1. Lingqiu Jin (E.I.T.)
Personal Information
Email: lingqiujin@gmail.com Mobile: 814 - 321 - 3910
10045 Imperial Highway, Apt703, Downey, CA 90242
Education
Master of Science: Electrical Engineering
Columbia University in the City of New York Aug. 2015 - May 2016
Bachelor of Science: Electrical Engineering & Mathematics
The Pennsylvania State University Aug. 2012 - May 2015
Project Experience
Machine Learning: Authorship Attribution
• Used Naïve Bayes, kernel SVM, Ada Boosting, decision trees and logistic regression to test
paper authenticity
• Compared these algorithms by calculating the misclassification rates, probability of false
positive and false negative
• Verified the influence of different sample methods like bootstrapping and cross validation
Machine Learning: Image Recognition and Reconstruction
• Used Principal Component Analysis (PCA) with CroppedYale Data Set to train eigenfaces
• Reconstructed the faces with the eigenfaces and calculated the misclassification rates using K
nearest neighbor algorithm
• Applied to character recognition on vehicle licenses
MTA Transfer Alert System Based on Amazon Web Service
• Used AWS EC2 store MTA data to S3
• Compared time consumption among different routines with AWS Machine Learning
• Created message alert with AWS Lambda, triggered by Kinesis
Internet of Things: Smart Egg Tray
• Used sensors to monitor the usage and quality of eggs
• Uploaded information to cloud and performed data analysis upon user’s consumption pattern
• Created an IOS notification system and Amazon fresh subscription system
Robotics: Tendon-driven robot hand
• Designed and built a tendon-driven robot integrated with the Baxter arm
• Optimized the motion with Grasplt, able to complete specific grasping and simple
manipulation tasks
Entrepreneurship & Robotics: Michelangelo Robotics (co-founder)
• Participated in development of a path-following robotic endoscope
• Experienced in rapid prototyping through CAD design, Matlab simulation and 3D printing
Big Data: UberMax
• Used k-mean cluster to MapReduce the data from 2015 NYC taxi data
• Customized algorithms to recommend top five routines with most possible profits for Uber
drivers Softerware

2. Circuit Design: RF Front-End Direct Conversion Receiver
• Designed receiver for use in GSM-900M and GSM-1800M Systems
• Accomplished through the design of a front-end matching network, an LNA, and a Mixer used
to create an I/Q output
• Imploded DSP techniques to reproduce wirelessly transmitted data in given RF bands
Circuit Design: CMOS Broadband Transimpedance Amplifier
• Designed a CMOS Broadband Transimpedance Amplifier for use in SONET/SDH OC
48/STM-16 transceiver
• Optimized the amplifier design to meet the specifications of 2.1G Hz bandwidth and 70Db
transimpedance gain
• Modeled and simulated the circuit with Cadence and 0.18 um technology
Circuit Design: Power Converter with 24 W output (24V 1A)
• Designed and built a power convertor with fly-back control
• Modeled and simulated the circuit with Multisim and transferred it into PCB layouts with
Ultiboard
Embedded System: Ecocar 3, Year One (Third Prize)
• Applied DSRC (Dedicated Short Range Communications) as communication media to
customize our ADAS (Advanced Driver Assistance Systems) which helps driver to optimize
the vehicle speed and reduce fuel consumption.
• Used US06 driving cycle as test standard, modeled and simulated fuel consumption in Matlab
Software
• Programing: Python, R, java, C++, Arduino, Matlab
• CAD Design: Solidworks
• Circuit Design: Cadence, Multisim, Ultiboard
• Modeling and Simulation: Simulink, LabVIEW
• Big data analysis: Hadoop, Spark
• Machine learning: R