I am driven to help people discover the world through images. I firmly believe that by first understanding how humans see and respond to images, we can then more effectively teach computers to do the same. To capture human responses to imagery, I have used techniques such as neuroscience, behavioral psychophysics, large-scale crowd-sourcing experiments, real-time A/B testing on commercial websites, and data analytics. With a deep understanding of human perception, I led the development and deployment of a highly scalable platform capable of generating billions of personalized image selections using computer vision, machine learning, and deep convolutional neural networks leveraging faster-than-real-time algorithms. These underlying computational models powered a variety of commercial products: image recommendation, image search, video thumbnail recommendation, GIF creation, thumbnail capture from live streams, and image recommendation from in-app cameras.
 
By commercializing image science from an academic research setting into a commercial platform, I gained an extensive understanding of the power of images to influence behavior and drive business results.  I am honored to have received a number of awards for my work, including Fast Company’s Most Creative in Business, the World Economic Forum’s Technology Pioneer, the Edison Award for Innovation, and the National Science Foundation’s SBIR Phase I & II.

EXPERIENCE
 
Co-Founder, Neon Open (Jan 2017 - present)

  • Launched open source platform for emotional AI: Neon Open
  • Led mission and vision for the platform 
  • Oversaw engineering, legal/IP, university relations, and marketing development
  • Platform to publicly launch October, 2017

Strategist, AI4ALL; Palo Alto, CA
(Jan 2017 - May 2017)

  • Worked directly with world leaders in artificial intelligence, Fei-Fei Li and Olga Russakovsky, on their mission to bring a diversity of voices to the field of AI.
  • Launched AI4ALL website
 
Co-Founder & Chief Science Officer, Neon Labs; San Francisco, CA
(Dec 2015 - Dec 2016)

  • Led the transition of the Neon Platform from GIST/nearest neighbor machine learning model into a deep convolutional neural network (DCNN)
  • Conceived of and led the development of in-camera image selection that deploys a highly optimized version of Neon’s deep learning model locally on a mobile device
  • Planned and prioritized the 2016/17 product roadmap
  • Built a strategic patent portfolio covering image and video software, hardware, and artificial intelligence 
  • Oversaw the product management, product marketing and deployment of the following new products into the market: image optimization, video clipping/GIFs, personalized images
  • Managed and developed a team of expert data scientists, machine learning and AI researchers and engineers, computer vision experts, and large-scale system engineers (PhDs hired from CMU, Stanford, MIT, who are now working at Google, Microsoft, Magic Leap, Amazon, other CV/ML focused startups)
  • Developed internship program where interns created self-directed, patentable work
 
 
Co-Founder & Chief Executive Officer, Neon Labs; San Francisco, CA
(Oct 2012 - Dec 2015)

  • Raised $10MM in public and private funding from NSF & Silicon Valley venture capitalists
  • Built and scaled a collaborative, vision-driven culture at Neon 
  • Launched Neon image selection platform, which analyzed 10 billion images and 100,000 hours of video
  • Hired and developed a high-performing team of engineers, designers, sales, operations, finance
  • Managed executive-level business relationships with Fortune 500 companies
  • Facilitated employee growth into new roles within the company
  • Generated hundreds of thousands of dollars in commercial revenue
 
Post-doctoral Researcher, Carnegie Mellon University; Pittsburgh, PA
(Sept 2011 - Oct 2012)

  • Conducted functional MRI research on rapid, unconscious emotional image perception
  • Developed behavioral tasks proven to correlate with the neural emotional response to images, resulting in a dataset of “tagged” images used to train machine learning image prediction models
  • Awarded a National Science Foundation grant to commercialize machine learning models capable of generating reliable predictions of image performance
  • Worked with technology transfer offices at CMU, Brown University, and Harvard Medical School/Massachusetts General Hospital  to license university IP that was foundational to my startup, Neon
 
EDUCATION
 
Brown University, Providence, RI
Department of Cognitive, Linguistic, and Psychological Sciences
PhD in Cognitive Neuroscience
2011
 
Glasgow University, Scotland, UK
1st Class Honors, Psychology
2005
 
University of California, San Diego, CA
Junior Year Abroad
2004-2005
 
SELECTED PATENTS

  • Method and system for using neuroscience to predict consumer preference
  • Automated thumbnail selection for online video
  • Method for clustering novel facial images based on identity 
  • A method for measuring implicit visual responses with an online task
  • Selecting a personalized high-valence representative image
  • Automatic optimization of image capture on mobile devices by human and non-human agents
  • Method for determining image similarity in a multidimensional valence feature space
  • Method for measuring implicit valence of images through web events
  • Systems and methods of generating a modified-view video from a video file based on valence 
 
SELECTED PUBLICATIONS
 
Lebrecht, S., Bar, M., Feldman Barrett, L., & Tarr, M.J. Micro-valences: Perceiving Affective Valence in Everyday Objects. Frontiers in psychology 3. 2012: doi:10.3389/fpsyg.2012.00107

​Lebrecht, S., & Tarr, M. J. Can Neural Signals for Visual Preference Predict Real-World Choices? BioScience. November 2012 / Vol. 62 No. 11

Roos LE, Lebrecht, S., Tanaka JW., Tarr MJ. Can singular examples change implicit attitudes in the real-world? Front Psychol. 2013 Sep 5;4:594. doi: 10.3389/fpsyg.2013.00594
 
Lebrecht, S., Pierce, L., Tarr, M. J., & Tanaka, J. (2009). Perceptual other-race training reduces implicit racial bias, PLoS ONE, 4(1), e4215 doi:10.1371/journal.pone.0004215
 
 
IMAGE THOUGHT LEADERSHIP    
 
Relevant Blog Posts
  • Images that make you click (blog post)
  • Why we can’t stop looking at Beyonce (blog post)
  • Perception and the Apple Store (blog post)
  • Gisele surfs Chanel: Waves, Diamonds, & No. 5 (blog post)
 
 
INDUSTRY LEADERSHIP

  • Future of Images: Conceptualized and spoke at Neon’s Future of Images panel at the International Center for Photography in NYC with Met Museum, CBS, Bloomberg, ESPN, Princeton (video)
  • Chasing the Unicorn: Determining the Value of Art and Tech Conceptualized and moderated discussion with Bonhams Fine Art, True Ventures, NVCA (video)
  • Images and Time: Conceptualized and moderated discussion with Getty Images, Huffington Post, and Hearst (blog post)
  • Future of Human Rights and Technology: Conceptualized panel discussion about the future of images and their impact on human rights, with WITNESS, the White House, UC Berkeley, and True Ventures (blog post)
 
Selected Speaking Engagements

  • Human Cognition, Meet Video in the Social Age: Online News Association (slides and audio)
  • Discovering the World through Images: Brown University (video)
  • When Algorithms are Biased: The Hive Think Tank (video)
  • Carnegie Mellon Interactive Technology: SXSW (article)
  • Picture Perfect: Business Insider IGNITION (article)
 
Selected Partnerships

  • WITNESS - collaborating on projects at the intersection of image technology and human rights
  • Bonhams - partnering to understand how image technology and big data intersects with fine art
  • Brightcove - collaborating to bring Neon’s image technology to Brightcove’s media and brand customers
  • Partnership Philosophy - partnership guidelines and learnings, featured by the Tory Burch Foundation (article)
 
Media Coverage

  • Most Creative People in Business - Fast Company (article)
  • New Software Sifts Photos for the Most Clickable - Wall Street Journal (article)
  • Steve Blank Introduces Scientists to a New Variable: Customers - Forbes (article)
  • Here are the 6 Best Images of CES (According to Neon Labs) - TechCrunch (article)
 
Awards
  • World Economic Forum Technology Pioneer (video)
  • Best New Product at National Association of Broadcasters Conference – Neon Live (video)
  • Cannes Lions – selected to present at Innovation Festival
  • NSF Small Business Innovation Research grant, Phase I & II
  • Most Creative People in Business, Fast Company (article)
  • Edison Award for Innovation (article)
 
PHD RESEARCH & TEACHING
 
Research

How Visual Face Training Reduces Implicit Racial Bias  
“Micro-valences”: Affective Valence in “Neutral” Everyday Objects  
Commercializing Image Research
  • Commercialized doctoral research on valence with the help of governmental grants and NSF I-Corps fellowship 
  • White House (blog post)
 
Teaching
 
Brown
  • Theatre and Neuroscience, Teaching Assistant, 2008
  • Perception and the Mind, Teaching Assistant, 2009
  • Functional Magnetic Resonance Imaging: Theory and Practice, 2009
  • How Implicit Biases Affect Our Teaching Practices, 2009
  • Introduction to Cognitive Neuroscience, 2010
 
Rhode Island School of Design
  • Face Perception and the Brain, 2008
  • Strategy Marketing for Designers in Industrial Design department, 2011

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