Information
Jifu Zhao (Click to download my resume)
Education
- Ph.D. Candidate in Nuclear Engineering, GPA: 3.91/4.00
University of Illinois at Urbana-Champaign, May 2019 (expected) - Master of Science in Applied Statistics, GPA: 3.91/4.00
University of Illinois at Urbana-Champaign, May 2018 - Master of Science in Nuclear Engineering, GPA: 3.87/4.00
University of Illinois at Urbana-Champaign, August 2016 - Bachelor of Science in Nuclear Engineering and Technology, GPA: 3.93/4.30
University of Science and Technology of China (USTC), June 2014
Skills
- Programming:
Python (proficient), Java, R, TensorFlow, Keras, Scala, MATLAB, C, SQL, Fortran - Platform:
Hadoop, Spark, Linux/UNIX, Amazon Web Service - Data Science:
Numpy, Pandas, Scikit-learn, Matplotlib, Seaborn, Plotly, H2O, CatBoost, LightGBM, XGBoost - Machine Learning:
Predictive Modeling, Anomaly Detection, Computer Vision, Recommender Systems
Internship
Artificial Intelligence Intern, Synchrony Financial (GPShopper), Summer 2018
- Designed and built a complete data pipeline for data query, cleaning and transformation
- Conducted comprehensive feature engineering and visualization over millions of financial data
- Built predictive models with Logistic Regression, Random Forest and Boosting for loan status prediction
- Developed face detection and verification systems with OpenCV, Keras and TensorFlow
Research
- Ph.D. Thesis: Implementation and Simulation of Mobile Sensor Networks for Nuclear Radiation Detection
- Led a team of five to develop the mobile sensor network simulation platform and conduct experiments
- Applied machine learning techniques (PCA, Autoencoder, KNN, SVM, Isolation Forest) to anomaly detection
- Developed algorithms with KDE, MLE and Kriging techniques for automated radioactive source localization
- Implemented Convolutional Neural Networks with Keras/TensorFlow for automated isotope identification
Projects
- Face Detection and Verification via OpenCV and Deep Learning
- Large Scale Landmark Recognition via Deep Learning
- Object Recognition in Images
- Lending Club Loan Status Prediction
- Chicago Divvy Bicycle Sharing Data Analysis and Modeling
- Hadoop Implementation of Movie Recommender System
- Hadoop Implementation of Page-Rank Algorithm
- Hadoop Implementation of Words Autocompletion
- Kaggle: Predicting Red Hat Business Value
- Comparison of Unsupervised Pre-training Methods for Digits Classification
- Course Projects
- CS 446: Machine Learning for Human Gender and Facial Expression Classification
- CS 598: Android Smartwatch Activation System Design and Development
- NPRE 498: Nuclear Radiation Detector Design based on Raspberry Pi
Selected Courses
- Computer Science, Machine Learning, and Data Science
- INFO 490: Introduction to Data Science
- INFO 490: Advanced Data Science
- CS 446: Machine Learning
- CS 598: Machine Learning for Signal Processing
- ECE 544: Pattern Recognition
- STAT 542: Statistical Learning
- STAT 578: Statistical Learning in Data Science
- IE 529: Statistics of Big Data and Clustering
- Statistics
- STAT 400: Statistics and Probability I
- STAT 410: Statistics and Probability II
- STAT 425: Applied Regression and Design
- STAT 429: Time Series Analysis
- ECE 534: Random Processes
- IE 410: Stochastic Processes and Their Applications
- NPRE 498: Probabilistic Risk Assessment
- NPRE 598: Advanced Risk Analysis
- Online Courses
- deeplearning.ai: Deep Learning Specialization
- Stanford University: Machine Learning
- Stanford University: Algorithms: Design and Analysis, Part 1 and Part 2
- Stanford University: Statistical Learning
- IBM: IBM Blockchain Founcation for Developers
- Princeton University: Algorithms, Part 1
- University of Toronto: Neural Networks for Machine Learning
- University of Washington:
Machine Learning:
Foundations, Regression, Classification, Clustering & Retrieval - Swiss Federal Institute of Technology in Lausanne: Functional Programming Principles in Scala
For more details, please refer to my resume.