---
# System prepended metadata

title: Dissertation projects at the intersection of data science and 'systems'.
tags: [Thesis, Project, Meeting, CSC8639]

---

Dissertation projects at the intersection of data science and 'systems'.
===
<!--https://hackmd.io/@Fig78KWdS3mtTh6qrg-FzQ/rk6eJJuH5/edit-->
###### tags: `Thesis` `Meeting` `Project` `CSC8639`

:::info
- **Location:** Zoom
- **Date:** April 28, 2022 10:30 AM
- **Present:** Carter Levy, Antreas Kasiotis, Chinomnso Ekwedike, Muzaffer Senkal, Joe Matthews, Iain Dixon, Stuart Jamieson, Tolu Awosanya
- **Agenda**
1. Welcome and Session Overview `5min`
    > [name=Matt]
2. Would does a 'dream' project look like to you? `5 mins`
2. Introduction to prior work `10 mins`
2. Open Discussion and Q&A `35min`
    > [name=Everyone]
3. Session Close and Next Steps `5 min`
	> [name=Everyone]
:::


---


# Session Aims
The aim of this session is to explore project ideas. By the end of this session we will hope to finalise the directions for each of your projects, and ways for these to collaborate.

You may find the following links useful: 
- [Project Handbook](https://ncl.instructure.com/courses/39394/files/5508157?module_item_id=2236456)
- [Interim Report Guidance](https://ncl.instructure.com/courses/39394/pages/interim-report-guidance?module_item_id=2236127)
- [Typesetting your Thesis](https://ncl.instructure.com/courses/39394/pages/typesetting-your-thesis?module_item_id=2236130)
- [(Frequently) Asked Questions](https://ncl.instructure.com/courses/39394/pages/frequently-asked-questions)
- [To help think about your problem](https://untools.co/)

# What does a 'dream' project look like to you?
*What tools would you like to learn?*
*What skills would you like to develop?*
*What sort of impact would you like to have, and for whom?*

## Carter Levy
- Develop understanding of new area and new techniques not taught on the course as of yet
- I am hoping to have an explainable impact with my work
- I want to achieve high marks (for lack of a better way to put it)
- DONE

## Antreas Kasiotis
- Learn about new topics
- Use new tools
- Enhance current knowledge
- 
- 

## Chinomnso Ekwedike
- Better understanding of empirical modelling and its relevance
- 
- 
- DONE


## Muzaffer Senkal
- data processing in streaming apps industry(real cases)
- project that can be used/impact in the industry 
- 
- DONE



# Useful resources
- DS2
    - https://www.usenix.org/conference/osdi18/presentation/kalavri
    - https://github.com/strymon-system/ds2
- NEXmark
    - https://beam.apache.org/documentation/sdks/java/testing/nexmark/
- One idea: creating more representative workloads that follow real-world trends
    - Java implementation of source functions as an extension to Apache BEAM
- Flink
    - https://flink.apache.org/
- Timeseries characterisation
    - We talk about trends and seasonality a lot
    - Much less about missingness and changepoint
    - Can we better understand what 'in the wild' TS datasets look like
- Empirical analysis of LTTB (https://github.com/sveinn-steinarsson/flot-downsample/)
- Streaming implementations of downsampling approaches
    - Arrival processes
    - Streaming logic
- LTTB for visualisation
    - https://github.com/santosjorge/cufflinks
    - http://holoviews.org/user_guide/Streaming_Data.html
- Workload Modelling
    - https://drive.google.com/file/d/14LabXg9zUV6xUhCgmlqRrHrLOZpn87KZ/view?usp=sharing


- Suggested Reading for Carter
    - asdf
- Muzaffer
    - Flink
    - Refine topic
    - Maybe workload function suggestion
- Nomnso
    - Deeper dive (with Stu and others)
- Antreas
    - Google workload traces? (https://github.com/google/cluster-data)
    - 