Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Brandon Anderson
Affiliation
Stanford RegLab, Stanford, CA, USA
Topic
Aerial Images,Agricultural Census,Artificial Neural Network,Aspect Ratio,Background Class,Convolutional Neural Network,Department Of Agriculture,False Positive,False Positive Predictions,Filtering Step,Image Classification,Image Segmentation,Intersection Over Union,Learning Rate,Multispectral Images,National Map,Object Detection,OpenStreetMap Data,Outside Of Range,Poultry Operations,Rank-order Correlation,Road Network,Semantic Segmentation,Spearman Rank-order Correlation,Training Area,Training Data,Training Set,Validation Data,Validation Set,
Biography
Brandon Anderson received the Ph.D. degree in physics from the University of California, Santa Cruz, in 2012.
He was a Research Associate with the Oskar Klein Centre for Cosmoparticle Physics, Stockholm, Sweden, where he focused on dark matter and statistical inference in gamma-ray astronomy. Pivoting into the startup world as a Data Scientist, he designed experiments and developed machine learning techniques for the analysis of large biological datasets with BioElectron Corporation, Mountain View, CA, USA, and led a team to build out real-time unsupervised fault detection systems in autonomous vehicles with Cognomotiv, Menlo Park, CA. Most recently, he has served as the Head of Data Science with Stanford's RegLab, Stanford, CA, where he provided research direction, team management, and technical support for a wide variety of projects in collaboration with government agencies and nonprofits. He is currently putting his considerable experience to public use at the Research, Applied Analytics, and Statistics Division, IRS.
He was a Research Associate with the Oskar Klein Centre for Cosmoparticle Physics, Stockholm, Sweden, where he focused on dark matter and statistical inference in gamma-ray astronomy. Pivoting into the startup world as a Data Scientist, he designed experiments and developed machine learning techniques for the analysis of large biological datasets with BioElectron Corporation, Mountain View, CA, USA, and led a team to build out real-time unsupervised fault detection systems in autonomous vehicles with Cognomotiv, Menlo Park, CA. Most recently, he has served as the Head of Data Science with Stanford's RegLab, Stanford, CA, where he provided research direction, team management, and technical support for a wide variety of projects in collaboration with government agencies and nonprofits. He is currently putting his considerable experience to public use at the Research, Applied Analytics, and Statistics Division, IRS.