Zhengyan's Personnel Webpage

  Building a Superhuman Flappy Bird Agent with Double DQN GitHub: https://github.com/lambo131/flappy-bird-DQN_agent_RL Youtube video: https://youtu.be/QNoUa5ieCFE PROJECT OVERVIEW ---------------- This project explores Deep Reinforcement Learning by implementing a Double Deep Q-Network (DDQN) agent capable of mastering the Flappy Bird environment (FlappyBird-v0), as well as classic control tasks like CartPole, MountainCar, and LunarLander. The system is built with PyTorch and Gymnasium, featuring a modular design that separates the agent logic, network architecture, and hyperparameter configuration. 1. CORE ARCHITECTURE -------------------- - Algorithm: The agent utilizes Double DQN, an improvement over standard DQN that decouples action selection from target evaluation to reduce overestimation bias. - Neural Network: A flexible Multi-Layer Perceptron (MLP) serves as the function approximator.   * Input: 12-dimensional state vector (e.g., bird position, velocity, pipe distance...

  My Journey in Smartwatch Innovation: Building the Foundation for On-S kin Handwriting My Research Report: report My robust finger tracking algorithm: video Gesture extraction demo: video ===================================================================== Hey folks! As a student researcher, I dove into a cool project to fix one of the biggest annoyances with smartwatches: those tiny screens that make typing or gesturing a hassle. My work focused on turning the back of your hand into a touchpad by "listening" to the sounds your finger makes when sliding on your skin. This was my UROP project, and it laid the groundwork for a bigger research paper called "Swift," co-authored with my professor and team. Let me break it down simply! The Challenge and My Idea Smartwatches are awesome for notifications, but interacting with them? Not so much. Your finger blocks the screen (the "fat finger" problem), and voice input isn't always private or quiet. Inspired ...

  Revolutionizing Robot Manipulation: How Diffusion Models Unlock Seamless Bimanual Pick-and-Place in Cluttered Shelves A simulation demo: video A real world demo: demo Imagine a warehouse robot staring at a jumbled shelf: it needs to grab a box lying flat on the table, flip it upright, and slide it neatly onto a high shelf — all without knocking anything over or dropping the item. Today’s robots often fail here. Single-arm systems hit kinematic limits; traditional planners get stuck in endless trial-and-error loops. But what if two robot arms could elegantly hand the object between them, optimizing every grasp and every joint movement together in one smart loop? That's exactly what our Final Year Project team at HKUST has built. The Engineering Problem We're Solving In real-world pick-and-place tasks — warehousing, assembly lines, even smart homes — objects rarely line up perfectly for a single grasp-and-place motion. You need reorientation , which demands bimanual handovers ...

  My ASTRI Internship: Pioneering a Diffusion-Based Algorithm for 3D Stomach Reconstruction Arxiv Paper: https://arxiv.org/abs/2602.00739 Video demos:  - video 1 - video 2 ================================================================= Hey everyone, it's Zhengyan here. As some of you know, I spent my summer interning at the Hong Kong Applied Science and Technology Research Institute (ASTRI) in their Advanced Electronics Components and Systems department. It was an incredible experience that combined cutting-edge tech, medical applications, and a bit of physics-inspired creativity. Today, I want to share what I worked on—a project aimed at improving diagnostic accuracy for stomach diseases using a magnetic capsule endoscope. We even submitted a paper to CVPR 2026 based on the algorithm I developed! Let's dive in. The Problem: Scanning the Stomach with a Tiny Capsule The project revolved around a swallowable capsule that scans the stomach for diseases. My mentor, LiYuan Qiu—a ...

Biomimetic Robotic Fish: Dual-Servo Mechanism & Parametric Gait Control Youtube video: TBC Course: ISD 2200 Physical Prototyping (2026)[cite: 1, 2] Team: "Last Team" (Clément COVIAUX, Zhengyan Lambo QIN, SIT Lok Long)[cite: 2] Role: Lead Hardware & Software Engineer for Custom Prototype[cite: 1] Core Concept: Bio-inspired underwater robot driven by an ESP32 microcontroller, featuring a dual-servo actuation mechanism and real-time sinusoidal gait control[cite: 1, 2]. Technical Specifications at a Glance Feature Specification Top Swimming Speed ~40 cm/s (11.5 seconds per pool length)[cite: 1, 2] Microcontroller ESP32-based board with wireless Blynk telemetry[cite: 1, 2] Actuation System Dual-servo side-to-side sliding mechanism[cite: 1, 2] Waterproofing Double O-ring seal ...