ABOUT DAVID WILD
David Wild is a researcher, practitioner and educator in data science, pharmaceutical research and crisis technologies. He is Associate Professor of Data Science and Informatics in the School of Informatics, Computing and Engineering (SICE) at Indiana University. He has founded and directed major research initiatives and educational programs including the Integrative Data Science Laboratory (IDSL), the IU Data Science Program, the IU Cheminformatics PhD Program, and most recently the Crisis Technologies Innovation Lab (CTIL). He is co-founder and President of Data2Discovery Inc., a company exploring with pharmaceutical customers the huge potential for AI and knowledge graphs in drug discovery. His research interests include data science for drug discovery and healthcare; cheminformatics; network chemical biology; crisis technologies, and data privacy, ethics and security. He is also active in multiple innovation and consulting initiatives, and is an advisor to several startups.
David completed a B.Sc. in Computing Science at Aston University, Birmingham, England in 1991, and a Ph.D. in Information Studies at Sheffield University, England in 1994. He worked for several years in scientific computing in the pharmaceutical industry, before moving into academia in 2004 to form new academic research and educational programs at Indiana University. He has around 100 research publications, and is founding editor of the Journal of Cheminformatics. He has been PI or CoPI on around $5m in funding. He is a certified Emergency Medical Technician (EMT) and is trained in Emergency Management.
You can contact David at djwild @ indiana.edu. You can read IU news stories about David here. Below are more details about David’s research and teaching.
AREAS OF RESEARCH
RELATED TEACHING AND EDUCATION
DS590 Data Science in Practice is a graduate course designed to help students gain critical, practical skills in applying data science to real world problems. Students will work in teams of 3-5 to tackle a real-world problem defined by a project sponsor. Project sponsors can be academics or industry practitioners. Students work with the project sponsor to understand the problem domain, identify where their data science skills can be applied, and to design, implement and test a solution.
INFO I426/516 Informatics in disasters and emergency response is an undergraduate/graduate elective designed for students interested in using technology and informatics skills in prevention of, mitigation of, response to and recovery from threats to safety, and emergency and disaster situations.
Info I590 Data and Society is a graduate course that introduces technically-trained students to the social, political, and ethical aspects of data science work. It is designed to create reflective practitioners who are able to think critically about how collecting, aggregating, and analyzing data are social processes, and processes that affect people.
RECENT BLOG POSTS
What if we could bring all the knowledge, data, insight, and prior decision-making of drug discovery together and use it to accelerate the discovery of new drugs? What if we could encode the millions of known relationships between potential new (or old) drugs, protein targets, genomics, biological processes, and disease mechanisms, and then use all this together to get new insights into disease and treatments?
A new report from FEMA shows efforts to encourage preparedness have failed, yet they are needed now more than ever. How can data science help?
There are now a plethora of apps and services that mean that if you do have internet service, you can to an amazing degree replicate the functions of an Emergency Operations Center (EOC) on the smartphone in your pocket. In this article we will describe a set of apps that will enable you to achieve the primary functions of the EOC: meeting & sharing space, phone and radio communications, situational awareness, and access to plans, documents and maps.
This is a five-minute flash talk on transforming pharmaceutical and healthcare companies into data companies.
Introducing Cheminformatics: an intensive self-study guide is a complete self-study guide designed to give you a rapid introduction to the emerging field of cheminformatics,
This is a talk given at the Pervasive Technology Institute at Indiana University on Big Data in Drug Discovery