Hi! I am a Research Engineer at Samsung Research America (SRA), Digital Media Solutions Lab, where I apply my extensive knowledge and skills in advanced Computer Vision projects. Prior to joining SRA, I completed my Master of Science in Computer Vision (MSCV) at Carnegie Mellon University (CMU). My time at CMU was marked by a deep dive into Computer Vision and Machine Learning. My experience also includes a summer internship as a research scientist at Flawless AI. There, I conducted a research project focused on multi-dataset semantic segmentation, which further enhanced my expertise in Computer Vision.
I obtained my HBSc from the University of Toronto, where I received an interdisciplinary education in the Computer Science and Neuroscience programs. During my undergraduate years, I had the opportunity to be a research student at Vector Institute, under the guidance of Prof. Animesh Garg and Prof. Igor Gilitschenski, focusing on ‘Language-Guided Cognitive Planning with Video Prediction.’ I also had a one-year internship at Huawei Ottawa R&D Center as a Research Engineer, working on Machine Learning applications on wireless communication.
My interests span 3D Vision, Continual Learning, multimodal foundation models, and Cognitive Neuroscience.
Master of Science in Computer Vision
Carnegie Mellon University
Honors Bachelor of Science, 2022
University of Toronto
Flawless AI
May 2023 - Aug 2023 | Los Angeles
Researched on multi-dataset fine-grained semantic segmentation.
Huawei Technologies Canada Co. Ltd.
Ottawa Research & Development Centre
May 2020 - May 2021 | Ottawa, CA
Independently completed 3 research projects that explored the development of wireless communication from 5G to 6G by applying Machine Learning techniques.
Python, Java, C, C++, R, Verilog, x86-64 Assembly, TensorFlow, PyTorch;
Android Studio, OS, Linux, OpenCV, Isaac Sim, OpenAI Gym
Chinese (native), English (proficient), Portuguese (elementary)
Biology, Genetics, Physiology, Cognitive Psychology, Neuroscience;
Linear Algebra, Multivariable Calculus, Probability Theory and Statistics