Alan Tseng

Contact

Hello! Thank you for reaching out. If you would like to contact me, please send an email to alan.tseng.cs@gmail.com.

Summary

Highly motivated and experienced software engineer with a strong track record of success in developing innovative solutions. Expertise in blockchain, artificial intelligence, web development, cloud-native applications, and computer vision. Passionate about learning new technologies and collaborating effectively to deliver impactful results.

Experience

  • LINE Corporation
  • Software Engineer Intern Taipei City, Taiwan, Jul 2022 – Nov 2022
    • Blockchain, Kubernetes, Cloud-Native Applications, CI/CD, web3, NFT, TypeScript, React, Python, Nx, NextJS
    • Developed a tool service that streamlines API development by 20% time by automating type definition and backend API integration with Swagger, ensuring a single source of truth. Seamlessly integrated the tool into the project and deployed it on Kubernetes, configuring DNS and load balancing for optimal performance.
    • Leveraged Nx to develop a scalable frontend architecture within a monorepo structure, and collaboration with the Korean backend team.
    • Participated in an Internal hackathon and led a team with 5 members to develop a merchant management system that uses NFT to empower the business and develop with NextJS and Spring Boot.
    • Presented a talk about Ethereum and Decentralized Application Development within an internal study group. slide
    • DOSI Store my contribution
  • National Taiwan University - Image and Vision Lab
  • Research Assistant Taipei City, Taiwan, Jul 2021 – Aug 2023 supervised by Yi-Ping, Huang
    • Tezos, NFT, Ticketing, cross-chain bridge, Ethereum
    • Participated in auditing of the smart contracts for the profile pictures (PFP) project, Tez Dozen, and the NFT trading platform, akaSwap.
    • Crawled and visualized akaSwap's transaction data to gain insights into user behavior and market dynamics.
    • Shared expertise in Solidity, NFT Ticketing, OpenSea, Jenny DAO, and SushiSwap to provide valuable input on smart contract design, security, and usability.
    • Designed and implemented a cross-chain bridge that enables NFT exchange between the Tezos and Ethereum blockchains.

Skills

  • Technical Skills
    • Blockchain, Artificial Intelligence(Machine Learning, DeepLearning), Web(Frontend/Backend) Development, Cloud-Native Applications, Computer Vision
    • Socket, Chrome Extension, SSG/SSR, MVC
    • Blockchain(EVM Compatible Chains(L1/L2), Tezos, COSMOS, Solana)
  • Software Skills
    • Languages: Python, C/C++, JavaScript/TypeScript, Solidity, Java, SmartPy, Swift, Dart, C#, Matlab
    • Tools: FastAPI/Flask, NodeJS, React(NextJS, ), Tensorflow, Scikit-Learn, OpenCV, OpenGL, Numpy, Pandas, Matplotlib, Processing(p5), Flutter
    • Storage: NoSQL(MongoDB), SQL(PostgreSQL, MySQL), p2p(orbitDB, GunJS), IPFS

Education

  • National Taiwan University
    Master’s Degree, Computer Science and Engineering (Sep 2021 - Jan 2024)

Publications

  • Sung, H.-M., Chen, T., Tseng, H.-C., Prayogo, B., Lin, J.-Y., & Hung, Y.-P. (2023). akaTick: Hybrid Mobile E-Ticketing System Based on Non-Fungible Tokens. 2023 IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom), 686–687. https://doi.org/10.1109/MetaCom57706.2023.00126
  • Tseng, H.-C., Tu, C.-W., Huan, X.-Y., & Chia, T.-L. (2020). Nighttime vehicle light detection based on deep learning and image enhancement. 2020 IPPR Conference on Computer Vision, Graphics, and Image Processing (CVGIP), 1–8.

Honors

Academic Performances

  • Research Excellence Award  (Jun 2021)
    • Recognized for outstanding research contributions, placing among the top 1% of graduating students.
  • College Student Research Scholarship  (Jul 2020)
  • Intel Andy Grove Scholarship  (Jan 2019)
    • Selected as one of 367 recipients worldwide, out of over 2,000 applicants, for demonstrating academic excellence, leadership potential, and promising accomplishments.
  • Academic Achievement Award
    • Top 1% in class (3 semesters) and Top 3% (3 semesters)

Certificate/Courses

  • Docker and Kubernetes: The Complete Guide - Udemy by Stephen Grider (Jun 2022)
  • Ethereum and Solidity: The Complete Developer's Guide - Udemy by Stephen Grider (Feb 2022)
  • Artificial Intelligence Application and Technology - Computer Skills Foundation (Aug 2020)
  • Big Data Process and Analysis - Computer Skills Foundation (Jun, 2020)
  • How Google does Machine Learning - Google Cloud (Sep 2019)
  • Computer Programing - Coursera (National Taiwan University)
  • Autodesk MAYA Certified Professional - Autodesk (2019)

Problem Solving

  • NTU FinTech kaggle1 (rank:3/36) kaggle2 (rank: 31/133) (2021)
  • Micro Processor App Design Contest (2018, 2019)
    • Android, Arduino
    • related to the project - Smart Potting System with Weather Forecast.
  • Robot Design Competition (2015, 2016)
    • C/C++, Arduino, Raspberry pi, Python, Linux
    • I led a team of 4 talented people to win First place and Third place in the competitive contests among more than 30 teams with innovative ideas and accomplishments in 2015 and 2016 respectively.
  • Taipei class website contest (2011)
    • HTML, CSS, JavaScript
  • Science fair - Honorable Mention (2012, 2011, 2010, 2009)
    • Science, Physics, Computer Science

Projects

  • FansTick
    • React Native, NextJS
  • Early detection of human tremor symptoms and home care services based on video and deep learning (Python 2021)
    • Tensorflow, Deep Learning, LSTM, RNN
    • Developed an LSTM-RNN model using Tensorflow Functional API to distinguish between patient tremor frequency and noise.
    • The model achieved an average accuracy of 94.8% on a dataset of 160,000 simulated signals.
    • The model can distinguish between different tremor frequencies with an accuracy of 94.14% and 95.42%, respectively.
    • repo
  • Adaptive Driving Beam System based on Deep Learning and Image Enhancement (Python 2021)
    • Computer Vision, Numpy, Scikit-Learn, Algorithm, Linear Algebra
    • Employed Nakagami image conversion, EdgeBox feature extraction, CycleGAN night-to-day conversion, YOLO object detection, and feature fusion with SVM classification.
    • Developed an Adaptive Driving Beam Headlamp system using camera calibration and projection to generate precise light patterns.
    • This project combines the recent DL research and the image enhancement to detect vehicles at night.
    • Achieved an average accuracy of 58.5% and an average recall rate of 59% on a variety of real-world video footage.
    • paper repo1 repo2 report-zh
  • Decentralized showroom (Decentralized Applications Term Project)
    • FastAPI, Tezos, React, MongoDB
    • Developed the backend API services for the showroom application, including authorization, room management, and NFT metadata retrieval.
    • Used FastAPI, React, and MongoDB to build the application.
    • Implemented the decentralized authentication mechanism using digital signatures.
    • articlerepo
  • Secure NFT Ticketing System (Multimedia Security Term Project)
    • FastAPI, Python, Security, Tezos, Steganography, Homomorphic encryption
    • Designed and implemented the backend API services for the ticketing system, including authentication, ticketing, and data services.
    • Used Python, FastAPI, and MongoDB to build the system.
    • Applied homomorphic encryption and steganography to create secure QR codes.
    • video presentation reposlidedemo
  • MCU-up (Side Project)
    • NodeJS, MVC, CRUD, Express, Authentication, Server-Side Rendering, MongoDB
    • MCU-up is a review site using MVC pattern, NodeJS, and Express from scratch with Authentication, CRUD, and Server-Side Rendering.
    • Led a team of 5 developers and designers to develop the application.
    • The application has been used by over 1,000 students.
    • article
  • alanhc.github.io
    • Static Site Generation
    • The application uses static site generation (SSG) to speed up page load times and improve SEO.
    • demo
  • Bitcoin Digital Signature Mechanism Implementation (FinTech course project)
    • Blockchain, Bitcoin, Python, Sagemath, ECDSA
    • Implemented the Bitcoin digital signature mechanism using SageMath.
    • The implementation is based on the Elliptic Curve Digital Signature Algorithm (ECDSA), using the secp256k1 elliptic curve and the SHA-256 hash function.
    • repo
  • Change My Style (Side Project)
    • FastAPI, Tensorflow, OpenCV, StyleGAN, Tkinter
    • Developed a machine learning inference API using FastAPI and Tensorflow.
    • Built a client application using Tkinter and OpenCV to interact with the API.
    • repo
  • Bloom Filter (Decentralized Applications Midterm Project)
    • solidity, Python, Algorithm
    • Developed a blockchain-based vaccine tracking system utilizing Bloom Filter for efficient and rapid vaccine batch number verification with lower time complexity O(k) and space complexity O(m).
    • slide articledemo
  • AlgViz (Algorithm course project)
    • Algorithm, JavaScript
    • Implemented algorithms including AVL Trees, Binary Search Trees, Dijkstra's algorithm, Kruskal's algorithm, Max Heaps, multiple sorting algorithms, and Topological Sort, and visualized the structures and time complexities of different sorting algorithms.
    • demorepo
  • Smart Recommended Shelves (Maker NTU Hackathon Project) (2019)
    • Arduino, Computer vision, Deep Learning, Embedded systems, C/C++, Python, OpenCV, CNN
    • Developed a smart shelf system to help indecisive customers make purchasing decisions.
    • Used OpenCV to capture facial images and CNN to determine the customer's gaze direction.
    • Controlled the smart shelf using Firmata protocol.
    • repo
  • Fake News Hunter Extension (Google Solution Challenge Project) (2020)
    • Chrome Extension, GCP, Python, Flask, GCP
    • Developed a Chrome extension to combat fake news, integrating with g0v's Cofacts API. The extension utilizes the Flask backend and leverages GCP's Cloud Function server for scalability and efficiency.
    • repo demo
  • Dcard trending post prediction (Side Project) (2020)
    • SQL, Machine Learning, Data Analysis
    • Developed a data pipeline to predict popular Dcard posts using SQL, scikit-learn, MySQL, and matplotlib.
    • Cleaned and analyzed Dcard data to identify key features for predicting popularity.
    • repodemo
  • Chrome Dino Jumper (Side Project) (2020)
    • Pose Estimation, Deep learning, Computer vision, Machine learning, JavaScript, p5.js
    • Using Posenet and modifying repo from source detecting human motions to control chrome dinosaurs.
    • Modified the source code of the Chrome Dino Runner game to add a pose-based jumping mechanic.
    • Used the PoseNet model from ml5.js to track the player's pose.
    • Used the p5 Vector class from p5.js to calculate the dinosaur's jump trajectory.
    • repo demo
  • Plant Pathology Challenge - Kaggle (Deep Learning Course Project)
    • DenseNet, Transfer Learning, Plotly, Tensorflow, Distributed Training, TPU, Deep learning, Computer Vision, Machine learning, Python
    • Studied state-of-the-art classification models, including DenseNet, EfficientNet, InceptionResNetV2, and image filtering methods.
    • Attempted to solve the Kaggle-Plant Pathology Challenge using transfer learning techniques and compared different methods.
    • Implemented image visualization techniques to analyze image data using Plotly, TensorFlow distributed training techniques and TPU usage.
    • repo reportslide
  • Drum.io (Interactive Media Programming Final Project)
    • socket Programming, Arduino, KNN, C/C++, NodeJS, KNN(ml5.js), socket.io, JavaScript
    • Awarded 1st place in Interactive Media Programming (52 participants) and 3rd place by collective vote (50 participants) for developing a multiplayer interactive game combining machine learning and hardware. Inspired by Chrome Music Labteachablemachine, and Agar. io, the game uses KNN algorithm to analyze acceleration data from an embedded device to create an air drum experience and enable online battles.
    • repo
  • Landing Planet (Interactive Media Midterm Project)
    • Java, Physical Simulation, Android
    • Received Second Place by collective vote (50 participants) for developing a space exploration game using Java and "Computer Graphics" concepts. Inspired by Mars: Mars, the game utilizes Java Processing to create immersive visuals and interactions, featuring physics simulations (gravity, landing) and particle effects (spaceship thrust, landing). An Android version of the game is also available.
    • repo demo
  • OpenGL Dancing Robot (Computer Graphics Term Project)
    • C/C++, OpenGL, OpenCV, Computer Graphics, Model Control, Animation
    • Got First place in the Computer graphics final project in a collective vote of 52 people.
    • Implemented a model control system in OpenGL, enabling a robot to jump, inspired by Maya's graphical model control system.
    • Utilized computer graphics concepts such as alpha, model import, and coordinate movement.
    • video demo repo
  • Money-Sea Crisis - A Global Warming Awareness Game Developed in Unity - NASA Space Apps Challenge Hackathon (2019)
    • C#, Unity, Game development
    • Developed a game for the NASA Hackathon to raise awareness of the impact of global warming.
    • Used Unity to create a game that combines a Monopoly-like land-buying mechanic with a quiz to teach players about climate change.
    • The game allows players to experience the effects of sea level rise firsthand and earn money by answering questions correctly.
    • project pagerepo
  • Mask Map Application, inspired by GDG Howard's mask map (Side Project)
    • Web Crawling, SQL, MySQL, GIS, Leaflet.js, Pandas, Web development, Python, Pandas, JavaScript
    • Crawled government open data daily to collect mask availability information.
    • Cleaned and formatted the data using Pandas.
    • Stored the data in a MySQL database for easy access.
    • Visualized the data on a map using Leaflet.js.
    • repo
  • Air quality prediction (Machine Learning Midterm Project)
    • Data science, Machine Learning, Python, Scikit-Learn, Algorithm, Matplotlib, Pandas
    • Learn different ML algorithms and how they can be used in daily life. Python, Pandas, matplotlib, scikit-learn, Algorithm (Linear regression, Bayesian classification)
    • Developed a Linear Regression algorithm with a high R^2 of 0.85 and a low MSE of 21.34.
    • Utilized Pandas, Matplotlib, and Scikit-Learn for data preprocessing, model training, and prediction.
    • repo slidereport dataset code
  • Flag and Religion (Machine Learning Final Project)
    • Data science, Machine Learning, Python, Feature Engineering, Matplotlib
    • Improved classification accuracy by 10% through feature selection and algorithm selection.
    • Studied and implemented support vector machines (SVMs) and naive Bayes classifiers.
    • Used UCI datasets and Pandas, Matplotlib, and Scikit-Learn to explore the effects of feature selection and different algorithms on classification accuracy.
    • reposlide dataset report code
  • Deep Learning Translation (Deep Learning Course Project)
    • seq2seq, RNN, LSTM, Natural Language Processing, Python, TensorFlow
    • Using a seq2seq model to translate English to Chinese.
    • Converted text into word tokens using a tokenizer.
    • Used an encoder-decoder architecture to generate the translated text.
    • repo report code
  • Face recognition (Deep Learning Course Project)
    • VGGFace, Deep Learning, Computer vision, Machine learning, Python, TensorFlow
    • Learned the VGGFace model to use face embedding techniques to generate feature vectors for face classification.
    • Used cosine similarity to classify the faces of team members and celebrities.
    • repo report
  • Intel Image Classification - Kaggle (Deep Learning Course Project)
    • Deep Learning, Computer vision, Machine learning, Python, Keras
    • Implemented a convolutional neural network (CNN) using the Keras library to classify images of the landscape from the Kaggle-Intel Image Classification dataset.
    • Experimented with transfer learning techniques using FCN, simple CNN, and Resnet50 networks.
    • Observed the feature maps of each layer of the CNN to gain a deeper understanding of the principles and implementation of convolutional neural networks.
    • reportreport2report3
  • Pima Indians Diabetes - Kaggle (Deep Learning Course Project)
    • Implemented a multi-layer perceptron (MLP) using the Keras library to solve simple logic problems (AND/OR, XOR) and the diabetes pima dataset.
    • Experimented with different MLP architectures to compare training time and accuracy.
    • report dataset
  • Sales prediction (Deep Learning Course Project)
    • Deep Learning, Machine learning, Python, Keras
    • Implemented a recurrent neural network (RNN) and long short-term memory (LSTM) model to predict future sales using a 12-month sales dataset.
    • Experimented with different hyperparameters to improve the accuracy of the predictions.
    • Evaluated the performance of the models using root mean square error (RMSE).
    • reportreport2
  • Identify signs of diabetic retinopathy in images (Data Mining Term Project)
    • Weka, PCA, Data Analysis
    • Used the Messidor dataset, which contains images of fundus with and without diabetic retinopathy.
    • Implemented the ensemble-based method proposed by Balint Antal and Andras Hajdu.
    • Extracted features from the images that represent the detected disease information.
    • Used Weka to visualize and analyze the data.
    • repomidterm reportfinal report
  • PDF2TEXT (Side Project)
    • Image Processing, Pandas, Optical Character Recognition
    • Developed a Python script to convert PDF files of sports courses offered by the school to text.
    • Used edge detection to detect squares and extract the region of interest.
    • Used adaptive thresholding to enhance the image.
    • Used EasyOCR to recognize the text and Pandas to format the text and save it to a file.
    • repo
  • Smart Potting System with Weather forecast (Research)
    • Bluetooth, Embedded System, Microcontroller programming, Natural language processing, Android, Mobile app development
    • Developed a plant care system for the elderly using a Linkit7697 development board and multiple sensors to monitor weather conditions and plant health. The system also includes a Bluetooth pairing feature and a conversational AI-powered app that allows users to interact with their plants in a more engagingly.
    • This project collects sensor data to speed up weather forecasts.
    • repo
  • Telegram shell (Programing Design of Networking Communication Term Project)
    • Python, Docker, Cloud Computing, Containerization
    • Developed a personalized private cloud service system for a laboratory using a Telegram-based command-line interface and containerization technology. The system provides a secure, fast, and efficient way for multiple users to share a single host without using traditional cloud services.
    • repo
  • Covid News (Side Project)
    • Web Crawling, Concurrency, Flask
    • Developed a Python web scraping project to crawl data from the Taiwanese Ministry of Health and Welfare's website, including the number of cases, deaths, and vaccinations.
    • Used Python's multiprocessing library to parallelize the crawling process, which significantly improved the performance of the project.
    • Hosted the web scraping results on a Flask web application with a Bootstrap frontend. The application allowed users to view the data in a variety of formats, including charts and tables.
    • repo
  • Radioactive Music Box (NASA Space Apps Challenge Hackathon) (2018)
  • Swift Practice (Side Project)
  • Rall-call (Side Project)
  • aka-viz Visualize NFT trading platform (Side Project)
  • Course Crawler (Side Project)

Extra-Curricular Activities

Leadership and Organization

  • Founder and Lead of Developer Student Club (2019-2021) Advisor by Yuh-Pyng, Shieh and Google Developer Student Clubs
    • Python, Tensorflow, Flutter, Machine Learning, Deep Learning
    • I’ve been appointed as one of 800 leaders among more than 3,000 passionate applicants worldwide, for helping my peers continuously learn and connect in a 2-year professional development program.
    • Founded and led a club of 6 core members, fostering a community for tech-passionate students.
    • Organized engaging events and talks on various technologies, reaching over 73 attendees.
    • Delivered talks on Deep Learning and PoseNet (18 attendees, 210 views), Python and Colab (26 attendees), and Flutter (29 attendees).
    • post

Technical Skills Development

Research and Development

  • Published research paper in 2020 IPPR CVGIP (Computer Vision, Graphics, and Image Processing).
  • Presented technical talks:
    • Ethereum & Smart Contract at LINE Blockchain study group (August 2022)
    • Deep Learning and Dino PoseNet at Developer Student Club (March 2020)
  • Machine Learning Game workshop - Program the World Association

Community Engagement

Additional Achievements

  • Microsoft Intern Program participant
  • Google Solution Challenge Team Captain (2020)
  • NASA Space Apps Challenge participant (2018, 2019)
  • MakeNTU hackathon participant (2019)
  • Micro Processor App Design Contest participant Team Captain (2018, 2019)

Talks

  • Ethereum & Smart Contract (LINE Blockchain study group) (Aug 31, 2022) slide
  • Deep Learning and Dino PoseNet (Mar 26, 2020) youtube slide 18 attendees, 210 views
  • Flutter Interact: Viewing Parties (Nov 21, 2019) Workshop (Nov 28, 2019) - 29 attendees
    • Introduce Dart, Flutter, and its concept.
  • Introduce to Python and Colab (Oct 6, 2020) - 26 attendees - youtube(no voice)
    • Python, Git

Links

Interest

  • Drum
    • Performance
      • 盧廣仲(Crowd Lu) - 快魚仔(Fish) (Feb 2020)
      • Marvin Gaye & Tammi Terrell - Ain't No Mountain High Enough (Sep 2019)
      • The Jackson 5 - I Want You Back (March 2019)
      • Kelly Clarkson - Because Of You (Aug 2018)
      • The Chainsmokers & Coldplay - Something Just Like This (Jan 2018)
  • Video Making

@alanhc