About

Qiang Lu, also known as Max, is a Deep Learning Software Engineer at Intel Corporation with a passion for robotics and self-driving cars. He has 4.85 years of relevant experience in the field and is proficient in Python, C++, and C#. Max has a strong foundation in mathematics and is skilled in machine learning techniques such as SVM, random forest, Keras, and CNN. Max has worked for LG Electronics as a Senior Software Engineer where he implemented map importer and exporter in the simulator for ApolloOpenDRIVE, LaneLet2, and OpenDRIVE formats. He also created a docker image to convert Apollo Cyber bag to XVIZ glb files to visualize sensor data inside a browser. Max integrated the latest Baidu Apollo and Autoware AD stacks with LGSVL automotive simulator and contributed to them. Additionally, he calibrated an autonomous car's sensors including camera, GPS, and lidar to collect data to simulate inside the simulator. Max has also worked as a Research Assistant at the University of Denver where he developed intelligent intersection control algorithms for autonomous intersection traffic. He participated in several projects including an intersection control algorithm using Mixed-Integer Programming (MIP) to provide an optimal trajectory for each vehicle and addressing communication delay and loss. He also optimized vehicles' sequence to expedite emergency vehicle's crossing using a Genetic Algorithm. Moreover, Max contributed to the safe and efficient intersection management in autonomous traffic project. Max holds a Doctor of Philosophy (Ph.D.) in Electrical and Electronics Engineering from the University of Denver, an MS in Aerospace, Aeronautical and Astronautical Engineering from Beihang University, and a BS in Physics from Southwest University. He also completed a Self-Driving Car NanoDegree from Udacity. Max's tech stack includes deep learning, software engineering, Python, Docker, ML, SVM, random forest, Keras, CNN, and Scikit. He is a driven individual with a passion for innovation and a desire to improve the world through technology.