SIMBig 2021

8th International Conference on Information Management and Big Data




28 - 30 Oct

01 -03




We encourage studies as response to COVID-19: methods to leverage data and evidence in the fight against the global pandemic, with an emphasis on late-breaking topics such as vaccination, long-COVID, mental health, the global response, and preparing for the next pandemic.

SIMBig 2021 welcomes proposals to help influence policy and decision making in the public and private sector (specially in South America).


Is one of the first conferences in Latin America grouping related areas such as Artificial Intelligence, Machine Learning, Healthcare Informatics, Biomedical Data Science, Natural Language Processing, Semantic Web, etc.

About SIMBig

Keynote Speakers

Marinka Zitnik

Professor, PhD

ZITNIK, Marinka

Harvard University, USA

Professor, PhD

Dr. Marinka Zitnik is a computer scientist studying applied machine learning with a focus on challenges brought forward by data in science, medicine, and health. Dr. Zitnik joined Harvard as an Assistant Professor in December 2019. Before joining Harvard, she was a postdoctoral scholar in Computer Science at Stanford University. She was also a member of the Chan Zuckerberg Biohub at Stanford. She received her bachelor’s degree, double majoring in computer science and mathematics, and then graduated with a Ph.D. in Computer Science from University of Ljubljana just three years later while also researching at Imperial College London, University of Toronto, Baylor College of Medicine, and Stanford University. Her algorithms and methods have had a tangible impact, which has garnered interests of government, academic, and industry researchers and has put new tools in the hands of practitioners. Some of her methods are used by major biomedical institutions, including Baylor College of Medicine, Karolinska Institute, Stanford Medical School, and Massachusetts General Hospital. Her work received several best paper and research awards from the International Society for Computational Biology. Her research recently won the Bayer Early Excellence in Science Award, Amazon Faculty Research Award, a Rising Star Award in Electrical Engineering and Computer Science (EECS), and a Next Generation Recognition in Biomedicine, being the only young scientist who received such recognition in both EECS and Biomedicine. More Information here.

Andrei Broder

Scientist, PhD.

BRODER, Andrei

Google, USA

Scientist, PhD.

Dr. Andrei Broder is a Distinguished Scientist at Google where he leads a multidisciplinary research team located across three continents. From 2005 to 2012 he was a Fellow and VP for Computational Advertising at Yahoo. Previous positions include Distinguished Engineer at IBM and VP for Research and Chief Scientist at AltaVista. He was graduated Summa cum Laude from Technion and obtained his M.Sc. and Ph.D. in Computer Science at Stanford under Don Knuth. Broder has authored more than a hundred papers and was awarded fifty US patents. His current research interests are focused on user understanding, computational advertising, uses of machine learning in information systems, and randomized algorithms. He is a member of the US National Academy of Engineering and a Fellow of ACM and of IEEE. Other honors include the ACM Paris Kanellakis Theory and Practice Award and a doctorate Honoris Causa from Technion. More Information here.

Professor, PhD

 Jiawei Han

HAN, Jiawei

University of Illinois, USA

Professor, PhD

Dr. Jiawei Han is Abel Bliss Professor in the Department of Computer Science at the University of Illinois. He has been researching into data mining, information network analysis, and database systems, with over 700 publications. He served as the founding Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data (TKDD). Dr. Han has received ACM SIGKDD Innovation Award (2004), IEEE Computer Society Technical Achievement Award (2005), IEEE Computer Society W. Wallace McDowell Award (2009), and Daniel C. Drucker Eminent Faculty Award at UIUC (2011). He is a Fellow of ACM and Fellow of IEEE. His co-authored textbook "Data Mining: Concepts and Techniques" (Morgan Kaufmann) has been adopted worldwide. Dr. Han is currently the co-Director of KnowEnG, a Center of Excellence in Big Data Computing, funded by NIH Big Data to Knowledge (BD2K) Initiative. He also served in 2009-2016 as the Director of Information Network Academic Research Center (INARC) supported by the Network Science-Collaborative Technology Alliance (NS-CTA) program of U.S. Army Research Lab. More Information here.

Professor, PhD

Vipin Kumar

KUMAR, Vipin

University of Minnesota, USA

Professor, PhD

Dr. Vipin Kumar is a Regents Professor at the University of Minnesota, where he holds the William Norris Endowed Chair in the Department of Computer Science and Engineering. Kumar's research spans data mining, high-performance computing, and their applications in climate/ecosystems and healthcare. He has authored over 300 research articles, and has coedited or coauthored 10 books including two textbooks "Introduction to Parallel Computing" and "Introduction to Data Mining", that are used world-wide and have been translated into many languages. One of Kumar's current major research focuses on developing "Physics-Aware" machine learning techniques to understand the impact of human induced changes on the Earth and its environment. More Information here.

Jian Pei

Professor, PhD

PEI, Jian

Simon Fraser University, Canada

Professor, PhD

Dr. Jian Pei is working hard to facilitate efficient, fair, and sustainable usage of data and data analytics for social, economic and ecological good. Through inventing, implementing and deploying a series of data mining principles and methods, he produced remarkable values to academia and industry. His algorithms have been adopted by industry, open source toolkits and textbooks. His publications have been cited extensively. He is also an active and productive volunteer for professional community services. He is recognized as a fellow of the Royal Society of Canada (i.e., the national academy of Canada), the Canadian Academy of Engineering, ACM and IEEE. He is honored to receive a series of prestigious awards, including the ACM SIGKDD Innovation Award and Service Award. Currently he is a full professor at Simon Fraser University, Canada. More Information here.

Francisco Pereira

Director, PhD

PEREIRA, Francisco

National Institutes of Health, USA

Director, PhD

Dr. Francisco Pereira leads the Machine Learning Team at the National Institute of Mental Health (NIMH). The mission of the team is to assist NIMH and NIDA researchers who want to use machine learning methods to analyze their data (brain imaging, neural recordings, behaviour, text, sensor, etc). The team also develops new methods and analysis approaches, motivated by the unique application opportunities within NIH. Prior to that, he was a staff scientist at Siemens Healthcare, where he managed the Computational Neuroscience program. He did his postdoc at the Princeton Neuroscience Institute, working with Matt Botvinick and Ken Norman. He has a Ph.D. in Computer Science and Neural Basis of Cognition from Carnegie Mellon University, where he worked with Tom Mitchell and Marcel Just. He dislikes writing bios, and promises not to talk about himself in the third person during his talk. More Information here.

Jean Vanderdonckt

Professor, PhD


Université catholique de Louvain, Belgium

Professor, PhD

Dr. Jean Vanderdonckt is a Full Professor at the Université catholique de Louvain (UCLouvain), where he leads the Louvain Interaction Lab, which is conducting research and development in the area of Human-Computer Interaction (HCI), Information Systems, Intelligent User Interfaces (IUI), and Engineering of Interactive Computing Systems (EICS). He currently holds the Francqui Chair in Computer Science dedicated to Gesture Interaction. He is ACM Distinguished Scientist and Speaker and Co-editor-in-Chief of Springer Human-Computer Interaction Series. He received the Brian Shakel Award for outstanding work in HCI. More Information here.

Important Dates

August 21, 2021

October 01, 2021

Papers submission deadline

September 24, 2021

November 01, 2021

Notification of acceptance

October 23, 2021

November 21, 2021

Camera-ready versions and Early bird registration

October 28 - 30, 2021

December 1 - 3, 2021

Fully virtual conference


Contact Us

Juan Antonio Lossio-Ventura

Ph.D. in Computer Science

National Institutes of Health

Bethesda, USA

Hugo Alatrista-Salas

Ph.D. in Computer Science

Universidad de Ingeniería y Tecnología - UTEC

Lima, PERU