- Develop an email system which sends email alert once it detects something that users are interested in (e.g. negative values in the data, etc)- Develop an email system which user send the data by email and an email with the calculation results will be sent back to the sender. This is all done automatically- Continued performing and building upon tasks from previous positions

- Developing a system (using R) which can automatically extract ship names from the header (text mining), and which will send an email alert to users whenever any sanction vessel is detected- Shiny App: It consists of a web interface for users to upload files and change the parameters or options for calculation. It is easy to use and complex calculations can be completed in several minutes. For simple calculations, it only takes several secondse.g. Run LOCUS and calculate margin: Excel takes at least 1.5 working days, whereas Shiny app only takes around 4 minutes- UOA (Used Oil Analysis) Shiny App: It is a website consists of a tutorial video teaching users how to use the app and allow users to get the calculated output by just clicking the "Submit" button. User will get the output within several seconds (Note: Excel takes several hours performing the same task.)- Converting GraphQL API data (from websites) to csv/Excel regularly using R automation- Applying my text mining skills in extracting key information (e.g. IMO and company names) from a pile of texts from the US Government website (https://www.treasury.gov/ofac/downloads/sdnlist.txt). The extracted list is also updated automatically- Combining a large number of Excel/csv files into a single file within several seconds. It also works for Excel/csv with irregular cell range- Extract a large number of file names and put them into Excel for vlookup- Updating data using GraphQL via R- OTIF (On Time In Full) project: Use the data downloaded automatically and get the results using R within 30 seconds (Note: Excel takes 3 to 4 working days performing the same task.)- Create Power BI visuals using R- Continued performing and building upon tasks from previous positions*NOTE: R and Shiny are free software

- Data automation (automated data scraping from websites into Excel/csv, merging datasets and carrying out calculations regularly)- Providing business insights by connecting company’s customer data with the worldwide vessel movement data. Summarising it using R and visualising it using Power BI- Converting JSON API data (from websites) to csv/Excel regularly using R automation- Extracting text from pdf and converting it to Excel format (in batches)- Converting data from wide format and stacking a set of columns into a single column of data and vice versa- Calculating the distance between ports (>3,000 ports) using latitudes and longitudes- Maintaining and updating Power BI regarding the ship database- Continued performing and building upon tasks from previous position

- Analysing big data (writing up R code for analysing vessel movement data with >14 million records)- Being responsible for writing up and running R code for LOCUS (Location Operation Call Update Supply). It predicts lubricant lifting volume and ports based on historical records- OTIF (On Time In Full) project: Download the data manually and get the results using Excel- EAC (Estimated Annual Consumption) Calculation

-Analysing data-Writing up reports-Conducting interviews-Journal peer reviewing-Searching for journals via internet