+ Developing new features and solving bugs for the Sim4Life (https://zmt.swiss/sim4life) product: GUI, simulation back-end, python integration, post-processing pipelines. Coding in C++ and Python.+ Working in accordance with Scrum methodology, in 4-week sprints. Serving frequently as Scrum master.+ Using Git, SVN, continuous integration system.

+ Built a novel data delivery architecture for future Internet architectures. Data delivery delay reduced by up to 80%, compared to state-of-the-art architectures.+ Built an architecture for video streaming on future Internet architectures. Improved video quality received by the clients and reduced the load on the sources by 60%.+ Built a distributed caching policy for future Internet routers that used content popularity to improve the performance of dynamic adaptive video streaming applications.+ Collaborated with Huawei Research USA to integrate the software prototype of our data delivery architecture in their future Internet video streaming testbed.+ Developed code in C/C++ and Python.+ Maintained the group's website, publication list, and annual report.

+ Developed a C++ application that enabled compliance verification of standard communication protocols for intelligent transportation devices.+ Built an Android application that records visited Wi-Fi networks and stores them in an SQLite database, used in mobility prediction algorithms.

+ Designed an application that improved the management of supplier's quality information.+ Server-side built with C\#/.NET, SQL. Client-side built with HTML, JavaScript/AJAX.

+ Built a data processing pipeline for social and sensor data fusion, that enabled prediction of people's mood, based on Twitter sentiment analysis and weather forecast data. Used big data tools like Hadoop, HBase, GSN, etc. + This work was published as a paper in IEEE MCN'12 (https://jonnahtan.github.io/files/mdm2012.pdf)In detail, I developed a travel recommendation system based on weather and social data. The data pipeline started with a data streaming processing called GSN (Global Sensor Network), developed at the lab where I was working (https://github.com/LSIR/gsn). I have created two sensors (producers): a social sensor, pulling data from Twitter, and a weather sensor, pulling data from WeatherUnderground. I also connected a consumer that stored this data in an HBase table. Then, this data was processed to generate a metric that measured how the mood of the people in the city was expected to be with certain weather conditions and stored that back into HBase. This was done in batches of 30mins. Finally, we could recommend a user what city to travel to, based on his preferences and the expected mood on the cities based on weather predictions.

Intern at the Signal Processing Laboratory, working for my MSc Thesis.+ Conceived and developed a protocol for real-time media streaming over peer-to-peer networks, using C++ and Matlab.+ Obtained highest grade for the MSc Thesis.+ Published a scientific paper at IEEE ICME, an international conference.