Jullian Arta Yapeter
+1(647)241-0989 jullianyap[email protected] /in/jullianyapeter/ github.com/jullian-yapeter jullianyapeter.com
Languages Python, C++, C, C#, Java, MATLAB
Tools OpenCV, PyTorch, TensorFlow, Jupyter, ROS, Docker, GCP, AWS (Lambda, EC2, S3), MongoDB
Hardware Raspberry Pi, NVIDIA Jetson, STM32, Arduino, Altera FPGA
University of Southern California August ’20 - June ’23
M.S., Computer Science (Scientists & Engineers)
University of Waterloo September ’15 - June ’20
B.ASc., Honours Mechatronics Engineering/ Artificial Intelligence Option GPA: 88.87/100
Dean’s Honours List (3x ranked top 10 in class), NSERC Research Award Recipient, President’s Scholarship
Courses: Computational Vision, Autonomous Vehicles, Machine Intelligence, Capstone: devpost.com/software/lilypod
Singapore University of Technology and Design January ’19 - April ’19
Exchange term, Engineering Product Development GPA: 4.83/5.0
Researched image-based segregation of blood cells for novel diagnostics under Prof. Rajesh Chandramohandas.
Deeplearning.ai Online Deep Learning 5-Course Specialization September ’19
Walt Disney Imagineering May ’19 - August ’19
R&D Lab Associate Intern - Computer Vision and Perception Team Glendale, CA
· Created new functionality for Disney’s computer vision pipeline using Python, C++, ROS, and Docker, to improve
its capacity to handle human-object interactions and more efficiently operate various actuators via DMX and OSC
· Invented a novel deep learning application in Keras to improve the transient performance of interactive attractions
IBM September ’18 - December ’18
AI & IoT Developer Intern Toronto, ON
· Prototyped a Dynamixel-based 4DoF robotic arm capable of picking up targets using inverse kinematics, as
recognized via a hybridization of Faster R-CNN (Caffe) and KCF Trackers, on NVIDIA’s Jetson TX2 and OpenCM
· Built a system of smart garbage bins using embedded hardware, MQTT, and Watson’s IoT & ML cloud platforms
Zero Gravity Labs May ’18 - August ’18
Innovation Developer Intern Toronto, ON
· Developed applications to improve the shopping experience; a nutritional app that performs object recognition on
grocery items, and an in-store AR game for collecting loyalty points using AWS, GCP, OpenCV, and Unity
· Implemented and performed benchmarking on Neural Arithmetic Logic Units (NALUs) and conditional generative
adversarial networks (CGANs) in PyTorch to research its potential use in the customer loyalty industry
General Motors 2908 Innovation Lab September ’17 - December ’17
Innovation Specialist Intern Kitchener, ON
· Conducted iterative prototyping and field research to establish product-market fit for advanced technology projects
· Created and facilitated Design Thinking workshops to generate innovative solutions for various GM teams
A.U.G. Signals January ’17 - April ’17
Image Processing Software Engineering Intern Toronto, ON
· Implemented an image processing pipeline in MATLAB and Python to analyze satellite imagery (channel-realignment,
spectral analysis, resolution standardization, and georeference-based transformations) for use in precision farming;
resulted in more accurate data and an improvement in processing time by 300% as compared to the legacy pipeline