/eng.jhu.edu\/wse\/magazine-winter-14\/item\/engineering-a-smarter-icu\/\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2011<\/div>\n<div class=\"honor_txt\"><span>National Science Foundation<\/span> Computing Innovation Fellowship; 17 awarded nationally.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2010<\/div>\n<div class=\"honor_txt\"><span>Science Transtional Medicine Cover article<\/span>.  More <a href=\"http:\/\/news.sciencemag.org\/health\/2010\/09\/new-model-predicts-complications-preemies\">here<\/a> and <a href=\"http:\/\/www.nsf.gov\/cise\/csbytes\/newsletter\/vol2\/vol2i2.html\">here<\/a>.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2010<\/div>\n<div class=\"honor_txt\"><span>American Medical Informatics Association<\/span> Best Paper Finalist for work on automated annotation of outcomes from electronic health record data.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2007<\/div>\n<div class=\"honor_txt\"><span>Uncertainty in Artificial Intelligence<\/span> Best Student Paper for work on inference for continuous time discrete space models.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2004<\/div>\n<div class=\"honor_txt\"><span>Rambus Fellowship<\/span> awarded for 3 years.<\/div>\n<\/div>\n<div class=\"honor_item\">\n<div class=\"honor_year\">2002<\/div>\n<div class=\"honor_txt\"><span>Microsoft Full Scholarship<\/span>. <a href=\"https:\/\/www.mtholyoke.edu\/offices\/comm\/csj\/052402\/microsoft.shtml\">here<\/a>.<\/div>\n<\/div>\n<\/div>\n<div class=\"public\">\n<div class=\"public_title\">Selected Publications (partial list prior to 2019; full list in google scholar): ML=Machine Learning, HI=Health Informatics<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] A. Subbaswamy, P. Schulam, S. Saria. <span>Learning Predictive Models that Transport<\/span>. Artificial Intelligence and Statistics (AISTATS), 2019. <a href=\"https:\/\/arxiv.org\/pdf\/1812.04597.pdf\">pdf<\/a>. <span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] P. Schulam, S. Saria. <span>Auditing Pointwise Reliability Subsequent to Training<\/span>. Artificial Intelligence and Statistics (AISTATS), 2019. <a href=\"https:\/\/arxiv.org\/abs\/1901.00403\">pdf<\/a>. <span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] A. Subbaswamy, S. Saria. <span>Counterfactual Normalization: Proactively Addressing Dataset Shift Using Causal Mechanisms<\/span>. Uncertainty in Artificial Intelligence (UAI), 2018. <a href=\"https:\/\/arxiv.org\/abs\/1808.03253\">pdf<\/a>. <span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] P. Schulam, S. Saria. <span>Discretizing Logged Interaction Data Biases Learning for Decision-Making<\/span>. arXiv preprint arXiv:1810.03025, 2018. <a href=\"https:\/\/arxiv.org\/abs\/1810.03025\">pdf<\/a>. <span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] P. Schulam, S. Saria. <span>Reliable Decision Support Using Counterfactual Models<\/span>. Neural Information Processing Systems (NIPS), 2017. <a href=\"https:\/\/arxiv.org\/abs\/1810.03025\">pdf<\/a>.<br \/>\n(<span class=\"red_txt\">Selected for an oral presentation<\/span>) <span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_intend\">\n<div>\n\t\t\t\t\t\tPrior version:<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t\t[ML] P. Schulam, S. Saria. <span>Reliable What-If Reasoning with Counterfactual Gaussian Processes<\/span>. Preprint. <a href=\"https:\/\/arxiv.org\/abs\/1703.10651v2\">pdf<\/a>. <span class=\"green_txt\">NEW<\/span><\/div>\n<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] H. Soleimani, J. Hensman, S. Saria. <span>Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction<\/span>. Transactions of Pattern Analysis and Machine Intelligence (in press), 2017. <a href=\"https:\/\/www.dropbox.com\/s\/w04on7u5uyxgikx\/Soleimani%2BSaria-UncertaintyAware-Sepsis-Alerting.pdf\">pdf<\/a><span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] H. Soleimani, A. Subbaswamy, S. Saria. <span>Treatment-Response Models for Counterfactual Reasoning with Continuous-time, Continuous-valued Interventions<\/span>. Uncertainty in Artificial Intelligence (UAI), 2017. <a href=\"https:\/\/arxiv.org\/abs\/1704.02038\">pdf<\/a><span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] Y. Xu, Y. Xu, S. Saria. <span>A Bayesian Nonparametic Approach for Estimating Individualized Treatment-Response Curves<\/span>. <a href=\"http:\/\/arxiv.org\/abs\/1608.05182\">pdf<\/a><span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_intend\">\n<div>Related work:<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t\t[ML] Y. Xu, Y. Xu, S. Saria. <span>A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves<\/span>. Conference on Machine Learning and Health Care (MLHC), Aug. 2016. <a href=\"http:\/\/arxiv.org\/abs\/1608.05182\">pdf<\/a><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t\t[ML] Q. Liu, K. Henry, Y. Xu, S. Saria. <span>Using Causal Inference to Estimate What-if Outcomes for Targeting Treatments<\/span>. NIPS workshop on \u201cWhat if\u201d Reasoning, 2016.  <a href=\"http:\/\/www.homepages.ucl.ac.uk\/~ucgtrbd\/whatif\/Paper19.pdf\">pdf<\/a>.<\/div>\n<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] P. Schulam, S. Saria. <span>Integrative Analysis Using Coupled Latent Variable Models for Individualizing Prognoses<\/span>. Journal of Machine Learning Research 17 (234):1\u221235. <a href=\"http:\/\/www.jmlr.org\/papers\/v17\/15-436.html\">pdf<\/a><span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] D. Robinson*, S. Saria*. <span>Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models<\/span>. International Joint Conference of Artificial Intelligence (IJCAI), 2016. <a href=\"https:\/\/arxiv.org\/abs\/1604.05819\">pdf<\/a><br \/>\n*equal contribution<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] P. Schulam, S. Saria. <span>A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-resolution Structure<\/span>. Neural Information Processing Systems (NIPS), 2015. <a href=\"https:\/\/papers.nips.cc\/paper\/5873-a-framework-for-individualizing-predictions-of-disease-trajectories-by-exploiting-multi-resolution-structure.pdf\">pdf<\/a><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] K. Dyagilev, S. Saria. Learning (Predictive) Risk Scores in the Presence of Censoring due to Interventions. Machine Learning, March 2016, Volume 102, Issue 3, pp 323-348. Online first: October 2015. <a href=\"http:\/\/link.springer.com\/article\/10.1007\/s10994-015-5527-7\">pdf<\/a>, <a href=\"http:\/\/arxiv.org\/abs\/1507.07295\">ArXiv<\/a><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] P. Schulam, F. Wigley, S. Saria. <span>Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery<\/span>. American Association for Artificial Intelligence, January 2015. <a href=\"http:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI15\/paper\/view\/10015\">pdf<\/a><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] S. Saria, A. Duchi, D. Koller. <span>Learning Deformable Motifs in Continuous Time Series data<\/span>. International Joint Conference on Artificial Intelligence (IJCAI), 2011. <a href=\"http:\/\/dl.dropbox.com\/u\/20167181\/Saria%2Bal-IJCAI11.pdf\">pdf<\/a><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] S. Saria, D. Koller, A. Penn. Learning individual and population level traits from clinical temporal data. NIPS Predictive Models in Personalized Medicine, 2010. <a href=\"http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.232.390&amp;rep=rep1&amp;type=pdf\">pdf<\/a>. (Other versions: short, long)<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] S. Saria, U. Nodelman, D. Koller. <span>Reasoning at the Right Time Granularity<\/span>. Uncertainty in Artificial Intelligence (UAI), July 2007. <a href=\"http:\/\/robotics.stanford.edu\/~nodelman\/papers\/dynamic-EP.pdf\">pdf<\/a> (<span class=\"red_txt\">Best student paper award<\/span>)<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[ML] V. Jojic, S. Saria, D. Koller. <span>Convex envelopes of complexity controlling penalties: the case against premature envelopment<\/span>. Artificial Intelligence and Statistics, 2011. <a href=\"http:\/\/machinelearning.wustl.edu\/mlpapers\/paper_files\/AISTATS2011_JojicSK11.pdf\">pdf<\/a><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] A. Zhan*, S. Mohan*, C. Tarolli*, R.B. Schneider, J.L. Adams, S. Sharma, M.J. Elson, K.L. Spear, A.M. Glidden, M.A. Little, A. Terzis, E.R. Dorsey, S. Saria. <span>Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: the Mobile Parkinson Disease Score<\/span>. JAMA Neurology 2018. Vol. 75, Issue 7, Pages:876-880. <a href=\"https:\/\/jamanetwork.com\/journals\/jamaneurology\/article-abstract\/2676504\">pdf<\/a><span class=\"green_txt\">NEW<\/span><br \/>\n*equal contribution<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] S. Saria. <span>Individualized sepsis treatment using reinforcement learning<\/span>. Nature Medicine 2018. Vol. 24. <a href=\"https:\/\/www.nature.com\/articles\/s41591-018-0253-x\">pdf<\/a><span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] K. Henry, D. Hager, P. Pronovost, S. Saria. <span>A Targeted Real-time Early Warning Score (TREWScore) for Septic Shock<\/span>. Science Translational Medicine 2015. Vol. 7, Issue 299. <a href=\"http:\/\/stm.sciencemag.org\/content\/7\/299\/299ra122\">pdf<\/a> (<span class=\"red_txt\">Cover article<\/span>)<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] S. Saria, A. Goldenberg. <span>Subtyping: What Is It and Its Role in Precision Medicine<\/span>. IEEE Intelligent Systems, 2015. Vol. 30, Issue 4. <a href=\"https:\/\/www.dropbox.com\/s\/krofvs7da6u3r4k\/Saria_IEEE2015_SubtypingAndPredicionMedicine.pdf\">pdf<\/a><span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] S. Saria, A. Rajani, J. Gould, D. Koller, A. Penn. Integration of Early Physiological Responses Predicts Later Illness Severity in Preterm Infants. Science Translational Medicine September 2010. Vol. 2, Issue 48. <a href=\"http:\/\/stm.sciencemag.org\/content\/2\/48.cover-expansion\">Link<\/a>  (<span class=\"red_txt\">Cover article<\/span>)<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] C. Paxton, A. Niculescu-Mizil, S. Saria. Developing Predictive Algorithms Using Electronic Medical Records: Challenges and Pitfalls. American Medical Informatics Association, 2013. <a href=\"https:\/\/www.dropbox.com\/s\/sabvd1ramnd0bvo\/developing-predictive-models-amia-final.pdf\">pdf<\/a><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] S Saria, G McElvain, AK Rajani, AA Penn, DL Koller. Combining Structured and Free-text Data for Automatic Coding of Patient Outcomes. American Medical Informatics Association, 2010. (<span class=\"red_txt\">Best student paper finalist <\/span> )<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[HI] A. J Ma, N. Rawat, A. Reiter, C. Shrock, A. Zhan, A. Stone, A. Rabiee, S. Griffin, D. M. Needham, S. Saria. Measuring Patient Mobility in the ICU Using a Novel Noninvasive Sensor. Critical Care Medicine. Vol. 45, Issue 4. Pp. 630-636. <a href=\"http:\/\/www.cs.jhu.edu\/~areiter\/JHU\/Publications_files\/ccm-nims.pdf\">Link<\/a><span class=\"green_txt\">NEW<\/span><\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[Perspective] S. Saria. A $3 Trillion Challenge to Computational Scientists: Transforming Healthcare Delivery, August 2014. IEEE Intelligent Systems. Vol. 29, Issue 4. <a href=\"https:\/\/www.dropbox.com\/s\/55zvpshi2ud5d8a\/SariaIEEEIS2014_TransformingHealthcareDelivery.pdf\">Link<\/a> (<span>Invited article<\/span>)<\/div>\n<div class=\"public_item\">\n\t\t\t\t\t[Perspective] D.W. Bates, S. Saria, L. Ohno-Machado, A. Shah, G. Escobar. Big data in health care: using analytics to identify and manage high-risk and high-cost patients, July 2014. Health Affairs. Vol. 33, Issue 7. <a href=\"http:\/\/content.healthaffairs.org\/content\/33\/7\/1123.abstract\">Link<\/a> ( <span class=\"red_txt\">Short presentation made to an audience of policy makers at the National Press Club, Washington D.C. <a href=\"http:\/\/www.healthaffairs.org\/events\/2014_07_09_big_data\/\">here<\/a> .<\/span>)<\/div>\n<\/div>\n<div class=\"national\">\n\t\t\t\t<span>National Science Foundation on our work in modeling complex, chronic diseases such as scleroderma<\/span>.  More <a href=\"http:\/\/www.nsf.gov\/news\/special_reports\/science_nation\/predictivemedicine.jsp\">here<\/a>.<\/div>\n<div class=\"youtube\">\n\t\t\t\t<iframe src=\"https:\/\/www.youtube.com\/embed\/EdUdYEejOBE\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\" name=\"fitvid0\"><\/iframe><\/div>\n<div class=\"national\">\n\t\t\t\t<span>TEDxBoston talk on Better Medicine Through Machine Learning<\/span>. <a href=\"https:\/\/tedxboston.org\/speaker\/saria\">More<\/a> .<\/div>\n<div class=\"youtube\">\n\t\t\t\t<iframe src=\"https:\/\/youtube.com\/embed\/Nj2YSLPn6OY\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\" name=\"fitvid0\"><\/iframe><\/div>\n<div class=\"national\">\n\t\t\t\t<span>NIPS 2016 Tutorial on ML Methods for Personalization with Application to Medicine<\/span>.  <a href=\"https:\/\/nips.cc\/Conferences\/2016\/Schedule?type=Tutorial\">More here<\/a>.<\/div>\n<div class=\"national\">\n\t\t\t\t<span>UAI 2017 Tutorial on Machine Learning and Counterfactual Reasoning for \u201cPersonalized\u201d Decision-Making in Healthcare<\/span>. More <a href=\"http:\/\/www.auai.org\/uai2017\/tutorials.php\">here<\/a>. <a href=\"https:\/\/www.dropbox.com\/s\/mfps08muedkpyp9\/uai2017_tutorial_saria_soleimani.pdf?dl=0\">Slides<\/a>. <a href=\"https:\/\/drive.google.com\/file\/d\/0BySbB7fujjskSlR4aXFDWk91cG8\/view?usp=sharing\">Video<\/a>.<\/div>\n<div class=\"machine\">\n<div class=\"machine_title\">\n\t\t\t\t\tMachine Learning and Healthcare Lab:<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"http:\/\/pschulam.com\/\">Peter Schulam<\/a> (PhD student; Computer Science) NSF and Centennial Fellow<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"http:\/\/kathen.github.io\/\">Katie Henry<\/a> (PhD student; Computer Science) NSF Fellow<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Yanbo Xu<\/a> (PhD student; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Noam Finkelstein<\/a> (PhD student; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Adarsh Subbaswamy<\/a> (PhD student; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"http:\/\/www.cs.jhu.edu\/~andong\/\">Andong Zhan<\/a> (PhD student; Computer Science; Primary advisor: Andreas Terzis)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Hossein Soleimani<\/a> (Postdoctoral fellow; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Wenpin Hou<\/a> (Postdoctoral fellow; Computer Science and Genetics)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Anton Alyakin<\/a> (ugrad; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Tony Wang<\/a> (ugrad; Biomedical Engineering)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Srihari Mohan<\/a> (ugrad; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Ryan Newell<\/a> (ugrad\/masters; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Adhiraj Yadav<\/a> (masters; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">San-He Wu<\/a> (Data Science Staff)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Dhanunjay Singh<\/a> (masters; Computer Science)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Ethan Groverman<\/a> (Project Manager)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Yanif Ahmad<\/a> (Streaming DB Researcher Extraordinaire)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Nestoras Mathioudakis<\/a> (NIH K-awardee; Assistant Professor in Endocrinology)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Faisal Rahman<\/a> (Clinical Fellow in Cardiology)<\/div>\n<div class=\"machine_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Nishi Rawat<\/a> (NIH K-awardee; Assistant Professor in Critical Care Medicine)<\/div>\n<\/div>\n<div class=\"alumni\">\n<div class=\"alumni_title\">\n\t\t\t\t\tAlumni:<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tAndy Ma (postdoctoral fellow 2014-2015; Assistant Professor at Sun Yat-sen University)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tMu-Hsin Wei (postdoctoral fellow 2013-2014; Data Science @ Bloomberg)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\t<a href=\"\">Kirill Dyagilev<\/a> (Postdoctoral Fellow 2014-2016; startup in NY)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\t<a href=\"https:\/\/github.com\/junr03\">Jose Nino<\/a> (Ugrad 2015-2016; Engineering Infrastructure @ Lyft)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tZhou Ye (2013-2014; Data Science @ Alibaba)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tChris Paxton (2012-2013; PhD student @ Johns Hopkins)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\t<a href=\"https:\/\/suchisaria.jhu.edu\/www.suchisaria.com\">Wenbo Pan<\/a> (masters student; Computer Science)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tAntonia Oprescu (Summer 2014; Undergraduate @ Harvard)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tPhillip Oh (Summer 2014; Undergraduate @ Johns Hopkins)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tRiashat Islam (Summer 2014; Undergraduate @ UCL)<\/div>\n<div class=\"alumni_item\">\n\t\t\t\t\tEthan Pronovost (St. Paul\u2019s High School; Undergrad @ Caltech)<\/div>\n<\/div>\n<div class=\"news\">\n<div class=\"news_title\">\n\t\t\t\t\tOther News:<\/div>\n<div>\n\t\t\t\t\t\u2013 Student news:<br \/>\nPeter Schulam wins the Centennial Fellowship (August 2013).  Miruna Oprescu wins second prize at the JHU Summer Research Expeditions program for her work with my lab on modeling health data (Aug. 2014).  Ethan Pronovost selected as one of the finalists at the Americal Medical Informatics Association HSSP for his work with my lab on measuring harms due to false alarms in the ICU (Oct. 2014).  Zach Barnes won second prize at the JHU Summer Research Expeditions for his work on deploying a tool for prognosticating lung fibrosis in scleroderma (Aug 2015).<\/div>\n<div>\n\t\t\t\t\t\u2013 I\u2019m the workshop co-chair for NIPS 2017 with Ralf Herbrich and NeurIPS (formerly NIPS) with Joaquin Quinonero Candela.<\/div>\n<div>\n\t\t\t\t\t\u2013 Old talks (I no longer keep my webpage up to date with talks):<\/div>\n<div>\n\t\t\t\t\t\u2013 Invited talks at the <a href=\"http:\/\/bigdata.stanford.edu\/\">Big Data in Biomedicine<\/a>, Advanced Pharma Analytics conference, Gordon Conference in Health Informatics, and the <a href=\"http:\/\/www.cell-symposia-systems-biology.com\/\">Technology<\/a>, <a href=\"http:\/\/www.cell-symposia-systems-biology.com\/\"> Biology and Data Science symposium by Cell Press<\/a>.<\/div>\n<div>\n\t\t\t\t\t\u2013 Interview with Katherine Gorman of  <a href=\"http:\/\/www.thetalkingmachines.com\/blog\/2016\/3\/10\/ivpi7nd68oln8kk9lz2o4nyibvfyqd\">Talking Machines<\/a><\/div>\n<div>\n\t\t\t\t\t\u2013 Invited talks at the <a href=\"http:\/\/www.mdanderson.org\/education-and-research\/departments-programs-and-labs\/departments-and-divisions\/division-of-quantitative-sciences\/educational-programs\/ibright-2015-program.html\">iBRIGHT Symposium<\/a>, University of Oxford, Princeton, Wireless Health, Informatics Meeting at Penn, Emory University, University of Washington<\/div>\n<div>\n\t\t\t\t\t\u2013 Area chair for ICML 2016, SPC for KDD 2016<\/div>\n<div>\n\t\t\t\t\t\u2013 Check out our workshop on <a href=\"https:\/\/sites.google.com\/site\/nipsmlhc15\/\">Machine Learning in Healthcare @ NIPS<\/a><\/div>\n<div>\n\t\t\t\t\t\u2013 Spring-Summer\u201915 Invited talks at Duke, ENAR, University of Wiscosin, Google DeepMind, University of Pennsylvania, Fred Hutchinson (Data Science to Data Sense Symposium), University of Washington, the VA.<\/div>\n<div>\n\t\t\t\t\t\u2013 Daniel Robinson and I won an IDIES seed grant for cost-sensitive predictive tools for preventing in-hospital adverse events (Summer 2015).<\/div>\n<div>\n\t\t\t\t\t\u2013 Co-editing a special topics issue for the Journal of Machine Learning Research on \u201cLearning from Electronic Health Data\u201d.<\/div>\n<div>\n\t\t\t\t\t\u2013 Senior Program Committee for KDD 2015, IJCAI 2015.<\/div>\n<div>\n\t\t\t\t\t\u2013 I lead an invited panel on Predictive Analytics @ <a href=\"http:\/\/www.amia.org\/amia2014\">American Medical Informatics Association<\/a> annual symposium (Nov. 2014)<\/div>\n<div>\n\t\t\t\t\t\u2013 I was a Keynote speaker on Big data approaches in Health @ the <a href=\"http:\/\/www.bigdatahitforum.com\/\">Big Data + Healthcare Analytics Forum<\/a> by HIMSS (Nov. 2014)<\/div>\n<div>\n\t\t\t\t\t\u2013 I presented work on opportunities for big data approaches to improve healthcare at D.C. National Press club (July 2014) at the inaugural event on Big Data by Health Affairs.<\/div>\n<div>\n\t\t\t\t\t\u2013 I was invited to the expert\u2019s panel at the Moore Predictive Analytics Symposium (Sept. 2013) to discuss predictive models from EMR and sensing data<\/div>\n<div>\n\t\t\t\t\t\u2013 I recently gave an invited talk at the Data Science for Social Good program in Chicago (August 2013)<\/div>\n<div>\n\t\t\t\t\t\u2013 I gave an invited panel talk the National Science Foundation and National Institutes of Health joint meeting on Computing and Health; I spoke with three other invited panelists on the \u2018Exploiting<br \/>\nData in Abundance\u2019 panel. (Oct. 2012)<\/div>\n<div>\n\t\t\t\t\t\u2013 I gave an invited presentation at the DARPA Defense Science Office workshop on opportunities in healthcare computing (Nov. 2012)<\/div>\n<div>\n\t\t\t\t\t\u2013 I gave an invited talk at INFORMS Healthcare on the big data in healthcare session (July 2013). INFORMS is the largest meeting in Operations Research. Informs Healthcare is a new meeting focused entirely on healthcare applications. There were ~600 attendees to the meeting in its 2nd year.<\/div>\n<div>\n\t\t\t\t\t\u2013 I co-chaired ICML workshop on <a href=\"https:\/\/sites.google.com\/site\/icmlwhealth\/\">Role of Machine Learning in Transforming Healthcare<\/a>  (July 2013)<\/div>\n<div>\n\t\t\t\t\t\u2013 I co-chaired <a href=\"http:\/\/mucmd.org\/program-information-2012.php\"> Meaningful Use of Complex Medical Data<\/a> (MUCMD) Symposium at the Children\u2019s Hospital LA (August 2012)<\/div>\n<div>\n\t\t\t\t\t\u2013 Other selected invited talks: Google (Oct. 2013), Carnegie Mellon University (Oct. 2013), Institute for Computational and Experimental Research in Mathematics at Brown University (Nov. 2012), University of Vanderbilt Grand Rounds in Informatics (2012), University of Maryland Machine Learning Seminar (2012), International<br \/>\nSociety for Bayesian Analysis (ISBA) (July 2012).<\/div>\n<\/div>\n<div class=\"teach\">\n<div class=\"teach_title\">\n\t\t\t\t\tTeaching:<\/div>\n<div class=\"teach_item\">\n\t\t\t\t\tCurrent (Spring 15): 600.476\/676 <a href=\"https:\/\/piazza.com\/jhu\/spring2015\/cs476676\/home\"> Machine Learning: Data to Models<\/a><\/div>\n<div class=\"teach_item\">\n\t\t\t\t\tPrevious (Fall 13): 600.476\/676 <a href=\"https:\/\/piazza.com\/configure-classes\/fall2013\/cs476676\"> Machine Learning in Complex Domains<\/a><\/div>\n<div class=\"teach_item\">\n\t\t\t\t\tPrevious: 600.476\/676 Machine Learning in Complex Domains, 600.775 Seminar in Machine Learning and Data-Intensive Computing<\/div>\n<\/div>\n<div class=\"faq\">\n<div class=\"faq_title\">\n\t\t\t\t\tFAQ:<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ00.  I am an international student and I want to apply to your PhD program.  Are you taking students?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tWe get 5+ emails of this type per week through the fall.  As a once international student, I understand the anxiety of being on the other side.  First, these emails are not effective unless you\u2019ve read the faculty\u2019s papers and have something intelligent to say.  So, don\u2019t bother wasting your time.  Second, let me explain a common issue with PhD admissions for international students. Typically, CS programs tend to fund their PhD students through the length of their program (5 years).  This means faculty tend to be risk averse.  Having sat on PhD admissions committees, most faculty find it challenging to assess the background of an international student because they don\u2019t often know your school or your advisor.  It\u2019s also difficult to gauge whether your grades are highly competitive or not.  As a result, most committees pass on international students unless they have an *obviously* strong application.  If you\u2019re serious about research and getting a PhD, and don\u2019t have a strong research background (i.e. published papers in top conferences and strong recommendation letters), apply to the masters program.  Very often, we take our strong masters students as research assistants after a semester or two.  This gives you a chance to build credibility.  And, very often, you can recover the cost of your masters through industry internships which pay quite a bit.  Also, at a place like Hopkins, there are many faculty outside of computer science that are looking for strong programmers for a research project.  That funding can tide you over until you find a lab.  But, in the long run, it\u2019s more fruitful to apply to a strong masters program with the goal of switching to a good PhD program rather than going to a PhD program with a poor fit.<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ0. I\u2019m primarily interested in machine learning.  But, I\u2019m unsure of the application area.  Do I need to have determined this ahead of time?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tNo. There are a number of faculty including myself that work on machine learning problems applicable to multiple domains.  Look through <a href=\"http:\/\/ml.jhu.edu\/\"> ML@JHU<\/a>.  Also, look through application areas at <a href=\"http:\/\/hltcoe.jhu.edu\/research\/about\/\">Human Language Center of Excellence<\/a> , and <a href=\"http:\/\/idies.jhu.edu\/research.aspx\">IDIES<\/a> .<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ1. I\u2019m a student at Hopkins and I\u2019m interested in working with you.  How can I get involved?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tPlease take a look at my papers.  If you still remain interested, please send me an email.  It\u2019s often also helpful to speak with the students in the research group to get a flavor of the problems you could get involved in.<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ2. I\u2019m not at Hopkins currently.  Can I apply to your lab for a PhD?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tYes, we are looking for creative and brilliant students to join us. However, you must formally apply to the PhD program for me to be able to consider you.  It might be helpful to read through this <a href=\"http:\/\/graddecision.org\/\">site<\/a>  on how to put together a strong graduate school application.  To gain a better understanding of the types of problems I work on, please read my papers.  I soon plan to put up an active projects page but if you\u2019re interested, feel free to send my students or I a note.<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ3. I\u2019m an undergraduate and I am looking for internship opportunities.  Can I visit your lab?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tYes, we started a new internship program called the <a href=\"http:\/\/www.cs.jhu.edu\/sre\/\">Summer Research Expeditions<\/a>  (SRE) in 2013.  The program brings together faculty from multiple departments in engineering and is a great opportunity to gain exposure to multidisciplinary applications of computing.<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ4. I\u2019m looking for postdoctoral or research scientist positions.  Are there positions in your lab?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tWe are always looking for great people to join our group.  There is flexibility in terms of the projects you can get involved with.  Please send me a copy of your CV if you\u2019d like to learn more.<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ5. I\u2019m interested in machine learning and your work but I have never worked in medicine\/biology\/healthcare.  Do I need a medical background to work on healthcare projects?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tNo.  In my own work, we\u2019ve made significant progress from bringing in a fresh machine learning perspective to existing problems in healthcare.  See my recent <a href=\"https:\/\/dl.dropboxusercontent.com\/u\/20167181\/SariaIEEEIS2014_TransformingHealthcareDelivery.pdf\">article<\/a>  to get a flavor of the kinds of interesting computational problems that machine learning researchers can help solve in healthcare.  You can learn most of what you need to know about the domain through your readings and interactions with your collaborators.  Our healthcare expenses are upwards of 2.5 trillion dollars and we\u2019re in desperate need of better approaches for improving outcomes and lowering cost.  Our health system produces vasts amount of messy and heterogeneous data that we need smarter modelers to be looking at and gleaning insights from.<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tQ6. Why Hopkins?<\/div>\n<div class=\"faq_item\">\n\t\t\t\t\tIf you\u2019re interested in solving difficult computational problems in healthcare, Hopkins is one of the best places to join. We have more than two dozen faculty across Computer Science, Statistics, and Biomedical Engineering who are studying novel ways to improve medicine and healthcare using computational techniques.  See <a href=\"http:\/\/www.icm.jhu.edu\/people\/index.php?role=01\">Institute for Computational Medicine<\/a> , <a href=\"https:\/\/www.lcsr.jhu.edu\/Main_Page\">Lab for Computational Sensing and Robotics<\/a> , inHealth, <a href=\"http:\/\/ml.jhu.edu\/\">ML@JHU<\/a>  and <a href=\"http:\/\/idies.jhu.edu\/\">Institute for Data Intensive Science and Engineering <\/a> for related work by faculty.<\/div>\n<\/div>\n<\/div>\n<\/div>\n<footer>\n\t\tPOWERED BY <a target=\"_blank\" href=\"http:\/\/www.cryoutcreations.eu\" title=\"Parabola Theme by Cryout Creations\" rel=\"noopener\">PARABOLA<\/a> &amp; <a target=\"_blank\" href=\"http:\/\/wordpress.org\/\" title=\"Semantic Personal Publishing Platform\" rel=\"noopener\">  WORDPRESS<\/a>.<br \/>\n\t<\/footer>\n","protected":false},"excerpt":{"rendered":"<p>Suchi Saria \u2013 Machine Learning, Computational Health Informatics Suchi Saria John C. Malone Associate Professor Johns Hopkins University Department of Computer Science Department of Applied Math &amp; Statistics Department of Health Policy &amp; Management Research Director, Malone Center for Engineering and Healthcare Contact: prefix@suffix where prefix=ssaria and suffix=cs.jhu.edu Twitter: Follow\u2026 <a class=\"continue-reading-link\" href=\"https:\/\/suchisaria.jhu.edu\/\">Continue reading<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-8","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=\/wp\/v2\/pages\/8","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8"}],"version-history":[{"count":104,"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=\/wp\/v2\/pages\/8\/revisions"}],"predecessor-version":[{"id":302,"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=\/wp\/v2\/pages\/8\/revisions\/302"}],"wp:attachment":[{"href":"https:\/\/suchisaria.jhu.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}