Abe Botros



  • Helping to maximize the probability of the long-term survival and wellness of humanity and all other life on Earth (now and throughout the future).
    • Climate change is currently the biggest existential threat to humankind, as well as all other species on Earth. We must rally to fight against it if we want to save as much life on Earth as possible from climate disaster and if we want to preserve a bright future for all humanity.
    • Life on Earth represents the only known life in the universe; we must protect it at all costs. We must not blink out of existence just yet.
    • Special interest: food and agriculture - we'll always need to eat, and what we eat is directly related to our wellbeing. In particular, we must produce healthy and diverse food in a way that is sustainable for the environment, sustainable from a socioeconomic standpoint, and resilient against climate change.
  • Pursuing real-world applications of artificial intelligence and machine learning.
    • Special interest in applying machine learning and large-scale data as part of a climate tech / ag-tech solution.
  • Bringing humanity together as one family by seeing the bigger picture of our existence and how meaningless our conflicts are in light of this.
    • Breaking down imagined barriers to instead work together towards a brighter future.


  • Senior machine learning engineer @ OpenSpace (2019-present)
  • Working on something new at the intersection of controlled environment agriculture, automation, and climate (2022-present)


  • On Deck Climate Tech fellow (Jul-Aug 2022)
  • On Deck Build for Climate fellow (Feb-Mar 2022)
  • Senior software engineer @ Marble (since acquired by Caterpillar) (2018-2019)
  • Engineer @ Human Dx (2016-2018)
  • Software engineering intern (web applications) @ Rocket Fuel (since acquired by Sizmek) (2014)
  • Research assistant at Stanford Vision Lab under Dr. Fei-Fei Li (2012-2013)
  • Member of UCLA Stroke Force organization (2011-2012)
  • NSF REU sponsored summer intern at the University of Michigan, Ann Arbor under Dr. Allison Steiner (2010)

Quick links:  LinkedInAngelListGitHub


  • Stanford University: M.S., Computer Science (2016)
    • Specializations: Artificial Intelligence, Real-World Computing
  • UCLA: B.S., Neuroscience (2012)


Personal Projects:

  • Tales
    • Social, worldwide, daily vlogging platform focused on simplicity and authenticity. Provides a quick and easy way for people around the world to vlog their daily lives, with the mission of bringing the world closer together as one family.
    • Built using Golang, Scala, PostgreSQL, Redis, React Native, TypeScript/JavaScript, Android/Kotlin/Java, iOS/Swift/Objective-C, and AWS.
    • (This platform has been retired as of 2021.)

Academic Projects:

  • Mars Hab-Bot
    • 2D simulation of robot constructing human-livable habitats on Mars. Modeled as Markov Decision Process (MDP), with multiple task phases implicitly formulated into transition/reward functions, allowing naturally solving the sequential phases without manual phase conditions or explicit instructions.
    • Manually modeled state and action spaces, transition and reward functions, and various “worlds”/difficulties. Applied varying degrees of model uncertainty (movement, object interaction, etc.). Used discrete value iteration to solve MDP.
    • Successful in simplistic settings, always achieving optimal policies and performances in minimal time.
    • Implemented using Julia, POMDPs.jl, and PyPlot.jl. Individual project. Dec 2015.
    • PDF, YouTube, GitHub
  • World Connector
    • Social network recommendation system for encouraging shared-interest, distance-based connections. Used Twitter network/dataset/API and Google Maps Geocoding API; acquired network structure and geographical locations for ~57,000 users, with 1 million connections between them. Generated simulated user interests vectors.
    • New user connection ranking and recommendation using network structure features, user geolocations and distances, and simulated interests. Successfully recommended both users with similar interests and geolocations (“distance-penalizing” mode) and with similar interests and distant geolocations (“distance-rewarding” mode).
    • Implemented using Python, Snap.py, and Gephi. Individual project. Dec 2015.
    • PDF, Poster
  • Quantum Hearts
    • 2D real-time puzzle game for Android OS using only Open GL ES 2.0.
    • Available on Google Play Store, built entirely from scratch with no external game libraries in under 10 days
    • Low-level handling of all shape drawing, shape texturing, game logic, player interaction, cross-thread communication, Android UI, etc.
    • Implemented using Android/Java and Open GL ES. Individual project. Aug 2015.
    • PDF, YouTube
  • HoloPanel
    • Mobile computer-vision/augmented-reality Android application. Performed real-time hand and finger tracking on a mobile device camera using only on-device computation. Interface enabled interaction with several on-screen functions via real-world hand and finger placement.
    • Used HSV-flesh probabilities with per-user/per-session calibration, CAMSHIFT and convex hull estimation for hand/finger localization, and Android for the augmented reality on-screen interface.
    • Implemented using Android NDK, C++, OpenCV, and Java/Android. Individual project. May - Jun 2015.
    • PDF, YouTube, GitHub
  • Galaxy Morphology Classifier
    • Machine learning and computer vision system for galaxy morphology characterization.
    • Used ~140K images from the Sloan Digital Sky Survey to provide outputs along ~40 continuous-valued morphology categories. Preprocessing involved cropping, Gaussian filter smoothing, downsampling, and rotated image copies for rotational invariance.
    • Used (Dense) SIFT, radii-based spatial descriptors, HSV, and bag-of-visual-words for features. Used K-nearest neighbors regression, ridge regression, support vector regression, and convolutional neural networks for learning. RMSE for eval.
    • Implemented using Python, OpenCV, scikit-learn, and Caffe. Individual project. Feb - Mar 2015.
    • PDF
  • Planet Hunter
    • Machine learning system to detect exoplanets using NASA Kepler Space Telescope data and planetary transit detection method applied to Kepler brightness time series data.
    • Noise reduction via sliding-window percentage-change transformation. Engineered manual features extracted from time series data, considering properties such as global statistics, peak width/magnitude/frequency, inter-peak width, etc. Applied k-means clustering and PCA methods for dimensionality reduction.
    • Used k-nearest neighbors, logistic regression, softmax regression, SVMs, and k-fold cross validation for classification. Achieved ~85% test classification performance.
    • Implemented using Python, NumPy, matplotlib, and LIBSVM. Individual project. Sep - Dec 2014.
    • PDF, Poster

Open-Source Projects:

  • LORE: Light Object-Relational Environment (LORE). Provides a simple and lightweight pseudo-ORM/pseudo-struct-mapping environment for relational database interaction using Golang.
  • Geocoder: Simple REST API server for geocoding addresses, implemented in Python.


  • Michelle R. Greene, Abraham P. Botros, Diane M. Beck, Li Fei-Fei. What you see is what you expect: rapid scene understanding benefits from prior experience. Atten Percept Psychophys (2015) 77:1239–1251, doi:10.3758/s13414-015-0859-8. Info, PDF
  • Michelle R. Greene, Abraham P. Botros, Diane M. Beck, Fei-Fei Li. Visual Noise from Natural Scene Statistics Reveals Human Scene Category Representations. CoRR (2014) 1411.5331. Info
  • Michelle R. Greene, Abraham P. Botros, Diane M. Beck, Li Fei-Fei. Discovering mental representations of complex natural scenes. Journal of Vision (2013) 1093-1093. 10.1167/13.9.1093. Info
  • Abraham P. Botros, Michelle R. Greene, Li Fei-Fei. Oddness at a glance: Unraveling the time course of typical and atypical scene perception. Vision Sciences Society conference, May 2013. (Poster presentation) PDF
  • Michelle R. Greene, M. R., Abraham P. Botros, Diane M. Beck, Li Fei-Fei. Discovering mental representations of complex natural scenes. Vision Sciences Society conference, May 2013. (Oral presentation)
  • Michelle R. Greene, Abraham P. Botros, Diane M. Beck, Li Fei-Fei. Internal representations of real-world scene categories. Cognitive Neuroscience Society conference, April 2013. (Poster presentation)
  • Abraham P. Botros, Todd Sigi Hale. Beat-induced auditory brainwave entrainment. Annual UCLA Science Poster Day, May 2012. (Poster presentation)
  • Abraham P. Botros, Todd Sigi Hale. Beat-induced auditory brainwave entrainment. Annual UCLA Neuroscience Poster Session, May 2012. (Poster presentation)
  • Steiner, A. L., Pressley, S. N., Botros, A., Jones, E., Chung, S. H., and Edburg, S. L.: Analysis of coherent structures and atmosphere-canopy coupling strength during the CABINEX field campaign, Atmos. Chem. Phys., 11, 11921-11936, doi:10.5194/acp-11-11921-2011, 2011. Info, PDF

Other Awards and Accomplishments

  • I carried out upper-division undergraduate neuroscience research under the guidance of Dr. Todd Sigi Hale at UCLA. My thesis project was: " Beat-Induced Auditory Brainwave Entrainment"; this was an independently-proposed and independently-executed pilot EEG research study on beat-induced auditory brainwave entrainment, showing cognitive performance enhancement in pilot subjects. Poster presentations of this work were recognized with both the UCLA Dean's Prize and the award for " Outstanding Poster Presentation" as winner of the annual UCLA Neurosience Poster Session in May 2012.
  • I was a member of the UCLA Stroke Force organization for my last two years at UCLA. As part of this team, we gave numerous presentations concerning the details, signs and symptoms, and risk factors of stroke to retirement centers, nursing homes, and other such at-risk populations in the Los Angeles community. In addition, we were given the privilege of working in the UCLA Ronald Reagan Hospital Emergency Room, helping the doctors and nurses identify, assess, monitor, and treat individuals suffering from stroke and enroll qualified patients in national stroke-related clinical trials. We also attended Grand Rounds with the Ronald Reagan Stroke Team physicians, and frequently held in-group presentations regarding relevant stroke and neuroscience research. Overall, this time with UCLA Stroke Force was an absolutely incredible experience for which I count myself extremely fortunate.