Meet the SoDa Labs team.
Klaus is Lecturer at the Department of Econometrics and Business Statistics at Monash University. His passion is in technology, economics, data and computational approaches to get exciting insights about human behaviour. Broadly speaking, his research sits under the headline: how does technological progress affect societies and vice versa? What behavioural patterns that were disguised previously can now be researched as people reveal their choices through the use of technology? How can we use collected data to improve operational outcomes of not for profit organizations by using Machine Learning? There are social issues that need to be addressed on an individual level, but he believes it is possible to impact the world on an aggregate level by using data.
Simon Angus is a computational and complexity scientist and Associate Professor of the Department of Economics, Monash University. With a background across the physical and social sciences, he has diverse interests including complex systems science, data-science, networks, systems biology, evolutionary game theory and most principally in Economics, the study of technology and innovation. Simon has co-founded a number of academic, commercial and not-for-profit impact outlets including KASPR Datahaus Pty Ltd, the IP Observatory, and SharedIntentions.net.
Simon is also a multi-award winning educator for his innovations in peer-assessment, feedback and in-class learning design, most often supported by learning analytics software he has developed.
Claudio Labanca is lecturer in the Department of Economics at Monash University. He joined the department in 2017 after completing his Ph.D. in Economics at the University of California, San Diego. His research falls at the intersection of labor economics and public economics and it covers a variety of topics, including wage and productivity differentials across firms, the effects of taxation on the supply of labor, and the impact of migration on local labor markets.
This research extensively uses big administrative data sets. In his work, he pays particular attention to the role played by the interaction between worker and firm behavior in shaping demand and supply of labor, wages and productivity. To estimate these interactions, he applies the latest econometric techniques on detailed matched employer-employee data.
Nathan is a Lecturer in Monash University's Department of Economics researching in the fields of political economy, economic development, growth, and economic history. A key area of focus is the evolution of developing economies during the Cold War, using new empirical tools to understand how conflict, elite politics, and state institutions shape economic outcomes
From studying post-colonial regimes to historic autocracies, he has developed passion for using creative techniques to create machine-readable data. Nathan has experience working with modern, high-dimensional statistical methods, as well as traditional archive hunting and digitization. His current projects use natural language processing to distill structured data from unstructured data.
Weijia is a lecturer in the Department of Economics at Monash University. He holds a Bachelor degree in Economics and Finance from Tsinghua University and a Ph.D. in Economics from University of California, Berkeley. He works on political economics, development economics, and economic history. He is especially interested in the origins and evolutions of meritocratic bureaucracy, as well as its interactions with other economic, political, and social institutions. To investigate these issues, he builds and analyzes both economic models and original datasets collected from rich historical records. These datasets reveal novel empirical patterns of political institutions for over one thousand years of Chinese history. Currently, he is applying natural language processing to historical documents, aimed at rendering them analyzable by econometric tools. He is also developing new models to rationalize and interpret novel patterns from datasets generated by historical records.
Paul is Associate Professor of Economics at the Department of Economics at Monash University.His research interests are in the fields of political economy, environmental economics, insurance economics and development economics.
Paul's research has been published, among others, in the Quarterly Journal of Economics,Journal of the Association of Environmental and Resource Economists, Journal of Environmental Economics and Management, and Journal of Public Economics. Some of his work has been featured by media outlets such as The Economist, The Washington Post, Wired, or MIT Tech Review.
Paul the founding director of datainspace, co-founder of the IP Observatory, and co-founder and one of the directors of KASPR Datahaus PTY LTD
Nandini is a PhD candidate in machine learning at Monash University. Her research focuses on clustering in high dimensional, sparse data sets. She completed her masters degree with specialisation in data science from Monash University in 2016.Prior to starting the graduate studies, she worked as a software developer for seven years, building products on Microsoft and MEANstacks. The passion for programming continues, and is now channeled towards machine learning programs in R and Python.
Eshan is an Economics honours student at Monash University and completed his undergraduate degree there in 2017, with majors in Economics and Econometrics. His research this year focuses on predicting social unrest using alternative data and machine learning. Previously, Eshan has worked in the modelling team at Frontier Economics where he helped develop real-time price visualisation tools for better insight into Australian electricity markets. He is passionate about utilising analytics to approach our most important public policy questions and hopes to continue his learning in this space.
Simon is a final-year undergraduate student at Monash University, studying a Bachelor Business Information Systems and a Bachelor of Commerce, majoring in Economics. His main interest is in combining analytics and modelling in a policy context. He has previously worked as a Marketing Analyst Intern at Xero, where he used R to automate weekly reporting and used NLP to provide insight on feedback from Marketing events. Additionally, he has worked on an education / technology consulting project for a social enterprise in Bangalore, India. He was the Team Leader for the project, which used a Human-Centred Design approach to inform project recommendations.
Miethy completed her undergraduate studies at North South University, Bangladesh and graduate studies at University of Nottingham, United Kingdom. She is currently doing her PhD at the Department of Economics at Monash University. Prior to moving to Australia, Miethy worked as a research assistant at the Policy Research Institute, Bangladesh and as a lecturer at North South University, Bangladesh. Her PhD thesis involves using data science and machine learning approach to derive socioeconomic information from alternative data sources like satellite images and Open Street Map.
Ashani is a PhD candidate in Economics at Monash University. Her primary research interests are political economy, development economics and economic shock treatment. Her PhD thesis focuses on using novel geocoded data at very fine spatial and temporal resolutions to explain trends in economic phenomena. Ashani completed her honours degree in Economics at University of Colombo, Sri Lanka. She worked for four years as an investment/finance specialist and as a lecturer at University of Colombo, before starting her PhD journey.
David is currently a PhD Student in Economics at Monash University. His research interests are comprised of political economy, civic conflict, and comparative development. David completed his Masters at the LMU Munich, where he constructed a novel subnational dataset for demographic structures in Sub-Saharan Africa to shed light on the nexus between civil conflic trisk and youth bulges. His future research projects will utilise GIS software and machine-learning techniques to contribute to a better understanding of human rights violations and civil conflict.