Adam Lund
About Adam Lund
Adam Lund is a researcher with a PhD in Statistics from the University of Copenhagen. He has extensive experience in academia and finance, having worked at institutions such as Københavns Universitet and Barclays Investment Bank, and currently contributes to statistical methodology projects at Speevr, Inc.
Current Role at Speevr, Inc.
Adam Lund currently works as a researcher at Speevr, Inc. since 2020. His role involves applying statistical methodologies to projects that aim for positive social, economic, or environmental impacts. He is affiliated with Speevr Labs, where he contributes to research initiatives that leverage his expertise in statistics and quantitative analysis.
Previous Experience in Academia
Adam Lund has extensive academic experience, having worked at Københavns Universitet in various capacities. He served as a Postdoctoral Research Fellow from 2017 to 2018 and as a Research Assistant in 2013. Additionally, he was a PhD Candidate from 2013 to 2017, where he focused on statistical research. His teaching role at the university spanned 11 years, from 2007 to 2018.
Professional Background in Finance and Technology
Adam Lund has held positions in the finance and technology sectors. He worked as a Quantitative Analyst at Barclays Investment Bank from 2018 to 2019 and as a Senior AI/ML Quant at Argus Media for three months in 2021. He also served as a Visiting Scholar at Columbia University in 2015, where he engaged in research related to industrial engineering and operations research.
Educational Qualifications
Adam Lund holds a Doctor of Philosophy (PhD) in Statistics from the University of Copenhagen, which he completed from 2013 to 2017. He also earned a Master of Science (MS) in Mathematics - Economics from the same institution between 2008 and 2012, and a Bachelor of Science (BS) in Mathematics - Economics from 2003 to 2008. Additionally, he studied for a year in Architecture at The Royal Danish Academy of Fine Arts in 2002.
Contributions to Open Source Software
Adam Lund is an active contributor to open source software communities, particularly in R (CRAN) and Python (PyPi). He has published academic work that includes both manuscripts and software, demonstrating his ability to blend theoretical knowledge with practical applications in statistical methodologies.