A Chinese in Amsterdam. I have obtained the Master degree of Computer Science in UvA/VU joint degree, focusing on Large-scale Data Mining and Analytics. Currently, I am working as a Software Engineer at IT Class in ING(Internationale Nederlanden Groep).
Curriculum VitaeConcentrate on Computer Science and technologies
Web Data Processing, Large Scale Data Engineering, Software Asset Management, High Performance Computing and Big Data, The Social Web, Information Visualization, Web Services and Cloud-Based Systems, Experimental Design and Data Analysis, E-Commerce Law, Data Mining Techniques, Machine Learning for the Quantified Self, Protocol Validation, Service Oriented Design, Performance of Networked Systems
Calculus, Linear Algebra and Analytic Geometry, Probability Theory and Stochastic Process, Fundamentals of Programming, Mathematical Statistics, Computer Organization, Computer Network Principle, Data Structure and Algorithms, Operating System Principles, Discrete Mathematics, Mathematical Logic, Compilers Principles, Assembly Language, Fundamentals of Optimization, Artificial Intelligence, Software Defined Network, Software Engineering, Computer Graphics, Algorithm Analysis and Design, Database System, Software Engineering, Design of VLSI Circuits, Introduction of Neuroscience, Essentials of Life Science, Circuits, Digital Logic Circuits, Analog Electronics
A fast learner with continuous learning
Finance knowledge: Computational finance, Financial market and institutions, Payments. Banking operations: Trading capturing, Know your customers, and Credit risk.
Linear Model, Decision Tree, Neural Networks, Support Vector Machine, Bayes Classifier, Boosting, Random Forest, Clustering, Principal Components Analysis, Semi-supervised Learning, Reinforcement Learning, and Deep Learning includes Convolution Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, and Variational Autoencoder.
Text Mining, Latent Dirichlet Allocation, Sentiment Analysis, Web Data Processing, Word Sense Disambiguation, Distributional Memory, Named Entity Recognition, and Content-based Social Web Analytics.
Cloud Computing (IaaS, PaaS, and SaaS), High Performance Computing, Distributed Computing, Massive Data Processing, Streaming Processing, Urban Computing, Recommendation System, and Large-scale Data Processing Engine.
Beyesian Analysis, Multiple Linear Regression, Analyses of Variance (ANOVA), Generalized Linear Regression Models, Non-parametric Testing Methods, Permutation and Bootstrap Methods.
Image Recognition, Face Detection, Mask R-CNN, Segmentation Models, Transformer Models, Object Detection, and SLAM(Beginner).
Resource Description Framework, Web Ontology Language, Reasoning, Statistical Inference, Basic Level Detection, Linked Data, and Knowledge Graphs.
C, C++, Java, Scala, Python, R, MATLAB, SQL, and HTML/CSS/JavaScript
TensorFlow, Keras, PyTorch, Spark, Kafka, and Hadoop
Microsoft Azure, Amazon Web Service, Databricks, Docker, and Kubernetes
Microsoft Azure DevOps, Pipeline, Automation
Java, SprintBoot, HTML/CSS/JS, Web Components, Lit, Angular
SQL, Oracle Database, IBM DataStage, Query Optimization
Elastic Stack: Elasticsearch, Logstach, Kibana. ELKaaS
Mandarin(native), English(proficiency), and Japanese(basic)
Git, Latex, Markdown, Bash, SSH, and Adobe Creative Cloud
Companies or organizations and my responsibilities
Under a trading product based on ION platform, serve as a DevOps engineer and take charge of development on aglie working regarding to business requirements. The product is aim to capture, operate, and monitor every trade on a defined or interested exchange market. Over the platform, implement and improve components as a service.
Design and implement functionalities in a trading platfrom, including to identify the platform elements, to become familiar with the development technology (Java mainly), to be full-stack development role, the main focuse is going to be at the Web Portal Solution, the compliance dimension: restrict the way the end-user is accessign the data via web UI, to work with the Feature Engineers implementing the functional requirements.
Develop and deploy the KYC Custom View for a valid, reliable, and up-to-date single understanding of the interity risk, including to know the architectures of KYC Data Area, to learn analytic tools of DataStage and Oracle DB Developer, to operate data within Enterprise DataLake, to work around Name Screening functional requirements, to work as a Data Engineer over ETL, to implement data processing features by Business Analyst.
Use the concept of Observability Engineering in addition to traditional monitoring approach, namely Elastic products like beats (Filebeat, metricbeat, heartbeat), Elasticsearch, Kibana, for visualizing the data and convert it to useful information for DevOps engineers, business analysts, and testers. To implement the concept of Observability Engineering for infrastructure + applications using Elastic (ELKaaS), and adopt the above into the existing Azure DevOps Pipeline approach for Elastic implementation for CI/CD maturity.
The internship has the responsibility of performing the following duties: running a swift and smooth fulfillment and logistics operation, transportation, inventory controlling, securing optimal shipping methods to meet shipping schedules and requests, monitoring import and export processes to ensure legal and regulatory compliance.
Join in the research of Basic Level Detection which is a project about organizing categorial and hierarchical data in Semantic Web. Using machine learning and statistics, I design algorithms to detect concepts in Basic Level in large-scale corpora. Formed my Master Thesis with the title of Basic Level Detection: Learning from natural language corpora with various characteristics and synthetic features.
The work was around developing applications of data mining and analysis using statistics and machine learning algorithms. The applications were served for Urban Computing based on Big Data.
Participate in the Summer Workshop of the NUS SoC and got grade A, focusing on deep learning and tele-robotics project practice. The topic was image recognition in Computer Vison and robotics in Control System. The main deep learning framework is Keras. The electronic platform is Arduino.
Participate in the construction and update project of the artificial intelligence cloud computing platform, Jiutian, using Docker clusters with Kubernetes.
Active in the field of research and applications
Design and implement a monitoring dashboard, an adaptive shifting model, and Kubernetes job scheduler.
Focus on Basic Level research using ML, Statistics, and Psycholinguistics. Master Project at HCDA, CWI
Review the major development of the Semantic Web during the last decade and the future trend with challenges.
Use the collected self-quantified data to train a model and use it to predict the user's activity label.
Published on CCC2021. Generate Xi'an Drum Music similar to Huffman coding, a model named Xi’an Drum Music Generation via Variational Autoencoder.
Build ranked hotel recommendations for users that are searching for a hotel to book using LambdaMART.
Use Sentiment Analysis on Twitter data to investigate how does social media reflect the process and result of US Election 2020. Using this model, we can forecast the winner of the Election.
Develop a visual application to help users choose the most suitable country for them among 31 European countries.
A large-scale data engineering project. Train a deep learning model to learn the GPS location of a picture.
Bachelor degree thesis. A semi-supervised learning based on Variational AutoEncoder is used to solve the trajectory user linking problem.
Data analytics projects in Scala using Spark, Music Recommendation and Decision Tree / Random Forest Prediction.
NUS SoC Summer Workshop 2019, my achievement and showing. A deep learning and tele-robotics project.
Happy to hear from you
Personal Email: danferwang1123@gmail.com
Work Email: haochen.wang@ing.com