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Eric M. Fischer

Ph.D. Statistics with specialization in Artificial Intelligence

University of California Los Angeles

About Me

I’m a first-year Statistics Ph.D. student with a specialization in artificial intelligence, advised by Dr. Song-Chun Zhu at the Center for Vision, Cognition, Learning, and Autonomy (VCLA) at UCLA. My emphasis is in natural language processing and generative modeling. Many projects are on my Github page.

I obtained a Master of Science in Computer Science with a specialization in artificial intelligence and a Bachelor of Arts in Philosophy with an emphasis in philosophy of language, both from UCLA.

Before my Masters, I worked as a Full Stack Software Engineer in the San Francisco bay area for 3 years.

Education

  • Ph.D. Statistics, Present

    University of California, Los Angeles

  • M.S. Computer Science with Thesis, 2020

    University of California, Los Angeles

  • B.A. Philosophy, 2013

    University of California, Los Angeles

Publications

Deep Generative Classifier with Short Run Inference

Deep generative classifier employs Short Run Markov Chain Monte Carlo inference with Langevin dynamics and backpropagation through time
Full Paper

Learning Multi-Layer Latent Variable Model with Short Run MCMC Inference Dynamics

Short Run MCMC sampling is utilized in a deep generative model with multiple layers of latent variables
Full Paper

Research

Topology Adaptive Snakes Improve Mask Generation for Image Inpainting

T-snake deformable models, which can segment complex-shaped structures, improve generated masks passed to a GAN for image inpainting
Github Code

Exact Sampling with Coupled Markov Chains and Swendsen-Wang Cluster Sampling of the Ising Model

Convergence analysis of exact sampling with Gibbs sampler and coupled Markov chains vs. cluster sampling with Swendsen-Wang algorithm
Full Paper Github Code

Implementation and Convergence Analysis of First-Order Optimization Methods for a CNN

Convergence analysis and Python implementations of SGD, SGD with momentum, SGD with Nesterov momentum, RMSprop, and Adam optimizers
Full Paper Github Code

Formulation of Variational Lower Bound and Application of VAE to MNIST Dataset

Formulation of the evidence lower bound (ELBO) for the variational autoencoder and an application to synthesizing binary images
Full Paper Github Code

Projects

Trigger Word Detection

Speech recognition algorithm for trigger word detection, the technology behind Alexa, Google Home, and Siri

Neural Style Transfer using Convolutional Neural Networks

Neural style transfer generates images that reflect the content of one image but the artistic “style” of another

Importance Sampling and Effective Number of Samples

Estimating the number of self-avoiding walks with importance sampling and effective sample size

Network Visualization with Saliency Maps, Fooling Images, and Class Visualization

Explores three techniques that use image gradients to generate new images

Facial Trait and Political Election Analysis by SVM

Trained SVM classifiers to infer 14 facial traits from low-level image features and use that information to make election predictions

Face Detection using AdaBoosting and RealBoosting

Used AdaBoosting, RealBoosting, Haar Filters, Non-Maximum Suppression, and hard negative mining for the task of face detection

PCA, Autoencoder, and FLD for Facial Analysis

Compares Principle Component Analysis, an Autoencoder, and Fisher Linear Discriminants for the task of analyzing human faces

Car Detection for Autonomous Driving

Achieving high-accuracy in real-time, YOLO algorithm is applied to car detection for autonomous vehicles

Experience

 
 
 
 
 

Graduate Student Researcher

Center for Vision, Cognition, Learning, and Autonomy

Mar 2019 – Present University of California, Los Angeles
Contribute to several NLP and generative modeling research projects with PhD students and other engineers
 
 
 
 
 

Full Stack Software Engineer

NatureBox

Mar 2016 – Jan 2018 Redwood City, CA
Main architect of new Flux/React web application after company added direct-to-consumer business; Led the following projects: Stripe payment processor migration, Login and Pay with Amazon, API v2
 
 
 
 
 

Software Engineer

Cinemagram

Sep 2015 – Feb 2016 San Francisco, CA
Worked with JavaScript, Ruby, SQL, and Redis to construct internal data management tools
 
 
 
 
 

SAT, ACT, and GRE Test Instructor

Veritas Prep

Jan 2011 – Feb 2016 Malibu, CA
Have tutored hundreds of students privately and in classes for the SAT, ACT, GRE, and other subjects

Keywords

AdaBoosting Adversarial Robustness Autoencoder Autonomous Driving Backpropagation through Time Boosting Cluster Sampling CNN Computer Vision Deformable Model Effective Sample Size Energy Based Model Exact Sampling Generative Modeling Langevin Dynamics Markov Chain Monte Carlo Monte Carlo Optimization Pattern Recognition Sampling Variational Autoencoder

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