Dylan Ler

Dylan Ler is an accomplished data scientist and machine learning engineer with a strong background in AI and deep learning. With extensive experience in developing innovative solutions, Dylan has a proven track record of driving impact in various industries. Passionate about technology, Dylan actively contributes to hackathons and engages in continuous learning.

DYLAN LER

EDUCATION

Georgia Tech

Masters in Computer Science - Concentration in Machine Learning (Remote Online/Part Time - Ongoing)

Machine/Deep Learning: TensorFlow, PyTorch, BERT, NLTK, Pandas, Jupyter, Scikit-learn, OpenCV, AWS, Sagemaker, GCP, Docker, Langchain

William Jessup University Class of 2021

Masters in Computer Science - Concentration in Technology Management

Technical skills: Python, C++, Java, SQL, Git, Matlab, Android Development, Flask, Gradio, Tableau, Matplotlib, Seaborn

University of California, Los Angeles Class of 2016 BSc. Electrical Engineering

Computer Vision, Computational Photography, Speech Recognition, and System Processing

PROFESSIONAL EXPERIENCE

WebMD () - Internet Brands Inc. Los Angeles, California

Senior Data Scientist & Machine Learning Engineer November 2016 - Present

Built a recommendation system for medical forums under WebMD using BERT embeddings and an LSI topic modeling model to increase user engagement and retention.

Developed, tested, & installed an AI tool that understands medical articles semantically, extracts important keywords from articles using PositionRank, and automatically hyperlinks keywords to internal medical articles.

Used NLP techniques and K-means clustering to successfully train and deploy a model that classifies text messages to aid physicians & doctors with patient appointments.

Built a churn prediction model using XGBoost with 98% accuracy to predict when a customer will cancel their subscription to in-house WebMD patient management software.

Built an AI chatbot that can answer questions in natural language about medical information from WebMD’s internal database using Langchain and Gradio.

Built a recommendation engine to recommend email newsletter to WebMD’s email newsletter which retained a more than 90% open rate using deep learning.

Created data visualization dashboards using Tableau to display visitor data on webmd in order to make analytical decisions to optimize the user experience as well as SEO purposes.

Participated in an internal company hackathon to create an AI music therapy tool that auto-generates relaxing music in any desired genre like lo-fi, classical, and hip-hop using an LSTM network.

Skills used: TensorFlow, PyTorch, NLTK, Pandas, Scikit-learn, BERT, Huggingface, Spark, Hadoop, Langchain

Udacity () Los Angeles, California

Mentor & student for AI Engineer Nanodegree Program March 2017- June 2018

Guided 50 students in topics of Deep Learning, Computer Vision, and C++ to build software for a cancer detection project.

Reviewed student code projects in Edge Detection, Image Classifiers, Data Augmentation, and Feature Engineering

Skills used: Python, C++, Git

INVENTIONS & PROJECTS

Aki Story NFT Project () Global

Software | Blockchain Developer April 2022-Ongoing

Developed smart contracts and a front-end website for an NFT project that created and fully distributed 5,555 NFTs with user utilities such as a virtual metaverse, educational material, and add-on NFTs on the Ethereum blockchain.

Skills used: Solidity, HTML, CSS, Javascript, Java, Python, Web3.js

UCLA Wireless Health Institute & IEEE Los Angeles, California

Software | Electrical Engineer September 2013-June 2015

Designed and built PRIME—an Android application that combines sensor tracking with medication & survey prompting to aid physicians and patients in progressing through the recovery phase.

Won competition creating gesture-based sign language communication devices using Myo band & Arduino (C++).

HIGHLIGHTS

Mentor for hackathons (software programming competitions): - Cal Hacks (UC Berkeley) & HackingEdu (San Mateo)

Author of a personal finance and investment blog to help people manage and practice healthy financial habits.

Hobbies: hiking, implementing deep learning models from research papers, and managing online communities.

Masters in Computer Science - Concentration in Machine Learning (Remote Online/Part Time - Ongoing)

• Machine/Deep Learning: TensorFlow, PyTorch, BERT, NLTK, Pandas, Jupyter, Scikit-learn, OpenCV, AWS, Sagemaker, GCP, Docker, Langchain

William Jessup University Class of 2021

Masters in Computer Science - Concentration in Technology Management 

• Technical skills: Python, C++, Java, SQL, Git, Matlab, Android Development, Flask, Gradio, Tableau, Matplotlib, Seaborn

University of California, Los Angeles Class of 2016 BSc. Electrical Engineering

• Computer Vision, Computational Photography, Speech Recognition, and System Processing