Andreas S. Weigend, Ph.D.

My courses combine real-world case-studies with academic rigor.

Working with the CEOs of multinationals and the founders of startups has provided me with a rich set of insights into framing problems and producing results. In my classes, I combine anecdotes, guest speakers, and exercises using actual data sets with concrete, up-to-date information about data mining, algorithms, and machine learning.

My knowledge of recent developments in the field is built on my foundation of more than 100 published academic papers, and my 15 years of teaching experience. I choose examples that work, whether my students are engineers at Stanford, MBAs at Berkeley, or executives in the US and abroad. Many of my students have gone on to make game-changing moves.

My full-time teaching career started as an assistant professor in Computer Science and Cognitive Science at CU Boulder and continued as an associate professor at the Stern School of Business at NYU.

After founding a successful Internet startup, and being brought in as Amazon.com’s first chief scientist, I was approached by the Statistics Department at Stanford in 2003 to develop a course on data mining and e-business.

In 2008, the Haas School of Business at Berkeley asked me to create a course reflecting the impact of consumer participation on traditional marketing paradigms. I also teach in top executive MBA programs in Europe and China.

Stanford - Data Mining and Electronic Business (Stats / MS&E)

Data can be collected about consumer behavior on the web: on e-commerce sites, in social networks, on dating sites, on mobile phones and so on. This annual course focuses on applying data mining techniques to build predictive models of behavior, create (and reject) hypotheses, design cool experiments, and learn from them quickly.

The first half of the course focuses on data: what can be collected, and what it is useful for, queries and social search, tags, and interaction data such as email headers. The second half of the course discusses applications, ranging from personalization, recommendations and online marketing (behavioral and situational targeting), to the principles behind collective intelligence, reputation systems, and peer-production.

Students are expected to actively engage in class discussions, to have their assumptions challenged, and to bring their diverse backgrounds to bear.

UC Berkeley – Marketing in Web 2.0 (Haas School of Business)

This newly developed course explores the possibilities for customer-centric marketing in the era of Web 2.0.

In Web 1.0, companies collected data to cut costs and help optimize business processes. In Web 2.0, users are contributing a wide variety of both quantitative and qualitative data, including intentions, attention gestures, geolocation, social relationships, and more. Companies now have profound opportunities to create new technologies to support innovative services. Social recommendations and behavioral targeting are examples of recent uses of these forms of data. What are the implications for old and new business models, products and services? What are our insights and intuitions about what will work in practice? And what are the risks?

Tsinghua University - The Digital Networked Economy (School of Economics and Management, Tsinghua/INSEAD Executive MBA program (TIEMBA)).

This course discusses the impact of the communication and data revolution on individuals, business, and society. Companies now have the potential to create unprecedented internal transparency and value for their customers. Applications range from personalization, recommendations, and online marketing to collective intelligence, peer-production, and enterprise 2.0.

Specific topics covered in 2008 include:

• Enablers of the Digital Networked Economy
• Quantifying the business: Creating transparency
• Pricing and Scarcity in the Digital Networked Economy
• Feedback Marketing: Truly engaging users

Students will participate in class discussion and group exercises, and write a “reflection” paper.

Other schools in China:

I gave my first lecture in China in 1994, and have had a residence in Shanghai since 2000. Since my first courses at Peking University and at Fudan in 1994, I have taught thousands of executive at China’s top schools, including Tsinghua University, Shanghai Jiao Tong University, Cheung Kong Graduate School of Business, and CEIBS (China Europe International Business School).