Alex L.

Worked on: 1. Orion AR Glasses (https://about.fb.com/news/2024/09/introducing-orion-our-first-true-augmented-reality-glasses/ ) 2. Rayban Meta Glasses (https://www.meta.com/ai-glasses/ray-ban-meta/) 3. Meta Rayban Display Glasses (https://www.meta.com/ai-glasses/meta-ray-ban-display/)

Augment Reality @ Reality Labs Worked on several software experiences on Orion AR Glasses https://about.fb.com/news/2024/09/introducing-orion-our-first-true-augmented-reality-glasses/ -- spatial computing with C++, Javascript/Typescript, Kotlin, C# OpenXR, Android&iOS

OneDrive & SharePoint Backend Core Engineering -- C#, Java, Typescript

Transitioned to Torqata, an ATD internally incubated data analytics startup * Price recommendation, Machine Learning Engineering and Deployment * Junior data scientists mentoring & learning * Speaker at Industry Conferences

Data Scientist #2 at American Tire Distributors (ATD) Projects: - Team building/leadership activities (Hackathon, Lunch&Learns, Conference Speaking, etc) - Workforce forecasting and optimization - Inventory optimization - Pricing recommendation and optimization

Developed machine learning/AI empowered applications to improve business efficiency and explore new business possibilities. Projects: 1. Call Volume Forecasting 2. Anomaly Detection using Recurrent Neural Network 3. Chat Bot/Voice Rec Natural Language Processing 4. Internal Data Science Package Development 5. Customer LTV (Life Time Value) modeling 6. SEO (Search Engine Optimization) Forecasting and Content Generation

Worked on building MATIN, an E-collaboration platform for material science research community at Georgia Tech.

Specialized in Machine Learning. * Deep Learning projects: Convolutional Neural Network for image classification, video frame segmentation; Autoencoder for data compression and denoising. * Machine Learning projects: Literature review in HMM for speech recognition; Algorithm and Model implementation (Python) for random forests, decision trees, adaBoost; Clustering implementations (MATLAB) of K-Means, K-Medoids; HMM implementations with forward-backward algorithm, Baum-Welch Algorithm * Artificial Intelligence projects: MinMax algorithm for Chess Playing; Bi-directional, Tri-directional search; Planning and Scheduling; HMM for sign language recognition

Joined the B2B Development Team at Storefront Engineering of Wayfair as Full Stack Web Software Intern. Developed internal facing data extraction tools as well as external website modal applications.

Computer Lab assistant for introduction courses in Computer Science. Mainly focus on helping students in Object-Oriented Java/C++ programming.

Help physics students on physics problems/concepts.

Graded homework for two elementary physics courses, and one higher level physics course.

I started work as a Chinese Tutor at Center for Teaching and Learning in Lawrence University since September 2011.

Successfully constructed a Monte-Carlo Simulation on Self-Binding Polymers in C++. Algorithms used include: Markov Chain, Metropolis Hasting Algorithm. Investigated the scaling effect on polymer's radius of gyration. Simulated polymer interactions with three energy components: linking energy component, exclusion volume component, hydrogen bonding energy component.

Worked with Doctor John. R Brandenberger on Coherent Population Trapping in Rb87 atoms.

Assisting the Modern Physics Lab at Lawrence University.

I started working as a student assistant at President's Office of Lawrence University from Jan 2012. I am currently involved in a website promotion project, called www.myelectiondecision.org.

Researched under Nanobiophysics group and optical science group at the University of Twente. Working with Post Doc Jord Prangsma on plasmonic enhancement of chemiluminescence.

Participated the Symposium On Undergraduate Research, (hosted by Division of Laser Science of American Physics Society) and presented my summer research work on Coherent population trapping.

Graduate study specialization: Machine Learning Research Assistant in Material Science Engineering Department

Specialized in Machine Learning. * Deep Learning projects: Convolutional Neural Network for image classification, video frame segmentation; Autoencoder for data compression and denoising. * Machine Learning projects: Literature review in HMM for speech recognition; Algorithm and Model implementation (Python) for random forests, decision trees, adaBoost; Clustering implementations (MATLAB) of K-Means, K-Medoids; HMM implementations with forward-backward algorithm, Baum-Welch Algorithm * Artificial Intelligence projects: MinMax algorithm for Chess Playing; Bi-directional, Tri-directional search; Planning and Scheduling; HMM for sign language recognition

Double majored in Mathematics and Physics. Senior Projects: * Randomized Simulation on Self-Binding Polymers (C++) * Computational Topology Scientific Research: * Coherent Population Trapping of Rb87 Atoms using a Magneto Optical Trap (Lawrence University) * Optical Flourescence near Gold nano rods (University of Twente, NL)

Concentrated on Physics, Math, Economics