Help engineers level up by sharing programming concepts and techniques

• Train and quantize ResNet-50 and YOLOv7 models with ByteTrack for image classification, object detection and tracking • Build real-time video streaming system (1080p resolution at 30fps) integrating machine learning inference on Rockchip and Qualcomm SoC with hardware-accelerated codecs using GStreamer, multiprocessing, and pipelining in Python• Create Python binding for C++ Snapdragon kernel libraries, streamlining development cycle for on-chip machine learning systems, bringing down inference time by 25 times compared to pure Python implementation• Deliver tools for camera calibration, image orthogonalization, image stitching, distance, and depth estimations with OpenCV, speeding up internal image processing workflow by 55%

• Developed web domain credibility ranking models with graph neural networks adopting PyTorch and NetworkX, set up end-to-end ML pipeline, deployed models in production (making prediction for > 1 million domains) using FastAPI• Established data infrastructure (data warehouse, computation, orchestration) on Azure Cloud Services, enhancing data security, quality, and integrity, improving efficiency of data and software teams, and fastening ML life cycle by 40%• Increased efficiency of social media data scraping process by 30% through customization of open-source tools

• Analysed tradeoffs in learning algorithms for spiking fully connected and convolutional neural networks• Framed architecture and wrote assembly instructions for spiking neural network hardware accelerators on FPGA

Placed on the Honour List of Student Tutors for Excellence in Teaching with 4.8/5 feedback point (faculty average: 4.2)IT5003 Data Structures and Algorithms• Conducted classes of ~20 Master students, reviewed DSA concepts and implementation techniques• Showcase live coding in Python, provided consultations, graded, and gave feedback to weekly problem setsCS2102 Database System • Facilitated teaching and discussion of Relational Algebra, ER model, SQL, and Database Normalization techniques• Marked and gave feedback on database design and implementation project and weekly assignmentsCG2111A Engineering Principles and Practice II• Provided consultations during lab sessions and guidance for the final course project, graded lab reports• Related topics: bare-metal programming, communication protocols, Lidar, SLAM, power management

• Trained and deployed ML models for scooter parking image classification on AWS SageMaker achieving 95% accuracy and 0.98 precision score, detecting bad parking behaviours, enhancing user experience, and saving US$200,000 annually• Proposed and coded backend for an in-house annotation platform utilizing Django REST Framework and PostgreSQL, streamlining collaboration between ML and data annotation teams, leading to time savings of 5+ hours per week• Performed experiments with RK1808 neural processing unit (NPU) for on-chip surface detection task on scooters

• Collaborated with Physics teachers and Engineers to design, develop and test experimental Physics models used in national and international Physics Olympiads• Conducted coaching sessions for students participating in national Physics Olympiads