Welcome to my LinkedIn profile! I am Stephen, a Master of Science in Computer Vision (MSCV) student at Carnegie Mellon University (CMU), School of Computer Science. I have previously interned and worked at Apple , Meta Reality Labs, and CMU Robotics Institute. My interests lie in AR/VR, computer vision, geometry, machine learning, and multimodel recommendation. I originally graduated from University College Dublin (UCD) in Ireland, earning a Bachelor’s in Software Engineering. During UCD, I took on a role as an ML/CV research intern in THEIA lab and collaborated with Nanyang Technological University (NTU), jointly supervised by Assoc Prof Yee Hui Lee and Dr. Soumyabrata Dev. My endeavors have culminated in 10+ works with 150+ citations published and delivered in esteemed AI conferences, journals, and workshops like CVPR, AAAI, CIKM, BMVC, IEEE, ACM, SCI, and Elsevier. In addition to my technical skills, my educational and professional journey across Ireland, China, Singapore, the United Kingdom, Canada, and the United States has enriched me with a profound cultural diversity. My unique multicultural background and diverse cultural experiences equip me to understand and adapt to global preferences and cultural nuances, fostering collaboration and innovation in multicultural teams.Seeking 25 New Grad work! Feel free to reach out to me at stephenw0516@gmail.com or heweiw@andrew.cmu.edu• GitHub: https://github.com/WangHewei16• Google Scholar: https://scholar.google.com/citations?user=zYma17IAAAAJ&hl
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Machine Learning EngineerAppleSeattle, Wa, Us -
Machine Learning Research Engineer (Vision Pro)Apple May 2024 - PresentSan Francisco Bay AreaWorking on AI/ML and 3D Vision algorithms in ARKit at Vision Products Group (VPG).
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Computer Vision Student Researcher (Meta Reality Labs)Meta Jan 2024 - May 2024Pittsburgh, Pennsylvania, United StatesI built an auto-calibration system and a Structure from Motion (SfM) pipeline to obtain intrinsics efficiently, utilized SuperPoint and Superglue as feature extractor and matcher, and then implemented a learning-based featuremetric refinement inspired by Pixel Perfect SfM to refine 2D keypoints position and 3D triangulated points to improve intrinsic accuracy compared with groundtruth in camera array's KRT. -
Research AssistantCarnegie Mellon University Robotics Institute Dec 2023 - May 2024Pittsburgh, Pennsylvania, United StatesI worked on computational imaging under the supervision of Assoc. Prof. Ioannis Gkioulekas, specifically focusing on creating imaging systems that generate feature descriptors and conduct feature matching, and also engaged in research related to physics-based rendering and differentiable rendering. -
Computer Vision Research InternUniversity College Dublin May 2021 - Jun 2023Belfield, Dublin 4, IrelandAs an undergraduate researcher at @THEIA lab supervised by Dr. Soumyabrata Dev, my research covers various AI-related topics and published 5+ papers. In computer vision, I have worked on salient object detection, stereo matching, 3D reconstruction, and video understanding. In machine learning, I have experience with medical stroke prediction, unsupervised generative models, and computationally efficient ML. As for autonomous driving, I investigated multi-modality and multi-task perception models.2 paper accepted by IEEE ROBIO'231 paper accepted by Elsevier Displays (SCI, IF=4.3)1 paper accepted by Elsevier Healthcare Analytics, with 50+ citations in half-year1 paper accepted by Elsevier Systems and Soft Computing1 paper accepted by Elsevier Entertainment Computing (SCI, IF=2.8)1 work accepted by CVPR'22 Image Matching Challenge (IMC) Workshop1 paper accepted by IEEE ICIP'21 -
Teaching AssistantUniversity College Dublin Sep 2021 - Jan 2023Belfield, Dublin 4, IrelandAs the Teaching Assistant (TA) for several CS modules at UCD (e.g., COMP3025J Augmented and Virtual Reality, COMP3023J Wireless Sensor Networks, COMP2006J Operating Systems), I delivered tutorials and sample exercises to reinforce in-class concepts, and mentored students about lecture contents. In addition, I guided 80+ students in discussion sections, tutored programming assignments, and graded quizzes.
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Research CollaboratorNanyang Technological University Singapore Sep 2022 - May 202350 Nanyang Avenue, SingaporeI conducted research at the intersection of computer vision, deep learning, and remote sensing with 5+ papers supervised under Assoc Prof Yee Hui Lee at @NTU Energy Research Institute. I proposed a real-time cloud segmentation model that balanced performance and computational complexity, in which I proposed the BSAM module as the decoder to create a segregated feature pair and used Efficientnet-b0 as the backbone to make the model real-time. Finally, the proposed model maintained performance as the SOTA with 70.68% less model size with beyond-real-time-benchmark speed of 299fps and 392fps for FP32 and FP16 respectively.1 paper accepted at IEEE IGARSS (Oral)1 paper accepted by IEEE AP-S/URSI1 paper delivered preprint on arXiv1 paper under review at IEEE TGRS1 paper under review at IEEE ICME -
Machine Learning Research Engineer InternChinese Academy Of Sciences Oct 2022 - Dec 2022Institute Of Automation, Chinese Academy Of Sciences (Casia)I developed an on-device real-time object detection module for autonomous driving perception system. As for model building, I integrated MobileNet-YOLOV5 and Faster RCNN, achieving a consensus of predictions. To optimize performance, I implemented k-means++ for calculating adaptive anchor sizes and enhanced the training data with mosaic augmentation. The simulation phase was conducted using CARLA. Furthermore, I utilized Neural Architecture Search to reduce the model size, enabling on-device deployment on NVIDIA Jetson AGX Xavier embedded system-on-module (SoM) for real-time object detection and pose estimation. -
Computer Vision Research Intern (Mitacs Globalink Research Internship)Mitacs Jul 2022 - Oct 2022Toronto, Ontario, CanadaI was responsible for developing a hybrid deep learning model for MRI image segmentation. I augmented the ABIDE dataset with over 7,8k images using Generative AI models based on Stable Diffusion and used Mip-NeRF for 3D reconstruction. I built a deep learning segmentation model by combining 3D U-Net and Vision Transformer (ViT), enhanced through Boosting ensemble. I also implemented Propensity Score Matching to evaluate time-dependent risk markers for Autism Spectrum Disorder, contributing to early diagnosis efforts. -
Machine Learning Engineer InternMelody Dreambit Feb 2022 - Jun 2022My task is to build an ML-based recommendation system for the website of instrument sales department to improve monthly revenue. I optimized and fine-tuned several language models like LSTM, Large Language Models (LLM), and BERT to extract/refine the user and product embedding, then combine them into our proposed recommendation deep learning network DeepMDR for personalized recommendation. -
Computer Vision Research CollaboratorAdapt Centre Mar 2021 - Jan 2022Dublin, County Dublin, Ireland1 paper accepted by IEEE ICIP as first-author1 paper accepted by IEEE ICIVC as first-author (Oral)Thanks to ADAPT SFI Research Centre for long-term support and sponsor for our research work at UCD :)
Stephen Wang Education Details
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Computer Vision -
Computer Vision -
3.98/4.0 (Scholaro Algorithm), First Class Honours, Cum Laude
Frequently Asked Questions about Stephen Wang
What company does Stephen Wang work for?
Stephen Wang works for Apple
What is Stephen Wang's role at the current company?
Stephen Wang's current role is Machine Learning Engineer.
What schools did Stephen Wang attend?
Stephen Wang attended Carnegie Mellon University, Carnegie Mellon University School Of Computer Science, University College Dublin.
Who are Stephen Wang's colleagues?
Stephen Wang's colleagues are Peter Trost, Luiz Alberto Arantes De Souza, Flor Canto, Erhan Tekes, Patrick Tang, Shruti Kalra, Jehad Mohamed.
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Stephen Wang
Greater Boston1signetjewelers.com2 +197893XXXXX
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Stephen Wang
Economics Student @ Nyu Stern/Cas Finance Student @ Harvard Extensional School Data Science Student@Yale Summer SessionNew York, Ny -
Stephen Wang
Brisbane, Ca -
2talentplus.com, gmail.com2 +140248XXXXX
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