A to B Lab: Algorithms to Business (Models)
AB Lab is set of research projects focused on the use of algorithms and data for business model innovation. AB Lab Projects are based on one of the Engineering Leadership principles that the role of algorithms, quantitative technologies, and large data sets will increasingly change business models and operations. For example, Google has replaced a direct sales force with a double-sided auction within its business model. This innovation would be unthinkable for any large firm 20 years ago.
AB Lab Projects have included collaborations with McKinsey & Co. for Business applications or real world customer problems in web design, sentiment analysis, and recommendation systems. Another AB Lab project collaboration focused on the algorithm and network design for Electric Vehicles, placement of charging infrastructure, and economic factors. Yet other AB Lab projects focus on quantitative algorithms for financial investment.
Sample Reports from AB Lab Projects
- Ikhlaq Sidhu, Andrew Lim, Max Shen, UC Berkeley Anoop Sinha, McKinsey & Company, Quantitative Technology Methods that can Improve Business Operations, CET Technical Brief, March 2011, link
- The Road Into the Cloud, Engineering Leadership White Paper, 4/2014 (link)
- Internet Privacy, Engineering Leadership White Paper, 3/2013 (link)
- Brick and Mortar 2.0, Lessons from Engineering Leadership, white paper, 10/2012 (link)
- Trends in Customer Loyalty Rewards Aggregation, Engineering Leadership White Paper, 3/2012 (link)
- Sidhu (PI), et al,”Impact of Widespread Electric Vehicle Adoption on the Electrical Utility Business – Threats and Opportunities”, CET Technical Brief., 8/2009. link
- Sidhu (PI), with T. Becker, et. al, “Electric Vehicles in the United States: A New Model with Forecasts to 2030”, CET Technical Brief, 8/2009. link
- Papavasiliou, Oren, Sidhu, Kaminsky, “Renewable Energy Supply for Electric Vehicle Operations in California”, 32nd International Association for Energy and Economics International Conference, San Francisco, 2009. link
- Self-Driving Cars, Engineering Leadership White Paper, 3/2013 (link)
The three projects in quantitative investment algorithms are not posted for download. The topics of the projects include co-integration, multi-moment analysis, trend correlations, backtest strategies, trading business models, genetics algorithms based testing, and related case studies.