About me

I am a 3rd year Phd Student in the Electrical and Computing Engineering Department of University of California, Santa Cruz working under professor Razvan Marinescu. My primary research interests encompass Image Reconstruction, Denoising, and Data Synthesis techniques for Medical Imaging applications. Currently, I am investigating Gaussian Splatting-based implicit 3D representations of CT brain datasets. The objectives are twofold: to achieve enhanced reconstruction quality from sparse-view signal acquisitions, and to enable novel viewpoint synthesis for radiographic imaging.

After getting my integrated MEng from the University of Glasgow in 2017, I worked for four years in industry as an embedded software and DevOps engineer in Belgium and France. My industry experience cultivated a strong desire to advance the state of the art through researching cutting-edge techniques. After performing an extensive literature review, I became particularly interested in Digital Signal Processing applications for Medical Imaging, which became the focus of my doctoral studies. During my first year of PhD I worked on a Poisson-MLEM algorithm for PET scanners on a CUDA interface for parallel computing. My main focus was to use CT scans as an attenuation map input during a reconstruction and obtain the attenuation factors.

DISCLAIMER: I'd like to give credit and thank github user "codewithsadee" whose template "vcard-personal-portfolio" I used as a basis for this website. Wonderful code, beautiful interface.

What i'm doing

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    Digital Signal Processing & Image Reconstruction

    My fascination in DSP stems from the entire process, from the moment an electronic signal arrives to the sensor all the way to the point where the final image or audio output is reconstructed. Moreover, I'm currently researching compressive sensing and 3D implicite scene representation for medical imaging.

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    Medical Imaging & Healthcare

    My interests lie in PET and CT, recently also started working on MRI. I am also interested in the projection of diseases in image space and how we can obtain accurate disease scores and score progression.

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    Generative Models & Statistical Machine Learning

    Generating medical datasets is my main objective in my PhD, being able to assist radiologists with additional statistical data that allow for cross evaluation could potentially be a huge help in complicated disease combinations and underrepresented populations, looking of the potential when used in Medical Imaging.

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    Music Writer and Producer

    On my free time, I enjoy writing and producing music. I've used Cubase and Reaper in the past. Curretly working on a new music album, stay tuned.

Supervisor

  • Razvan Marinescu

    Since January 2023 I've started working with professor Razvan Marinescu. Razvan is specialized in AI in Healthcare and has motivated me to look deeper into generative models and Statistical Machine Learning. You can read all about him by clicking here

Daniel lewis
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Daniel lewis

Richard was hired to create a corporate identity. We were very pleased with the work done. She has a lot of experience and is very concerned about the needs of client. Lorem ipsum dolor sit amet, ullamcous cididt consectetur adipiscing elit, seds do et eiusmod tempor incididunt ut laborels dolore magnarels alia.

Research

Research Work & Publications

  1. GaSpCT: Gaussian Splatting for Novel CT Projection View Synthesis [Under Review Process]

    2024

    Emmanouil Nikolakakis, Utkarsh Gupta, Jonathan Vengosh, Justin Bui, Razvan Marinescu

  2. BMapOpt: Optimization of Brain Tissue Probability Maps using a Differentiable MRI Simulator [Under Review Process]

    2024

    Utkarsh Gupta, Emmanouil Nikolakakis, Moritz Zaiss, Razvan Marinescu

  3. Quantum entanglement for identifying true c in a CZT-based PET system (poster presentation at SPIE Medical Imaging 2023)

    2023

    Emmanouil Nikolakakis, Gregory R. Romanchek, Emily Enlow, Shiva Abbaszadeh

  4. Comparison of Image-Derived Input Functions from a Dedicated Head and Neck PET Scanner and a Commercial System: A Simulation Study (poster presentation at NSS-MIC 2022)

    2022

    Gregory R. Romanchek, Emmanouil Nikolakakis, Guobao Wang, Shiva Abbaszadeh

Experience

Experience

  1. Atempo, Paris: Lead Software Engineer

    01/2020 — 09/2021

    - Toolchain and infrastructure development and maintenance
    - Simultaneous collaboration and support provided for multiple products in development
    - Significant input in source code reviewing and validating processes and refactoring

  2. Altran, Brussels: Consultant Embedded Software and DevOps Engineer

    09/2017 — 09/2019

    - Worked on projects as Embedded Software and DevOps Engineer at Toyota, Thales, NXP and Daikin
    - Developed software for IoT applications, BLE for headphones, aircraft communication systems and autonomous parking
    - Developed CI/CD and test automation infrastructure primarily using Jenkins, Git, Docker and Python

  3. Thermoelectric Conversion Systems Ltd. (TCS), Glasgow: Electronics Engineer Internship

    07/2016-01/2017

    - Designed a test fixture controller for testing thermoelectric generators
    - Development included PCB Design and programming a PIC24 microcontroller

Contact

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