ELogs/Febian: Difference between revisions

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This section highlights the events/activities that have been done throughout the PhD. It also includes what have been learned and important key takeaways (From the most recent to the oldest one).
This section highlights the events/activities that have been done throughout the PhD. It also includes what have been learned and important key takeaways (From the most recent to the oldest one).


'''(Oct 2024)'''
'''(Oct 2024)'''
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**Presenting the Workflow of current FPGA coding for DAQ process
**Presenting the Workflow of current FPGA coding for DAQ process


'''(Jul 2024)'''
*STFC Summer School in Liverpool:
*STFC Summer School in Liverpool:
**Networking with people from the same cohort
**Networking with people from the same cohort

Revision as of 20:50, 22 November 2024

This is Febian's Electronic Log in completing PhD at UCL from September 2023 to September 2027

To Do

Last updated 22/11/24’’

  • Coding FPGA to interface the new daughter board utilising Zmod Port
  • Investigating Bragg Curve Fitting
  • Bragg Curve Fitting inside FPGA
  • Investigating Naoki attempts in fitting Bragg curve using minimiser
  • Exploring ML approach for bragg curve fitting

Dates and Progress

Date Event
2 October 2023 Starting PhD Journey in PBT Group at UCL
9 November 2023 MAThRAD 2nd Workshop at Teddington
8 January 2024 Starting Industrial Project with Peak.AI
18 - 31 January 2024 Away for family vacation in US
21 - 23 February 2024 Valencian Proton Therapy Facility Workshop
25 April 2024 CDT Industrial Partner Presentations (Peak.AI)
30 April - 1 May 2024 Beam Test at UCLH: Quarc, Temperature (NPL) and Pixel Sensor (Birmingham)
14 & 17 May 2024 Science Communication Workshop
8 - 17 June 2024 PTCOG62 Annual Conference in Singapore
17 - 30 June 2024 Away on Vacation in Indonesia
14 - 19 July 2024 STFC Summer School in Data Intensive Science Liverpool
9 - 12 Sep 2024 Phystat - Statistic meet Machine Learning Workshop, Imperial College London
26 Aug - 27 Sep 2024 DKFZ 6th Summer School in Medical Physics
18 - 19 Oct 2024 HITRI Hadron Therapy Workshop: Status and Plans for Future
24 Oct 2024 CDT DIS Partner Event Fall - Spotlight talk and poster

PhD Completed

This section highlights the events/activities that have been done throughout the PhD. It also includes what have been learned and important key takeaways (From the most recent to the oldest one).

(Oct 2024)

  • CDT DISI Partner Event Fall
    • Created an A0 Poster on what will be done throughout the PhD journey
    • Presenting a 2 minutes spotlight talk to industrial partner
  • Curve Fitting on FPGA started
    • Fittings started on Linear Regression application
    • Discuss and seek for guidance from Naoki - suggested to check HLS4ML and Vitis
  • Hadron Therapy Workshop status and perspectives, plans for next generation facilities (Remote)

(Jul 2024 - Sep 2024)

  • Phystat - Statistics meets Machine Learning Workshops by Imperial College London (Online)
    • Various algorithm, statistical model and Machine Learning application in HEP and Astrophysics world
    • Discussion on interpretability, data sources, samples relevance, and mismodelling.
  • DKFZ 6th Summer School in Medical Physics.(Online)
    • Recapped on Radiobiology and particle interactions
    • Scintillators and luminescent materials for detector
    • Monte Carlo simulation insight
  • Initiate the creation of PBT Group Github organisation for Collaborative workspace.
  • Practical FPGA and Implementation in Vivado
    • Installation and run through the current Nexys Video FPGA code for DaQ (assisted by Matt)
    • Follow through the STFC Training books for RTL to FPGA Basics.
    • Implementation of FPGA code on easy applications (LED and Gates)
    • Creating a github repository on the FPGA end-to-end guide on debugging and implementation
    • Learning on Hierarchical programming and IP components in Vivado
    • Learning FTDI (USB driver management)
    • Creating Github repository documenting a stable ground for DAQ using Nexys Video FPGA
    • Presenting the Workflow of current FPGA coding for DAQ process
  • STFC Summer School in Liverpool:
    • Networking with people from the same cohort
    • Highlighting session about: Neural Network, Clustering and Data Visualisation, Publishing Code

(Jun 2024)

  • PTCOG62 Conference in Singapore
    • Education session includes medical aspects of PBT, standard procedure in QA, etc
    • Open source data/tools and AI discussion in PBT
    • Networking with people from the same field of research

(Apr 2024 - May 2024)

  • Science Communication Workshop
    • Tips for good presentation slides and skills
    • Body language impact on communication
  • Beam Testing at UCLH
    • Helping and learn logical step by step set up
    • Taking notes of the experiments taken
  • Data Acquisition Process and Plotting the data using the provided code by Sonia
    • Marking the USB-C configuration (which side to plug)
    • Testing supply voltage in each node of DaQ
    • Formulating consistent working DaQ with the latest Matt Version FPGA code
    • Setting up data acquisition process on MacBook M2 Chips

(Oct 2023 - Mar 2024)

  • Group Project with Peak.AI
    • Working on RL PPO implementation for supply chain inventory management
    • Working on META-RL MAML algorithm for supply chain inventory management
  • Testing and Categorising types of different USB-C 3.x Cable regulating in the market
    • 16 Cable was tested and 3 general classification of USB-C 3.x were found
  • Doing literature review as part of MPHY0038 Assignment on IMPT and the emergence of AI in the field.
  • Reading Saad (Previous PhD student) Thesis
  • Modules Completed:
    • PH4515 Statistics Course Royal Holloway (Mathematical theory behind ML)
    • PHAS0102 High-Performance Computing (GPU optimisation)
    • COMP0233 Research Software using Python (Basic Python and Colaborative work)
    • MPHY0038 Treatment Radiation (Radiotherapy theory and highlights)
    • COMP0210 Research Computing with C++ (C++ introduction)
    • SPCE0038 Machine Learning with Big Data (Using python to implement ML algorithm on big data)