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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
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A

Registered Workshop Participants

Abid, Rizwan – Abbas Institute of Medical Sciences, Muzaffarabad

Adams, Christopher – Federal Trade Commission

Agara Mallesh, Dhanush – University of Tennessee

Agudelo, Carlos – Ecopetrol ICP

Ahearn, Clare – Economic Consultant

Ahearn, Mary – Agricultural and Applied Economics Association

Alekseyenko, Alexander – Medical University of South Carolina

Alexiades, V. – University of Tennessee

Alharbi, Rawan – Northwestern University

Ali-Rahmani, Fatima – National Cancer Institute, National Institutes of Health (NIH)

Allen, Genevera – Rice University; Baylor College of Medicine

Allen, Melissa – Oak Ridge National Laboratory

Allen, Tim – Cigna

Alshurafa, Nabil – Northwestern University

Alves, Vinicius – University of North Carolina, Chapel Hill

Amaral, Henrique – Universidade Estadual do Maranhão

Ambani, Zainab – University of Pennsylvania

Amorim, Leila – Universidade Federal da Bahia, Brazil

Anderson, Erik – Humana

Anderson, Patrick – California Department of Public Health

Andreev, Victor – Arbor Research Collaborative for Health

Aoki, Yutaka – National Center for Health Statistics, Centers for Disease Control and Prevention (CDC)

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Arterburn, David – Group Health Research Institute

Arya, Suresh – NIH

Avram, Alexandru – National Institute of Child Health and Human Development, NIH

Bagrow, James – University of Vermont

Ball, Robyn – Stanford University

Barbaresco, Frederic – Thales

Barber, Jarrett – Northern Arizona University

Barnard, Ben – Baylor University

Baro, Elande – U.S. Food and Drug Administration (FDA)

Barreto, Mauricio – Fiocruz

Baru, Chaitan – National Science Foundation

Bass, Emily – Avac

Basseville, Agnes – NIH

Basu, Saonli – University of Minnesota

Bawawana, Bavwidinsi – U.S. Census Bureau

Baydil, Banu – Columbia University

Beaudoin, Nicholas – Anser

Behan, Brendan – Ontario Brain Institute

Behera, Priyaranjan – North Carolina State University

Beresovsky, Vladislav – National Center for Health Statistics

Berlin, Brett – George Mason University

Blanken, Tessa – Netherlands Institute for Neuroscience

Boehm, Fred – University of Wisconsin, Madison

Borum, Peggy – University of Florida

Bourne, Phil – NIH

Bowles, Kathy – University of Pennsylvania School of Nursing

Bowman, Sarah – Massachusetts Institute of Technology (MIT)

Brady, Thomas – National Intrepid Center of Excellence

Bray, Mathieu – University of Michigan

Brennan, Patricia – University of Wisconsin, Madison

Brosig, Jill – Harrison Street

Brown, Emery – MIT; Massachusetts General Hospital; Harvard Medical School

Brown, Matthew – University of North Carolina, Charlotte

Bures, Regina – National Institute of Child Health and Human Development, NIH

Bushel, Pierre – National Institute of Environmental Health Sciences, NIH

Busillo, Joseph – SEI

Butaru, Florentin – Office of the Comptroller of the Currency

Cai, Wenlong – University of North Carolina, Chapel Hill

Calimlim, Brian – ICON Plc

Campbell, Robert – Brown University

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Campos-Trujillo, Alfredo – Centro de Investigación en Materiales Avanzados

Cao, Nanwei – NIH

Cárdenas O’Farrill, Andrés – University of Bremen

Casper, Craig – Pikes Peak Metropolitan Planning Organization

Cassidy, Ruth – University of Michigan

Castro, David – Instituto Para la Evaluación de la Educación

Chakraborty, Hrishikesh – University of South Carolina

Chan, Melvin – National Institute of Education

Chandra, Kavitha – University of Massachusetts, Lowell

Chang, Fengshui – Old Dominion University

Chang, K.C. – George Mason University

Chang, Wo – National Institute of Standards and Technology

Chao, Ariana – University of Pennsylvania

Charlton, Sarah – U.S. Government

Chaubal, Rohan – Tata Memorial Center

Chaudhary, Mandar – North Carolina State University

Chehade, Abdallah – University of Wisconsin, Madison

Chen, Alex – Western Michigan University

Chen, Din – University of North Carolina, Chapel Hill

Chen, Gin – University of Southern California

Chen, Lily – University of Michigan

Chen, Weiping – National Institute of Diabetes and Digestive and Kidney Diseases, NIH

Chen, Weiwei – Florida International University

Chen, Yu-Chuan – National Center for Toxicological Research, FDA

Chen, Zhen – NIH

Chen, Zhuo – CDC

Cheng, Yu – University of Pittsburgh

Chernofsky, Ariel – Columbia University Mailman School of Public Health

Cheung, Paul – Xi’an Jiaotong-Liverpool University

Chiang, Chihyuan – U.S. Army Medical Research Institute of Infectious Diseases

Chih, Ming-Yuan – University of Kentucky

Cho, Eungchun – Kentucky State University

Chowbina, Sudhir – GenomeNext

Chu, Haitao – University of Minnesota

Chun, Asaph Young – U.S. Census Bureau

Chung, Matthias – Virginia Tech

Chung, Steve – California State University, Fresno

Cifuentes, Patricia – Ohio State University

Clark, William – Saint Louis University

Clegg, Lin – U.S. Department of Veterans Affairs

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Coa, Kisha – ICF International

Coelho, Joseph – Marquette University

Coffman, Donna – Pennsylvania State University

Coletta, Christopher – NIH

Colopy, Glen Wright – University of Oxford

Commichaux, Seth – Georgetown University

Compher, Charlene – University of Pennsylvania

Conlin, Michael – Level X Talent

Coogan, John – Raytheon

Cooper, Gregory – University of Pittsburgh

Corbin, Amie – University of Leiden

Corliss, David – Ford Motor Company

Costa, Paulo – Instituto de Ciências Biomédicas Abel Salazar–U. Porto

Costilla, Antonio – Centro de Investigación en Matemáticas A.C.

Courtney, Paul – Dana-Farber Cancer Institute

Coyle, Patrick – NORC at the University of Chicago

Crank, Keith – National Science Foundation

Cross, Chad – Nevada State College

Cui, Naixue – University of Pennsylvania

Cui, Xinping – University of California, Riverside

Currey, Kareen – NIH

Daluwatte, Chathuri – FDA

Dani, Gabriele – Georgetown University

Daniels, Michael – University of Texas, Austin

Daramola, Olumuyiwa – Georgetown University

Dasgupta, Abhijit – National Institute of Arthritis and Musculoskeletal and Skin Diseases, NIH

Davey, Adam – University of Delaware

Davis, Sean – National Cancer Institute, NIH

Day, Kevin – Waggoner Engineering

De Sturler, Eric – Virginia Tech

Debakey, Samar – Health Research and Analysis

Decorte, Lauren – Accenture

Dempster, Arthur – Harvard University

Derkach, Andriy – National Cancer Institute, NIH

Deshmukh, Shraddha – University of Southern California School of Social Work

Dewey, Colin – University of Wisconsin, Madison

Deyonke, Jay – Raytheon

Dhingra, Radhika – U.S. Environmental Protection Agency (EPA)

Dibello, Anthony – National Institute of Diabetes and Digestive and Kidney Diseases, NIH

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Dilthey, Alexander – National Human Genome Research Institute, NIH

Dixon, John – Amazon Web Services

Dolgikh, Svetlana – Kazhydromet

Dombrowski, Lad – University of Michigan

Dorfman, Alan – National Center for Health Statistics, CDC

Duncan, Dean – University of North Carolina, Chapel Hill

Dunn, Jessilyn – Stanford University

Dunn, Michelle – NIH

Dye, Laurel – National Aeronautics and Space Administration Safety Center

Eaton, Anne – Memorial Sloan Kettering Cancer Center

Eck, Michael – Army Public Health Center

Ejim, Jennifer – ITWatchIT

Ekram, Matt

Eltinge, John – U.S. Bureau of Labor Statistics

Erdley, W. Scott – Behling Simulation Center, University of Buffalo

Evain, Trevor – Lawrence Berkeley National Laboratory

Fahroo, Fariba – Defense Advanced Research Projects Agency

Fang, Jianwen – National Cancer Institute, NIH

Fann, Yang – National Institute of Neurological Disorders and Stroke, NIH

Faries, Douglas – Eli Lilly

Federer, Lisa – National Institutes of Health Library

Feng, Hao – Emory University

Fenimore, Paul – Independent Analyst

Fiaccone, Rosemeire – Federal University of Bahia

Figueroa, Patricio – World Dermatology Institute

Finneran, Kevin – National Academies of Sciences, Engineering, and Medicine

Flagan, Richard – Caltech

Flanagan, Patrick – National Resources Conservation Center, U.S. Department of Agriculture

Flores, Fernando – Tucma Software

Follmann, Dean – NIH

Forsythe, Alan

Fosse, Nathan – Harvard Business School

Frau, Lourdes – LMF Pharmacoepidemiology

Frey, Jeremy – University of Southampton

Fu, Yi-Ping – NIH

Gabriel-Whyte, Piriye – Canadian Executive Service Organization

Gagnon, Stuart – Federal Highway Administration

Gail, Mitchell – National Cancer Institute, NIH

Gan, Weiniu – National Heart, Lung, and Blood Institute; NIH

Gandikota, Madhuri – Tapasvi Clin-Molbio Solutions, Inc.

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Gandour, Fabio – IBM Research

Garcia Islas, Luis Heriberto – Universidad Autonoma del Estado de Hidalgo

Gatsonis, Constantine – Brown University

Ge, Ping – U.S. Department of Energy

Geissert, Peter – Portland State University

George, Nysia – National Center for Toxicological Research, FDA

Gezmu, Misrak – NIH

Ghadermarzi, Shadi – Johns Hopkins University (JHU)

Ghahari, Alireza – Nuclear Energy Institute

Ghitza, Udi – National Institute on Drug Abuse, NIH

Ghosh, Basanti – Health Canada

Ghoshal, Devarshi – Lawrence Berkeley National Laboratory

Gibson, Jen – Fors Marsh Group, LLC

Gillette, Shana – U.S. Agency for International Development

Gindi, Renee – CDC

Giordano, Nicholas – University of Pennsylvania Nursing

Glaser, Elizabeth – Brandeis University

Gleicher, David – NORC at the University of Chicago

Glick, Joseph – Expertool Software, LLC

Godoy, Juan – Universidad Nacional de Córdoba

Golla, Srujana – NIH

Golozar, Asieh – Johns Hopkins Bloomberg School of Public Health

Gomes, Fabio – National Institute of Allergy and Infectious Diseases, NIH

Gordon, Chloe

Gorman, Bryan – JHU Applied Physics Laboratory

Goroff, Daniel – Alfred P. Sloan Foundation

Gouripeddi, Ram – University of Utah

Govindaiah, Swetha – University of Alabama, Huntsville

Govindarajan, Ramya – Emory University

Govindarajan, Thirupugal – NIH

Govindu, Ramakrishna – University of South Florida

Grandieri, Chris – Anne Arundel County Public Schools

Graven, Christian – North Carolina State University

Grayi, Gray

Greathouse, Leigh – Baylor University

Griffith, William – University of Washington

Groseclose, Sam – Office of Public Health Preparedness and Response, CDC

Gue, F. – Uni Konstanz

Guerra, Martin – Guerra Music Studio

Hakkinen, Pertti – National Library of Medicine, NIH

Hall, Benjamin – Humana

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Hall, Henry – Consultant

Haneuse, Sebastien – Harvard University

Hanlon, Alexandra – University of Pennsylvania

Harden-Barrios, Jewel – Ochsner Health System

Harlow, Lisa – University of Rhode Island

Harris, Ann – Seton Hall University

Harris, Anna – University of Arkansas, Pine Bluff

Harris, Jason – Oak Ridge Institute for Science and Education at EPA; University of North Carolina

Harris, Marcus – Portland State University

Hart, B.

Hartman, Anne – Tobacco Control Research Branch, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH

Hayes, Valerie – Hayes & Associates

He, Shisi – Georgetown University

Hector, Emily – University of Michigan

Heller, Ruth – NIH

Heller, Yair

Hero, Alfred – University of Michigan

Hewamanage, Samantha – Northwestern University

Hicks, Daniel – Science and Technology Policy Fellowships, American Association for the Advancement of Science

Higdon, Dave – Social and Decision Analytics Laboratory, Biocomplexity Institute of Virginia Tech

Higgins, Ixavier – Emory University

Hilal, Sheha – American Computer Resources

Hirschman, Karen – University of Pennsylvania School of Nursing

Hodzic, Migdat – International University of Sarajevo

Hoffeld, J. Terrell – U.S. Public Health Service

Hogan, Joseph – Brown University

Holko, Michelle – Booz Allen Hamilton

Hollm-Delgado, Maria-Graciela – JHU

Horton, Nicholas – Amherst College

Hoshizaki, Deborah – National Institute of Diabetes and Digestive and Kidney Diseases, NIH

Hou, Ping – University of Michigan

Howard, Rodney – National Academies of Sciences, Engineering, and Medicine

Hsu, J. – Harvard Medical School

Hsu, W. – University of California, San Diego

Hu, Ping – National Cancer Institute, NIH

Hu, Xiaowei – Oklahoma State University

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Huang, Howie – George Washington University

Huang, Jie – Kaiser Permanente

Huang, Wei – Northwestern University

Huang, Weichun – National Institute of Environmental Health Sciences, NIH

Huang, Yishi – George Washington University

Hughes, Nicole – U.S. Department of Defense (DOD)

Hutfless, Susan – JHU

Huynh, Viet – Deakin University

Hyacinth, Albert – CDC

Hyun, Noorie – National Cancer Institute, NIH

Irani, Elliane – University of Pennsylvania School of Nursing

Irions, Amanda – Aim Data Science

Isayev, Olexandr – University of North Carolina, Chapel Hill

Iyer, Ganesh – Emory University

Iyer, Lax – Labcorp Inc.

Jabbar, Shirin – Emory University

Jackson, Eugenie – University of Wyoming

Jackson, Thomas – Econometrica

Jang, Don – Mathematica Policy Research

Jeng, Jessie – North Carolina State University

Ji, Chuanyi – Georgia Tech

Ji, Xiaopeng – University of Pennsylvania

Jiang, Hongmei – Northwestern University

Jiang, Miao – Harvey L. Neiman Health Policy Institute

Jiang, Zhuoxin – Medimmune

Jovanovic, Borko – Northwestern University

Juarez, Octavio – National Institute of Allergy and Infectious Diseases, NIH

Kafadar, Karen – University of Virginia

Kalmankar, Sundeep – Cisco Systems

Kang, David – Microbiotest Division of Microbac Laboratories, Inc.

Kankam, Joaquina – Prairie View A & M University Cooperative Extension Program

Kannan, Nandini – National Science Foundation

Kapphahn, Kristopher – Stanford University

Karpen, Joshua – University of California, San Diego

Kass, Robert – Carnegie Mellon University

Kaul, Abhishek – National Institute of Environmental Health Sciences, NIH

Kayaalp, Mehmet – NIH

Kelley, Douglas – GE Healthcare

Kennedy, Amy – National Cancer Institute, NIH

Khare, Meena – National Center for Health Statistics, CDC

Khatry, Deepak – Medimmune

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Khattree, Ravindra – Oakland University

Khuder, Sadik – University of Toledo

Khuong, Hoa – Northeastern Illinois University

Kim, Dong-Yun – National Heart, Lung, and Blood Institute; NIH

Kim, Hyeonju – University of Arizona

Kim, Kwang-Youn – Northwestern University

Kim, Sinae – Rutgers University

Kim, Sohyoung – National Cancer Institute, NIH

Kim, Yoonsang – University of Illinois, Chicago

King, Karen – National Science Foundation

Knapp, Adam – U.S. Naval Research Laboratory

Knepper, Mark – National Heart, Lung, and Blood Institute; NIH

Knudson, Keith – Alphaport, Inc.

Ko, Yi-An – Emory University

Koch, Tara – Occupational Safety and Health Administration, U.S. Department of Labor

Konduri, Karthik – University of Connecticut

Kong, Lan – Pennsylvania State University, College of Medicine

Kong, Maiying – University of Louisville

Kong, Xiangrong – JHU

Kosorok, Michael – University of North Carolina, Chapel Hill

Kotsiras, Angela

Kotzinos, Dimitris – Etis Lab, University of Cergy Pontoise

Kuang, Xiaoting – Teachers College

Kuczynski, Edward – Tufts University

Kulkarni, Kshitij – University of Southern California

Kunicki, Zachary – University of Rhode Island

Kupriyanov, Roman

Kurban, Gulriz – Howard University

Kuruppumullage Don, Prabhani – Dana-Farber Cancer Institute

Labadie, Seth – U.S. Army

Laird, Douglas – U.S. Department of Transportation

Lalonde, Donna – American Statistical Association

Lancaster, Robert

Landers, Richard – Old Dominion University

Landowne, Stephen – Old Dominion University

Lanzas, Cristina – North Carolina State University

Lasater, Karen – University of Pennsylvania

Laubenbacher, Reinhard – University of Connecticut Health

Lee, George – Case Western Reserve University

Lee, Hana – Brown University

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Lee, James – University of Minnesota (retired)

Lee, Julia – Northwestern University

Lee, Steven – U.S. Department of Energy Advanced Scientific Computing Research

Lee, Un Jung – National Center for Toxicological Research, FDA

Lee, W. Robert – Duke University School of Medicine

Lei, Lei

Leicht, Benjamin – U.S. Army Medical Research Institute of Infectious Diseases

Lengerich, Ben – Carnegie Mellon University

Lesko, Catherine – Johns Hopkins Bloomberg School of Public Health

Li, Alicia – Open Health Systems Laboratory

Li, Jun – University of California, Riverside

Li, Junxin – University of Pennsylvania

Li, Leping – NIH

Li, Liang – University of Texas MD Anderson Cancer Center

Li, Meng – Duke University

Li, Ming – NIH

Li, Qing – National Human Genome Research Institute, NIH

Li, Sebastian – BMO Financial Group

Li, Shijie – North Carolina State University

Li, Xiaojuan – University of North Carolina, Chapel Hill

Li, Yuanyuan – National Institute of Environmental Health Sciences, NIH

Liang, Catherine – Partners Healthcare

Liberton, Denise – NIH

Lin, Carol – CDC

Lin, Linda – Harris Corporation

Lin, Xihong – Harvard University

Lin, Yanzhu – NIH

Lin, Yong – Rutgers University

Link, Curtis – Montana Tech

Little, Roderick – University of Michigan

Liu, Anran – CDC

Liu, Bao – Fudan University

Liu, Kaibo – University of Wisconsin, Madison

Liu, Lei – Northwestern University

Liu, Rong – University of Toledo

Liu, Yusheng – Prairie View A&M University

Livermont, Elizabeth – Stevens Institute of Technology

Lobdell, Danelle – EPA

Long, Charles – Business Intelligence Services and Predictive Analytics Services

Long, Christopher – DOD

Long, Qi – Emory University

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Lopez, Christy – County of San Diego Health and Human Services Agency

Lopresti, Charles – Pacific Northwest National Laboratory (retired)

Lu, Kun – University of Oklahoma

Lu, Shou-En – Rutgers University

Lu, Tsai-Ching – HRL Laboratories, LLC

Lu, Wenbin – North Carolina State University

Lubin, Jay – National Cancer Institute, NIH

Luo, Qingyang – Ochsner Health System

Luo, Yuqun – FDA

Lynch, Miranda – University of Connecticut Health Center for Quantitative Medicine

Ma, Sean – University of Michigan

Ma, Yanling – National Institute of Diabetes and Digestive and Kidney Diseases, NIH

Machado, Moara – National Cancer Institute, NIH

Madhavan, Guru – National Academies of Sciences, Engineering, and Medicine

Makambi, Kepher – Georgetown University

Makowsky, Robert – HTG Molecular

Malone, Susan – University of Pennsylvania

Manz, Boryana – PCCI

Marchant, Roman – University of Sydney

Marcotte, John – University of Michigan

Mariotto, Angela – National Cancer Institute, NIH

Markatou, Marianthi – University at Buffalo

Markowitz, David – Intelligence Advanced Research Projects Activity

Marrakchi Ben Jaafar, Ouwais – Lawrence Berkeley National Laboratory

Martinez Fonte, Leyden – Scotiabank

Martinez, Wendy – U.S. Bureau of Labor Statistics

Massie, Tammy – NIH

Matusko, Niki – University of Michigan Health System

Maziarz, Marlena – National Cancer Institute, NIH

McBee, David J. – University of Arizona

McCalla, Clement

McElroy, Charles – Case Western Reserve University

McGuire, Mary – University of Texas Medical School at Houston

McKaig, Rosemary – Division of AIDS, National Institute of Allergy and Infectious Diseases, NIH

McKay, Cameron – Georgetown University

McLean, Tameika – Adventist Healthcare

McManus, Doug – Freddie Mac

McNeil, Becky – U.S. Department of Veterans Affairs

Mejia, Raymond – Laboratory of Cardiac Energetics; National Heart, Lung, and Blood Institute; NIH

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Mendes, Pedro – University of Connecticut Health

Merchant, Anand – Leidos

Messner, Michael – EPA

Meyer, Denny – Swinburne University of Technology

Meyer, Eugene – Loyola University, Maryland (retired)

Mietchen, Daniel – NIH

Miller, Peter – U.S. Census Bureau

Miller, Suzanne – Cobalt Spin

Mitchell, Kimberley

Mkondiwa, Maxwell – University of Minnesota

Mondrzejewski, Dawid – Stena

Montalvo-Urquizo, Jonathan – Center for Research in Mathematics

Moore, Taplin – U.S. Army Medical Research Institute of Infectious Diseases

Morland, Andrew – University of Wisconsin, Madison

Morris, Jeff – University of Texas MD Anderson Cancer Center

Moser, Richard – National Cancer Institute, NIH

Mughal, Zaki – University of Houston

Mukherjee, Kumar – Chicago State University

Murrie, Bruce – U.S. Department of Education (retired)

Nazimuddin Fazal, Sinan – Al-Hussan International School, Khobar, Dammam Ksa

Nemeth, Margaret – Statistical Consultants Plus, LLC

Newton, Elizabeth – Fontbonne University

Ng, Nawi – Umeå University, Sweden

Nguyen, Quynh – University of Utah

Ni, Andy – Memorial Sloan Kettering Cancer Center

Nielson, Jessica – University of California, San Francisco

Nobel, Andrew – University of North Carolina, Chapel Hill

Norman, John – ExxonMobil Biomedical Sciences, Inc.

Nowell, Lucy – U.S. Department of Energy Office of Science

Nsoesie, Elaine – University of Washington

Nussbaum, Amy – American Statistical Association

Nyamekye, Kofi – Integrated Activity-Based Simulation Research, Inc.

Ocelewski, Eric – piandpower.com

Ogawa, V. Ayano – National Academies of Sciences, Engineering, and Medicine

Oliva, Nancy – University of California, San Francisco

Oliver, Karen – Veterans Health Administration

Olson, William

Ong, Mei-Sing – Boston Children’s Hospital

Oreskovich, Joanne – Montana Department of Public Health and Human Services

Ortega-Villa, Ana Maria – National Institute of Child Health and Human Development, NIH

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Ostrouchov, George – Oak Ridge National Laboratory

O’Sullivan, Brendan – DOD

Overby, Casey – JHU

Padilla, Luis – Arizona State University

Pai, Vinay – National Institute of Biomedical Imaging and Bioengineering, NIH

Pal Choudhury, Parichoy – JHU

Palencia, Francisco – Universidad Nacional de Colombia

Pan, Wei – Duke University

Panagiotou, Orestis – National Cancer Institute, NIH

Panchal, Rekha – U.S. Army Medical Research Institute of Infectious Diseases

Pandey, Abhishek – Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, FDA

Pantula, Sastry – Oregon State University

Pao, Gerald – Salk Institute for Biological Studies

Park, Soojin – Columbia University

Patel, Pragneshkumar – University of Tennessee

Patsopoulos, Nikolaos – Harvard Medical School

Pearson, John – Duke University

Peddada, Shyamal – National Institute of Environmental Health Sciences, NIH

Pescatore, John

Pfeiffer, Ruth – National Cancer Institute, NIH

Pierson, Steve – American Statistical Association

Pino, Robinson – U.S. Department of Energy

Pita, Jorge

Plata Stapper, Andres – Stanford University

Popova, Olga – Energy Information Administration, U.S. Department of Energy

Potluru, Vamsi – Comcast Research

Pratap, Abhishek – Sage Bionetworks; University of Washington

Presnell, Brett – University of Florida

Prost-Domasky, Scott – Apes, Inc.

Pugach, Oksana – University of Illinois, Chicago

Qian, Jing – University of Massachusetts, Amherst

Qin, Steve – Emory University

Quach, Kathleen – Salk Institute

Quiroz, Antonio – Universidad Autónoma del Carmen

Racuya-Robbins, Ann – World Knowledge Bank

Radmacher, Michael – Humana

Raghavan, Vasanthan – Qualcomm

Raghavan, Vijay – Harvard University

Raghuram, Viswanathan – National Heart, Lung, and Blood Institute; NIH

Ragland, John – University of Rhode Island

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Ramachandran, Mahesh – Cape Cod Commission

Rammon, Jennifer – National Center for Health Statistics, CDC

Ramsey, Gregory – TAGR2

Rappazzo, Kristen – EPA

Raval, Devesh – Federal Trade Commission

Regan, Eileen – University of Pennsylvania School of Nursing

Reyna, Cecilia – National Scientific and Technical Research Council; University of North Carolina

Reynares, Emiliano – National Scientific and Technical Research Council

Rice, Edward – National Oceanic and Atmospheric Administration

Rice, Elise – National Cancer Institute, NIH

Richardson, Lisa – CDC

Richmond, Therese – University of Pennsylvania

Rigdon, Joseph – Stanford University

Ritz, Derek – ecGroup Inc.

Riyazuddin, Firas – NIH

Rodriguez, Pedro – Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires

Rojas García, Juan – University of Granada

Rokke, Laurie – National Oceanic and Atmospheric Administration

Rolka, Deborah – Centers for Disease Control and Prevention

Rosa, Pedro – Innopolis

Rosarda, Jessica – NIH

Rose, Jhona – Health Canada

Rose, Roderick – University of North Carolina, Chapel Hill

Rose, Sophia Miryam – Stanford University; Veterans Affairs Palo Alto Health Care System

Rosemond, Erica – National Center for Advancing Translational Sciences, NIH

Roth, Holger – NIH

Roy Choudhury, Amrita – National Center for Biotechnology Information, NIH

Ruggiero, Lucia – Ghia Global Health Advisors

Ruiz-Columbie, Arquimedes – National Wind Institute, Texas Tech University

Russell, George – Fox News Channel

S., Rajani

S., Sriram – NIH

Sagan, Philip – Sagan Consulting, LLC

Salahura, Gheorghe – Office of the Comptroller of the Currency

Sales, Anne – University of Michigan

Samai, Peter – University of North Carolina Lineberger Comprehensive Cancer Center

Sampson, Joshua – National Cancer Institute, NIH

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
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Santana, Vilma – Federal University of Bahia

Santoro, Joseph – The Atlantic and Startup Grind

Santos, Carlos Antonio De Souza Teles – Fiocruz

Satagopan, Jaya – Memorial Sloan Kettering Cancer Center

Schechtman, Edna – Ben Gurion University of the Negev

Schenck, Natalya – Office of the Comptroller of the Currency

Schultz, Henning – BASF

Schwalbe, Michelle – National Academies of Sciences, Engineering, and Medicine

Scully, Christopher – FDA

Sen, Saunak – University of Tennessee Health Science Center

Shalizi, Cosma – Carnegie Mellon University

Shankar, Venkataraman – Pennsylvania State University

Shapiro, Aaron – Health Care

Shapiro, Danielle – Health Care

Shapiro, Mary – Health Care

Shapiro, Sandra – Health Care

Sharma, Surja – University of Maryland

Shi, Chengchun – North Carolina State University

Shi, Lan – Office of the Comptroller of the Currency

Shi, Min – National Institute of Environmental Health Sciences, NIH

Shih, Nw – University of Pennsylvania

Shim, Youn – Agency for Toxic Substances and Disease Registry

Shmagin, Boris – South Dakota State University

Si, Yajuan – University of Wisconsin, Madison

Siddique, Juned – Northwestern University

Sieber, Karl – National Institute for Occupational Safety and Health, CDC

Sihm, Jeong Sep – University of North Carolina, Greensboro

Sikka, Reita – Innovatrix

Sims, Kellie – Veterans Affairs Cooperative Studies Program Epidemiology Center, Durham

Sinha, Shashank – University of Michigan

Sitoula, Bibas – Oklahoma University

Slud, Eric – U.S. Census Bureau

Small, Dylan – University of Pennsylvania

Smarr, Melissa – National Institute of Child Health and Human Development, NIH

Smirnova, Ekaterina – University of Wyoming

Smith, Charles Eugene – North Carolina State University

Smith, Dan – University of Rhode Island

Smith, David – EPA

Song, Changyue – University of Wisconsin, Madison

Song, Jing – Northwestern University

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Song, Lina – Harvard University

Sonkin, Dmitriy – National Cancer Institute, NIH

Sood, Akshay – University of Wisconsin, Madison

Sop-Kamga, Gaelle – Georgetown University

Sorant, Alexa – National Human Genome Research Institute, NIH

Southern, Patrick – National Science Foundation

Spahr, Judy – Main Line Health

Spencer, Michael – National Science Foundation

Spratt, Heidi – University of Texas Medical Branch

Sreekumar, Vishnu – NIH

Stites, Edward – Washington University in St. Louis

Strachan, Rodney – University of Queensland

Strassle, Paula – University of North Carolina, Chapel Hill

Strawn, George – National Academies of Sciences, Engineering, and Medicine

Stuart, Elizabeth – Johns Hopkins Bloomberg School of Public Health

Sturrock, James – Federal Highway Administration

Summers, Ronald – NIH

Sun, Jiwu

Sun, Junfeng – NIH

Sun, Xuezheng – University of North Carolina, Chapel Hill

Suzuki, Rie – University of Michigan, Flint

Szalma, Sandor – Janssen

Szelepka, Sam – U.S. Census Bureau

Szewczyk, Bill – National Security Agency

Tabachnik, Eugene

Takeda, Takako – NIH

Tan, Kay See – Memorial Sloan Kettering Cancer Center

Tan, Xinyu – University of Michigan

Tanaka, Yoko – Eli Lilly

Tang, Lu – University of Michigan

Tang, Wei – NIH

Tapley, Byron – Center for Space Research, University of Texas, Austin

Taylor, Jonathan – Stanford University

Thakkar, Rahul – Insitu, Inc.

Thomas, Fridtjof – University of Tennessee Health Science Center

Thompson, Carla – University of West Florida

Thompson, William – Northwestern University

Tiwari Dikshit, Priyanka – North Carolina State University

Tognoli, Emmanuelle – Center for Complex Systems and Brain Sciences

Totah, Deema – University of Michigan

Travillian, Ravensara – Pacific Northwest College of Allied Health Sciences

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Trotta, Andrés – National University of Lanús

Trout, Kimberly – University of Pennsylvania

Ui Ghiollagain, Aine – Consultant

Ulanday, Kathleene – National Cancer Institute, NIH

Umbach, David – National Institute of Environmental Health Sciences, NIH

Uno, Hajime – Dana-Farber Cancer Institute

Uzoma, Ijeoma – U.S. Army Medical Research Institute of Infectious Diseases

Valentin, Naomi – Ryone Inc.

Vandi, Henry – CDC

Vanhove, Eric – Engility Corporation

Vardhanabhuti, Saran – Harvard T.H. Chan School of Public Health

Vattikuti, Shashaank – NIH

Vedula, Swaroop – JHU

Veiras, Hernan – Mad Mobile

Venkatachalapathy, Rajesh – Portland State University

Verma, Amit – Emory University

Viana, Marcele – Capturity

Villarreal, Maria – Centro de Investigación en Matemáticas A.C.

Villavicencio, Stephan – George Washington University

Voelker, Meta – JHU Applied Physics Laboratory

Waagen, Alexander – Hughes Research Laboratories

Wactlar, Howard – Carnegie Mellon University

Wang, Mel – Greenpeace

Wang, Ming – Pennsylvania State Hershey Medical Center

Wang, San – George Washington University

Wang, Wen – University of Michigan

Wang, Yaqun – Rutgers University

Wang, Yikai – Emory University

Wang, Yuan – University of Wisconsin, Madison

Wasserman, Emily – Pennsylvania State Hershey College of Medicine Department of Public Health Sciences

Wasserstein, Ronald L. – American Statistical Association

Wei, Wei – University of California, San Diego

Weidman, Scott – National Academies of Sciences, Engineering, and Medicine

Welch, Lonnie – Ohio University

Wender, Ben – National Academies of Sciences, Engineering, and Medicine

Wexler, Michael

Weylandt, Michael – Rice University

White, Don – University of Toledo

Wilkins, Ken – National Institute of Diabetes and Digestive and Kidney Diseases, NIH

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Williams, Andre – Nemours Specialty Care

Willock, Glen Roberts – Wesleyan College

Wilson, Jim – Technology Analyst

Wilson, Lauren – National Institute of Environmental Health Sciences, NIH

Witt, Michael – DNV GL

Witten, Daniela – University of Washington

Wolz, Michael – National Heart, Lung, and Blood Institute; NIH

Wong, Charlotte – Memorial Sloan Kettering Cancer Center

Wu, Jiacheng – Yale University

Wu, Jialiang Paul

Wu, Timothy – Defense Health Agency, DOD

Wu, Wenqi – Baylor University

Wu, Zhenke – Johns Hopkins Bloomberg School of Public Health

Xia, Ashley – NIH

Xian, Xiaochen – University of Wisconsin, Madison

Xu, Hong – National Institute of Environmental Health Sciences, NIH

Xu, Jianwu – NEC Laboratories America, Inc.

Xu, Yizhen – Brown University

Xue, Cao – Northwestern University

Yadegari, Ramin – University of Arizona

Yaghouby, Farid – FDA

Yang, Chengwu – Pennsylvania State College of Medicine

Yang, Jiabei – Harvard School of Public Health

Yang, Qi – Ledios Biomedical Research, Inc.

Yang, Sinji – University of Michigan

Yang, Yandan – Javelin

Ye, Wen – University of Michigan

Yeh, Chen-Min – Salk

Yoon, So Yoon – Texas A&M University

Young, Darrell – Raytheon

Yu, Bin – University of California, Berkeley

Yu, Jenny – Mycroft

Yu, Kai – National Cancer Institute, NIH

Yu, Mandi – National Cancer Institute, NIH

Yue, Mun Sang – Brown University

Yue, Yuchen – University of Maryland

Zadrozny, Sabrina – University of North Carolina, Chapel Hill

Zhai, Ruoshui – Brown University

Zhang, Henry – National Cancer Institute, NIH

Zhang, Huikun – University of Wisconsin, Madison

Zhang, Lijun – Pennsylvania State University

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×

Zhang, Qing – CDC

Zhang, Shun – NORC at the University of Chicago

Zhang, Tianchi – ICF International

Zhang, Tingting – University of Virginia

Zhang, Xilin – University of Michigan

Zhang, Xingyou – U.S. Census Bureau

Zhang, Xinli

Zhang, Yan – Office of the Comptroller of the Currency

Zhao, Dan – University of Illinois, Chicago

Zhao, Lihui – Northwestern University

Zhou, Ling – University of Michigan

Zhou, Qin – Memorial Sloan Kettering Cancer Center

Zhuy, Yeyi – National Institute of Child Health and Human Development, NIH

Ziemba, Robert – University of South Florida

Zimmerlin, Timothy – Automation Technologies

Zou, Shasha – University of Michigan

Zuo, Yanling – Minitab

Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Suggested Citation:"Appendix A: Registered Workshop Participants." National Academies of Sciences, Engineering, and Medicine. 2017. Refining the Concept of Scientific Inference When Working with Big Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24654.
×
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Next: Appendix B: Workshop Agenda »
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The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.

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