This is just a timeline of various selected topics, source material and projects I was working on in the past to give you an overview and for me to keep track:

2020

Paper: TabNet

  • TabNet: Attentive Interpretable Tabular Learning
  • Keywords: Tabular data, interpretable neural networks, attention models

Project: Automated Stock Trading via Interactive Brokers

  • Data Streaming via Interactive Brokers and RabbitMQ
  • Data Storage via time series database TimeScaleDb
  • Containerisation of Interactive Brokers Software
  • Container orchestration for 5 workers:
    1. retrieving live stock data from Interactive Brokers API
    2. cleaning and storing stock data
    3. calculating time series features and stock indicators
    4. execution of trading strategy
    5. live trading of stocks via Interactive Brokers API

Multi-armed bandits

Paper: Causal Impact

  • Inferring Causal Impact Using Bayesian Structural Time-Series Models
  • Keywords: Causal inference, counterfactual, synthetic control, observational, difference in differences, econometrics, advertising, market research.

WhitePaper: Multiworld Testing:

  • Multiworld Testing Decision Service: A System for Experimentation, Learning, And Decision-Making
  • link

2019

Book: Forecasting: Principles and Practice

  • Forecasting: Principles and Practice

Project: Prediction of Food Intolerances

Paper: Shap Values

  • Consistent Individualized Feature Attribution for Tree Ensembles, Scott M. Lundberg et al.
  • link

Paper: NgBoost

Framework: H2O

Recurrent Neural Networks: LSTMs

Bayesian AB testing

2018

Paper: Xgboost

Paper: Catboost

Paper: LightGbm

Project: Stock Trading Strategies

2017

Framework: D3 for Data Visualisation

Project: KnowNet Document Search Engine

  • Development of a personal knowledge graph and graph based search engine that connects personal information (e.g. local or cloud files, emails and notes) in a network of nodes and allows contextual full text search
  • WebApp development using React, Node.js and hosting on Heroku
  • Business Model development
  • Application for an Exist Business Start-up Grant

Python Packages for Natural Language Processing

  • NLTK
  • GENSIM

Paper: Topic Modelling

  • Latent Dirichlet Allocation
  • https://ai.stanford.edu/~ang/papers/nips01-lda.pdf

Paper: PageRank

2016

Paper: Monte Carlo Tree Search (MCTS)

  • link

Frameworks:

  • Apache Spark (Scala)
  • Kafka (Scala)

Project: Big Data Risk Reporting Platform

  • Design and Implementation for a DAX company
  • Programming Language: Scala

Master Thesis:

  • Modelling the global trade network: Nodes act as regional economical sectors (agriculture, automobile industry, etc.) and edges are trading routes between them
  • This networks demand and supply can be perturbed by climatic extreme events (floods, droughts, tornados, etc.)
  • Simulation of the distrubance propagation through the network
  • Application of Decision Trees to predict the most vulnerable network nodes