Marc Lajeunesse | University of South Florida
Marc is an Associate Professor in ecology and evolutionary biology at the University of South Florida. He is an elected member of the Society for Research Synthesis Methodology (SRSM) and has 15 years of experience in research synthesis methods. Marc has developed meta-analysis and systematic review tools in Python (OpenMEE) and R (metagear).
Wolfgang Viechtbauer | Maastricht University
Wolfgang is associate professor of methodology and statistics at Maastricht University in the Netherlands. His research is primarily focused on developing statistical methods and software for meta-analysis and the design and analysis of longitudinal and multilevel studies using appropriate mixed-effects models. He is author of the metafor package for R, which covers a wide variety of standard and advanced meta-analytic methods (e.g., fixed/random/mixed-effects models, meta-regression, multilevel and multivariate meta-analysis, network meta-analysis, phylogenetic and spatio-temporal models).
The participants in the inaugural Evidence Synthesis Hackathon are listed below, in alphabetical order by last name. This list will be updated as we confirm details for the remaining participants.
Laurie Baker | University of Glasgow
Laurie is a final year PhD student in Biology at the University of Glasgow. For her PhD she is using Bayesian state-space models to understand spatial and temporal patterns in disease transmission. During her masters and bachelors in marine biology she studied grey seal movement off the coast of Nova Scotia and the effect of management decisions on the Chilean pink cusk-eel fishery. Her interests are in spatial modeling and she’s recently discovered the joys of text analysis and topic modeling.
Sergio Leonardo Benítez Díaz | Prodigious
Sergio is a system engineer with the emphasis on the design of user interfaces for improved user experiences. His work focussed on improved human-machine interactions and novel tools for data visualisation. His interests include football, tennis and travel.
Panagiotis Bozelos | University of Oxford
Panagiotis is a PhD candidate in Theoretical and Computational Neuroscience, with a major in Molecular Biology and Genetics. He is also employed as a Data Analyst at the Centre for Neural Circuits and Behaviour, University of Oxford. His research interests revolve around hippocampal processing functions of spatial and non-spatial information. He is also interested in the fields of Machine Learning / Artificial Intelligence, and History / Philosophy of Science.
Katie Corker | Grand Valley State University
Katie is a quantitative methodologist and assistant professor of psychology at Grand Valley State University. Her personality and social psychology research seeks to understand motivational differences between individuals. Katie also has active research interests that intersect with the open science and reproducibility in science movements. Together with others in the community (see improvingpsych.org), she is working to build and support structures that improve methods and practices in psychology. She also has a particular interest in meta-analysis and cumulative knowledge building.
Brian Cottrell | AT&T
Brian is a mobile software engineer and hackathon enthusiast from Redondo Beach, California. He received his degree in physics from the University of California, Santa Barbara and currently works on developing mobile and TV applications at AT&T. In his free time, he enjoys building prototype software as a part of hackathons or other challenge events as well as competitive sailboat racing.
Sanita Dhaubanjar | International Water Management Institute
Sanita is a research officer in the Water Futures group at the International Water Management Institute. A water resources engineer by degree, Sanita currently supports watershed modeling research with hydrological and climate data processing, analysis and visualization. Her primary interest is the application of models and data analysis to provide information needed to achieve equitable and transparent water governance and management. In that pursuit, she has worked in environmental modeling, hydro-meteorological monitoring, hydroeconomics and forecasting. Sanita is passionate about finding novel ways to synthesize and visualize scientific evidence to support better decision making in water management.
Spencer Dixon | UN Environment World Conservation Monitoring Centre
Spencer is a full stack web developer at UN Environment World Conservation Monitoring Centre in Cambridge, UK. He currently works on creating various web based tools like ProtectedPlanet.net and SpeciesPlus.net that allow organisations and governments to make better decisions around conservation and biodiversity. In his spare time, he is experimenting with machine learning in conservation, speaking about blockchain, and making music.
Jacqui Eales | Exeter University
Jacqui is an evidence synthesis specialist who has spent the last 9 years working in systematic reviews in the environmental management and human health sectors. Her background is in ecology and conservation, having completed a PhD in genetics of tropical invasive species in 2008. She is PI on a long-term research project characterising the terrestrial and marine biodiversity of a tropical forested Caribbean island, Dominica, in partnership with the NGO Operation Wallacea and the Dominican Government. Jacqui has also focused on education and capacity building, previously holding a position as Lecturer in Conservation at Bangor University, UK.
Andrew Feierman | Data-Driven Yale
Andrew is a Quantitative Analyst for the Yale Data-Driven Environmental Solutions group. His research and experience is centered around energy efficiency in real estate. Prior to joining Yale, he worked for the Institute for Market Transformation in Washington, DC, where he modeled city-level environmental policies and worked with real estate companies to reduce energy consumption within their buildings. He has a B.A. from American University’s School of International Service, and further education from the New York City Data Science Academy.
Matt Grainger | Newcastle University
Matt is a Research Associate in the Modelling, Evidence & Policy Research Group at Newcastle University. He works with graphical Bayesian decision models to contextualise scientific evidence for the benefit of policy makers in the realm of biodiversity conservation and sustainability. He is an expert in combining quantitative and qualitative data and dealing with high levels of uncertainty. He also has a side-line in the conservation of pheasants, predominately in Southeast Asia.
Charles Gray | La Trobe University
Charles is a proud mathbassador for the Australian Mathematical Sciences Institute’s Choose Maths program. Her role as a math-talking-doing-advocate grrrl is a relatively new career development, after spending almost twenty years working as a classically-trained pianist and music teacher. She lectures at La Trobe University, where she is undertaking a PhD in statistical data science and takes an active role in the Victorian branch of the Statistical Society of Australia. She likes to think of herself as a data detective who tells stories with data. Charles thinks she has the best job in the world.
Sarah Han | Collide LLC
Sarah is a multi-disciplinary software engineer and UX/UI designer with skills in front end development, 3D web visualizations and 3D modeling. She is passionate about integrating design and technology to develop beautiful, functional and interactive products that enhance people’s lives. Sarah is particularly interested in emerging and experimental technologies. She regularly participates in hackathons to create innovative inventions.
Udit Jain | Data-Driven Yale
Udit is a Senior at Yale College where he is a double major in Computer Science and Statistics & Data Science. He’s worked on numerous projects as a researcher with the Data Driven Environmental Research group at Yale. Most of his projects leveraged his interest and expertise in large scale data analysis, machine learning, natural language processing and network science. His other research projects have focused on deep learning. Udit is also passionate about startups and venture capital and serves as a Partner at Dorm Room Fund.
Peter Ma | Clean Water AI
Peter has been a software developer for more than 14 years, and has been involved in many start-ups and projects that pushed the envelope of innovation. He is part of the Intel Software Innovator program, and focusses on emerging technologies like AI and IoT. He is currently working on Clean Water AI, an AI system that detects dangerous bacteria in the water sources.
Biljana Macura | Stockholm Environment Institute
Biljana is a Research Fellow at SEI, Sweden. She is an environmental social scientist with interdisciplinary background. She holds a PhD in forest policy from University of Padova, Italy and Bangor University, United Kingdom. Biljana is currently working with the MISTRA EviEM project (www.eviem.se) on evidence synthesis in the field of environmental management where she conducts systematic reviews, provides training and works on improvement of systematic review methods. Biljana is also Editorial Manager of the Collaboration for Environmental Evidence journal – Environmental Evidence.
Andrew Martin | University of Oxford
Andrew is in the final stages of his DPhil in long-term ecology at Oxford University. He uses dendroecological, stable isotope, and mechanistic modelling techniques to address questions surrounding Arctic ‘shrubification’. Andrew became interested in evidence-based techniques through creating an evidence-map of the controls on Arctic shrub growth and expansion. With a background as a software developer (in Government, and as an intern at Microsoft Research), coding is central to all aspects of his research, particularly the application of functional programming and web technologies. Aside from his Arctic research, Andrew is also lead researcher on the Global Pollen Project (globalpollenproject.org), which aims to establish a global pollen taxonomy.
Geoffrey Martin | Yale NUS College
Geoffrey is a third-year undergraduate student from Yale-NUS College majoring in computer science and statistics. He has spent time conducting data driven research on economics, dating, health policy and the environmental sciences, for several research centers at his university and in the data analytics industry. His interests span the intersection of data science and macrosociological issues, and will be spending the coming summer as a machine learning intern at NASA’s Jet Propulsion Laboratory.
Christopher Penkin | Digital Solution Foundry
Chris has 16 years web and application development experience, working on a wide range of different technologies over the years. His passion is to not just creating great software, but great looking, easy to use software where the user is the central character of any solution.
Daniel Perez | Epistemonikos
Daniel studied Computer Science, and co-developed Expenews.com in 2007, a service to allow mountaineers and adventurers to share their experiences of Antarctica or Everest in realtime. In 2009 he traveled to Silicon Valley to co-found Zappedy (since acquired by Groupon), and then in 2011 co-created Epistemonikos with Gabriel Rada, a non for profit that seeks to provide the best evidence in health. Today Epistemonikos is the world’s largest systematic reviews search engine. He teaches about Blockchain and cryptocurrencies, and programs in Python, Ruby and Node. XP (of Agile development) and Customer development are strong influences on his approach to software development.
Gihan Samarasinghe | University of New South Wales
Gihan is a Research Associate in the School of Biological Earth and Environmental Sciences (BEES) of University of New South Wales (UNSW), Sydney, Australia, and mainly working in the project titled “Developing a Methodology for Systematic Review and Establishing Synthesis Methodology in Built Environment: Towards Evidence-Based Practice and Policy”. Gihan did his PhD in Machine Learning and Computer Vision in the School of Computer Science and Engineering of UNSW and he has research and industrial experience in Machine Learning, Database Systems, and Software Engineering.
Gorm Shackelford | University of Cambridge
Gorm works on sustainable agriculture as part of the Conservation Evidence project at the University of Cambridge (www.conservationevidence.com). He systematically reviews evidence for the effects of agricultural practices on soil, water, biodiversity, crops, and other variables. His academic training was not in computer programming, but he has increasingly been using Python (Django) to develop web apps, such as a crowdsourcing platform for systematic reviews of global catastrophic risks (www.x-risk.net) and a platform for meta-analysis that is now in development. He has used R extensively for meta-analysis, GIS, and statistical modelling. Before he started working in academia, he was a professional portrait photographer (www.gormshackelford.com).
Ezgi Tanriver-Ayder | University of Edinburgh
Ezgi is a Biostatistician and a PhD student at the Centre for Clinical Brain Sciences working with the CAMRADES group. Her research focuses on improving statistical approaches for meta analysis in preclinical drug discovery research. Her key interest is on providing solutions to reproducibility issue and enhance ways to translate the obtained outcomes from animal research to human studies. Her project mainly involves reviewing existing statistical methods used in systematic review and meta analysis of preclinical data as well as developing new techniques to overcome the limitations in the existing tools, including Bayesian approaches.
Juan Vásquez | Epistemonikos
Juan is a software engineer at Epistemonikos Foundation. He has contributed on the development of the Epistemonikos database (www.epistemonikos.org) and some other projects on the evidence synthesis field such as iSoF (Interactive Summary Of Findings), iEtD (Interactive Evidence To Decision) and most recently L·OVE (Living OVerview of the Evidence) which is a platform with evidence organized by PICO question designed to make possible the creation of living overviews. His interests are data visualization, data processing, data mining and machine learning.