Peter Swartz
Co-Founder and Chief Science Officer of Altana AI.
Peter Swartz is co-founder and chief science officer at Altana AI. Altana's mission is to power a new era of globalization defined by Trusted Networks, which span and connect governments, businesses, and civil society to shape a more resilient, secure, efficient, and fair world. Peter has spoken on global trade, supply chains, and machine learning at the World Trade Organization, the World Customs Organization, the US Court of International Trade, the National Academies of Medicine, and the O’Reilly and Wolfram conferences. Previously, Peter was Head of Data Science at Panjiva (listed as one of Fast Company’s most innovative data science companies in 2018 and sold to S&P Global). He holds a number of patents in machine learning and global trade. Peter completed his undergraduate and graduate education at Yale, MIT, and the Federal Polytechnic of Lausanne (EPFL), with a focus on engineering, statistical methods, and global trade. He has high-level proficiency in both French and Chinese.
Peter is motivated by the automated generation of explainable and reliable insight and decision support across global scale datasets to facilitate public and private sector operation in a turbulent world. He has deep expertise in data processing and artificial-intelligence/machine-learning (AI/ML) systems. The focus of his work is large scale hybrid AI/ML systems that generate insight across billions of records using both classic machine learning, deep learning, and modern generative AI. He also has experience in knowledge graphs, network analysis, natural language processing (NLP), and explainable AI.
Peter Swartz is co-founder and chief science officer at Altana AI. Altana's mission is to power a new era of globalization defined by Trusted Networks, which span and connect governments, businesses, and civil society to shape a more resilient, secure, efficient, and fair world. Peter has spoken on global trade, supply chains, and machine learning at the World Trade Organization, the World Customs Organization, the US Court of International Trade, the National Academies of Medicine, and the O’Reilly and Wolfram conferences. Previously, Peter was Head of Data Science at Panjiva (listed as one of Fast Company’s most innovative data science companies in 2018 and sold to S&P Global). He holds a number of patents in machine learning and global trade. Peter completed his undergraduate and graduate education at Yale, MIT, and the Federal Polytechnic of Lausanne (EPFL), with a focus on engineering, statistical methods, and global trade. He has high-level proficiency in both French and Chinese.
Peter is motivated by the automated generation of explainable and reliable insight and decision support across global scale datasets to facilitate public and private sector operation in a turbulent world. He has deep expertise in data processing and artificial-intelligence/machine-learning (AI/ML) systems. The focus of his work is large scale hybrid AI/ML systems that generate insight across billions of records using both classic machine learning, deep learning, and modern generative AI. He also has experience in knowledge graphs, network analysis, natural language processing (NLP), and explainable AI.
