Dezhi “Andy” Fang
(802) 294-3264 · dezhifang@gatech.edu · Atlanta, GA
Full CV available at: https://andyfang.me · Software Engineer
Georgia Institute of Technology
Major in Computer Science. Information Network & Intelligence Threads, GPA: 3.7/4.0
Software Development Engineer Intern
Airterns'17
Undergraduate Research Assistant
Research in data mining with professor Polo Chau.
- One of the investigators in NIH's MD2K (Mobile Data to Knowledge) initiative. Developing a predictive visualization dashboard.
- MMap: Scaling up scientific computation with memory mapping
- ARGO: Billion-scale visualization of network data
STAR Intern on Software Engineering
Utilizing data mining (with Hadoop and Python) to improve malware detection efficacy.
- Inferring unknown files' reputations with parent file and execution environment features.
- Deployed new rule in Symantec's AV Engine with a false positive rate of only 0.2%. Used in Norton Security and Symantec Endpoint Protection.
- Implemented a decision tree executor for detecting malware using file features that replaced Symantec's existing implementation.
Technical Lead
Technical lead in an online education startup.
- Lead developer of a CMS for online education.
- Built email marketing system sending 100k+ emails per month.
- Maintained and updated internal infrastructure across multiple applications and distributed services including celery and memcached.
Software Engineer
Full-stack software engineer
- Sole developer of claryfy.com, a web forum for international students built with Django and PostgreSQL
- Built front-end of InitialView's Interview Booking System
- Built front-end of InitialView Interview Player
Carina: Interactive Million-Node Graph Visualization using Web Browser Technologies [ arXiv ] [ PDF ]
The 2017 World Wide Web conference (WWW’17)
[Presenter] M-Flash: Fast Billion-scale Graph Computation Using a Bimodal Block Processing Model [ Slides ] [ arXiv ] [ PDF ]
Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD’16)
Visual Exploration of Machine Learning Results using Data Cube Analysis [ ACM ] [ PDF ]
Proceedings of the Workshop on Human-In-the-Loop Data Analytics (HILDA’16) (Co-located with SIGMOD/PODS’16)
M3: Scaling Up Machine Learning via Memory Mapping [ arXiv ] [ PDF ]
Proceedings of the 2016 International Conference on Management of Data (SIGMOD/PODS’16)
Material, Supplies and Technology Grants (MS&T)
Georgia Institute of Technology
Supported by MS&T grants for resesarch in Visualization and Virtual Reality during Summer 2017. $1,000.
President's Undergraduate Research Award (PURA)
Georgia Institute of Technology
The Undergraduate Research Opportunities Program competitively funds individual requests by a student to support undergraduate student involvement in faculty research. Dezhi “Andy” Fang received:
- PURA Travel Award funding to present at 2016 ACM SIGMOD/PODS @ San Francisco, USA. $500;
- PURA Salary Award (PURA) for faculty research in Fall 2016, $1,500.
Undergraduate Research Poster Competition Finalist
ACM Special Interest Group on Management of Data (SIGMOD 2016)
Presented M3: Scaling Up Machine Learning via Memory Mapping . Awarded to ~10 recipients globally each year.
Georgia Tech Online Masters Program Scholarship
Georgia Tech College Of Computing
A full scholarship of the Georgia Tech Online Masters Program (worth $7000) was awarded.
Third Prize, China Adolescents Science & Technology Innovation Contest
China Association for Science and Technology
Presented a stereo in-door location system using computer vision.
First Prize, National Olympiad in Informatics in Provinces
China Computer Federation (CCF)
Programming competition in a form similar to ACM-ICPC.
China Economy Draws More Students Back From Abroad [ article ]
The Wall Street Journal
‘The U.S. is still the greatest place for doing cutting-edge research.’ —Dezhi Fang, a junior at the Georgia Institute of Technology
Companies Cash In On Us Universities' Video Interview Requirements [ article ]
China Daily
Runner Up, Emory GCC Case Competition
Emory Global China Connection
Case competition focused on mobile payment industry. Developed strategy for a U.S. based company to enter China's market with NFC payment technology.
Runner Up, BizTech'16 Case Competition
Georgia Tech Management Information Systems (MIS) Club
Case competition focused on Electronic Health Record (EHR) industry. Developed strategy for an established EHR company to transform its infrastructure to cloud-based solutions with high interoperability among EHR standards and medical devices.
Runner Up in Education Track, HackDuke'15
HackDuke
Developed ResumeWorks, a platform for creating different versions of resumes to fit each job application.
Hacker's Choice Award, VandyHacks'15
VandyHacks
Developed Bank Guard, an app for detecting credit card frauds.
4th Place, IronCoder'15
Cardlytics
A semiannually held programming competition by Cardlytics.
First Place, Georgia Tech College of Computing Alumni Hackathon'15
Georgia Tech College Of Computing
Developed MapsOnPoint, an app for finding points of interest along your road trip route without taking an unreasonable detour.
django-asyncmailer
- An async email sending solution with load balancing and routing among multiple SMTP credentials
- Now sending 100k+ emails per month with a delivery rate of more than 98%
ResumeWorks
- 2nd Best Hack of Education in HackDuke
- A tool for creating different versions of resumes to fit each job application
- User can choose a subset of their experiences to match with the company's interest
Maps OnPoint
- First Place in Hackathon @ Georgia Tech College of Computing
- Web app for planning trip navigation with a quick stop for food at any point along the route
Web Development : Django, HTML / CSS, JavaScript, NodeJS, Webpack, Gulp, React, Flux, Three.js, D3.js
Infrastructure : Memcached, Redis, Nginx, WSGI, RabbitMQ, Linux, Supervisor, Vagrant, Docker, Amazon AWS
Programming Languages : C / C++, Python, JavaScript, Java
Data Mining : Python, OpenCV, Jupyter Notebook, SciPy, Hadoop, Spark, Hive, Pandas, NumPy, Scikit-learn