Chief Scientist
& SVP of AI

Dataminr, NYC

Alejandro (Alex) Jaimes, Ph.D.

Scientist (Deep Learning, Machine Learning, Computer Vision, Artificial Intelligence), speaker, engineering executive. 15+ years of intl. experience in research (Columbia U., KAIST) and product impact at scale (DigitalOcean, Yahoo, Telef√≥nica, IDIAP-EPFL, Fuji Xerox, IBM, Siemens, and AT&T Bell Labs) in the USA, Japan, Chile, Switzerland, Spain, and South Korea. 100+ patents and publications. Columbia University Ph.D.. 

I leverage large-scale data using a Human-Centered approach to design, build, and deliver business value in novel algorithms for products used by millions of people. Core competencies:

  • Building and managing internationally distributed teams of scientists and engineers.
  • Strategic, technical, and operational leadership to maximize business impact of research.
  • Creating synergies as a catalyst between engineers, designers, product managers, and executives.
  • Communicating across diverse communities (70+ international invited talks).
  • Designing and leading implementation of algorithms, advanced metrics, and A/B tests.
  • Taking on projects that involve multiple stakeholders, delivering solutions that matter at the individual level, work at scale, and make business sense.

Diverse technical skills at the intersection of AI and User Experience across various industries (Cloud, Healthcare, News/Media):

  • Computer Vision, Data Mining & Machine Learning   
  • Content Recommendation & Social Discovery
  • Behavioral insights & Product strategy

I like to travel, read, and explore different cultures. I have lived in 8 cities in 4 continents [Bogota, New York, Santiago de Chile, Tokyo, Lausanne, Madrid, Barcelona, Daejeon] and traveled in 80+ countries [Flickr].

Past EU projects: Social Sensor, ARCOMEM, and the CENIT Social Media.

Recent invited talks

Recent papers
  • To Click or Not To Click: Automatic Selection of Beautiful Thumbnails from Videos. CIKM 2016.
  • TGIF: A New Dataset and Benchmark on Animated GIF Description. CVPR 2016.
  • Predicting celebrity attendees at public events using stock photo metadata. Multimedia Tools and Applications. 75(4): 2145-2167, 2016.
  • Mouse Activity as an Indicator of Interestingness in Video. ICMR 2016.
  • TGIF: A New Dataset and Benchmark on Animated GIF Description. CVPR 2016.
  • Humor in collective discourse: Unsupervised funniness detection in the New Yorker Cartoon Caption Contest. LREC 2016.