Xin Gao

I'm an Applied Scientist at Amazon.

Currently I am teaching more than 10 different courses in Amazon, including Reinforcement Learning, Natural Language Processing, Computer Vision, Deep Learning, Time Series Forecasting, Graph Machine Learning, Decision Tree & Ensemble Methods, AutoGluon for MultiModal Data, Machine Learning for Tabular Data and Maths for Machine Learning etc.

Before I joined Amazon, I was a Machine Learning Engineer in Human Machine Intelligence Department at SAIC Innovation Center, helping build the AI system for autonomous vehicles.

I received a Ph.D. in Computer Science from New Jersey Institute of Technology in 2018, working under the supervision of Prof. Zhi Wei . Prior to my Ph.D., I received a B.E. in Computer Engineering and a LL.B. in Civil Law both from Nankai University in 2012.

I am broadly interested in deep learning, natural language processing, bioinformatics and intelligent transportation.

Contact: xg54 AT njit DOT edu

Recent publications

Google Scholar

Journal Papers

tRNA-DL: A deep learning approach to improve tRNA prediction results
Xin Gao, Zhi Wei and Hakon Hakonarson
Human Heredity, 2018, 83(3), pp.163-172.
DeepPolyA: a convolutional neural network approach for polyadenylation site prediction
Xin Gao, Jie Zhang, Zhi Wei and Hakon Hakonarson
IEEE Access, 2018, 6, pp.24340-24349.
Scheduling Survivability-Heterogeneous Sensor Networks for Critical Location Surveillance
Jie Tian, Tan Yan, Xin Gao, and Guiling Wang
ACM Transactions on Sensor Networks (TOSN'15), Vol. 11, No. 4, pp. 56:1-56:23, November 2015.
2D K-barrier Duty-Cycle Scheduling for Intruder Detection in Wireless Sensor Networks
Jie Tian, Wensheng Zhang, Guiling Wang and Xin Gao
Elsevier Computer Communications (COMCOM'14), Vol. 43, pp. 31-42, 2014.

Conference Papers

Predicting Animal Shelter Pet Adoption Times and Feature Importance Analysis using CatBoost
Cem Sazara, Xin Gao
In Proceedings of 11th IEEE International Conference on Intelligent Systems (IS’22), Warsaw, Poland, October 12-14, 2022.
Deep Learning for Sequence Pattern Recognition
Xin Gao, Jie Zhang and Zhi Wei
In Proceedings of 15th IEEE International Conference on Networking, Sensing and Control (ICNSC'18), Zhuhai, China, March 27-29, 2018.
ARPP: An Augmented Reality 3D Ping-Pong Game System on Android Mobile Platform
Xin Gao, Jie Tian, Xiaoyuan Liang and Guiling Wang
In Proceedings of The 23rd International Conference on Wireless and Optical Communication Conference (WOCC'14), Newark, New Jersey, USA, May 9-10, 2014.
User Behavior based Automatical Navigation System on Android Platform
Jie Tian, Guiling Wang, Xin Gao, Kaixuan Shi
In Proceedings of The 23rd International Conference on Wireless and Optical Communication Conference (WOCC'14), Newark, New Jersey, USA, May 9-10, 2014.

Workshop, Poster and Miscellaneous

Detection of Transportation Mode based on Smartphones for Reducing Distracted Driving
Xin Gao, Jie Tian, Guiling Wang
In Proceedings of the 20th annual international conference on Mobile computing and networking (MobiCom'14), Maui, Hawaii, USA, September 7 - 11, 2014.
Development and Evaluation of Smart Bus System
Joyoung Lee, Liuhui Zhao, Steven I-Jy Chien, Guiling Wang, Xin Gao
In Proceedings of University Transportation Research Center, 2016.

Patents and Invention Disclosures

Method, Apparatus and Computer Program Product for Comprehensive Management of Signal Phase and Timing of Traffic Lights
Jingwei Xu, Bruce Bernhardt, Arnold Sheynman, Xin Gao
U.S. Patent 10,127,811 (grant)
Method, Apparatus and Computer Program Product for Estimation of Road Traffic Condition Using Traffic Signal Data
Jingwei Xu, Xin Gao, Weimin Huang, Bruce Bernhardt
U.S. Patent 10,181,263 (grant)

Industrial Experience

Machine Learning Engineer, SAIC Innovation Center Human Machine Intelligence Research Team, San Jose, CA, Nov 2018 – Feb 2020.
Designed a deep learning model for autonomous vehicle for detecting driver sleepiness based on sensor data from steering wheel and video cameras. For dataset annotation used EEG and ECG data.
Designed a deep learning model for intelligent vehicle AC control system.
Designed a deep learning model for music speech classification and volume prediction.
Machine Learning Engineer Intern, NIO Machine Learning Team @ Digital Cockpit Department, San Jose, CA, Jun – Aug 2017.
FaceID System: Built a C++ version real-time deep learning system FaceID to recognize the driver and passengers for Self-Driving Car Project. Obtained a high precision 96.65% and a high frame rate 23fps.
Methods involved: Facenet, MTCNN, libSVM, etc.
Tools and platforms involved: Docker, Git, Nvidia, Cuda, Cudnn, Opencv, Qt, Tensorflow, Python.
Data Science Intern, HERE North America Traffic & Dynamic Content Research Group , Chicago, IL, Jun – Sep 2016.
Developed methods and algorithms to predict traffic congestion condition of the intersections.
Two related patents/invention disclosures have been filed.
Applied statistical analysis and quality analysis on SPAT data using Tableau & R.
Implemented SPaT Distributed Computing Platform using Kafka and AWS EC2.
Research Intern, Futurewei Shannon Research Lab, Bridgewater, NJ, Jun – Aug 2014.
Research topic: Software Defined Network (SDN).
Designed methods for virtual network embedding in SDN in C++ and R for Shannon Research Lab.

Research Experience @ NJIT

Research on Natural Language Processing based on Topic Modeling, Fall 2017.
Research on Smartbus Project, Summer 2015 -- Spring 2016.

Teaching Experience @ NJIT

Lab Instructor, CS 115 - Introduction to Computer Science I with C++, Spring, 2017.
Lab Instructor, CS 115 - Introduction to Computer Science I with C++, Fall, 2016.
Teaching Assistant, CS 610 - Data Structures and Algorithms, Summer, 2015.
Lab Instrutor, CS 115 - Introduction to Computer Science I with C++, Spring, 2015.
Instructor, CS 100 - Roadmap to computing with Python, Fall, 2014.
Lab Instructor, CS 101 - Computer Programming and Problem Solving with Matlab, Spring, 2014.
Teaching Assistant, CS 341 - Automata Theory and Complexity Theory, Fall, 2013.
Teaching Assistant, CS 659 - Image Processing and Analysis, Fall, 2013.
Teaching Assistant, CS 661 - System Simulation, Spring, 2013.
Teaching Assistant, CS 341 - Automata Theory and Complexity Theory, Spring, 2013.
Teaching Assistant, CS 656 - Internet and Higher Layer Protocols, Fall 2012.
Teaching Assistant, CS 506 - Foundations of Computer Science, Fall 2012.
Teaching Assistant, CS 332 - Operating Systems, Fall 2012.

Awards and Honors

Awards

Best Conference Paper Finalist Award, 15th IEEE International Conference on Networking, Sensing and Control, 2018
First Place Data Networking Poster Award, IEEE North Jersey Advanced Communications Symposium, 2014
Certificate of Merit for Microsoft International Women’s Hackathon, The Murray Center for Women in Technology at NJIT, 2014

Travel Awards

NSF Student Travel Grant for ACM MobiHoc 2015
NSF Student Travel Grant for ACM MobiCom 2014
NSF Student Travel Grant for CRA-W Grad Cohort Workshop 2015, 2016 & 2017

Professional Service

Journal Reviewer

IEEE Access
IEEE Transactions on Computational Social Systems
Journal of Experimental & Theoretical Artificial Intelligence
ACM Computing Reviews
IEEE Systems Journal
Ad Hoc & Sensor Wireless Networks
IEEE Internet of Things Journal
Computational and Structural Biotechnology Journal
WIRES Data Mining and Knowledge Discovery
Computer Networks
BMC Genomics
Computers in Biology and Medicine
PLOS ONE
Hindawi International Journal of Distributed Sensor Networks

Conference Reviewer

CITEI 2020 (Conference on Internet of Things and Embedded Intelligence)
IEEE MASS 2020 (IEEE International Conference on Mobile Ad-Hoc and Smart Systems)
ICNC’19 SCSD (2019 International Conference on Computing, Networking and Communications)
IEEE INFOCOM 2016 (IEEE International Conference on Computer Communications, top conference in networking area)
ICSPCT 2014 (International Conference on Signal Propagation and Computer Technology)