• EH14 4AS

    United Kingdom

Accepting PhD Students

PhD projects

Projects in the area of deep learning applied to neurodegenerative disesases are preferred, but other diseases are also possible.

20132024

Research activity per year

Personal profile

Research interests

My research interests are at the intersection of machine learning and healthcare (neurodegenerative diseases and cancer). My work focuses on creating advanced deep learning and evolutionary algorithms for diagnosis, prognosis, treatment and understanding of Parkinson's Disease, Huntington's Disease and ALS/Motor Neuron Disease.

Biography

Dr Marta Vallejo is an Assistant Professor at the School of Computer Sciences and Programme Director for the Graduate Apprenticeship programme in Data Science. Before that, she held a tenure-track Research Fellow position in biomedical signal and image processing for four years under the reputed Bicentennial Research Leader position. Prior to this appointment, she was head of AI and machine learning at ClearSky Medical Diagnostics Ltd. (www.clearskymd.com). She holds a PhD in computational intelligence and predictive modelling and an MSc in artificial intelligence. She has worked on several research projects in the areas of deep learning, evolutionary algorithms and predictive modelling. Notably, she was the lead researcher for "A Multiobjective Evolutionary Approach to Understanding Parkinson's Disease", a project that saw the development of new predictive models for Parkinson's disease management. She also led the Data Analytic work package at the Proteus project (https://www.proteus.ac.uk/), which focused on the treatment of critically ill respiratory patients using advanced microendoscopic imaging and sensing technologies. Dr Vallejo has also worked as a project manager on several EU research projects in Spain. She is also a fellow of the Higher Education Academy.

Research Grants and Projects

Lung Cancer Registration (EDDPMA-May22\100054).

This Primer Award project, funded by Cancer Research UK (CRUK), is led by the University of Edinburgh (UoE), where I serve as a Co-Investigator. My contribution included supporting a 9-month Postdoctoral Researcher using Heriot-Watt University funds from the Proteus project.

The research focuses on the application of deep learning for multi-modality image co-registration of super-resolution fluorescence microscopy images. This project was also supported by my successful application for EPSRC Access to High-Performance Computing Facilities (Cirrus), granting 96,432 GPU hours, which enabled computationally intensive deep learning tasks.

The outcomes of this work include the publication of a paper in Nature Communications Biology and the collection of a unique super-resolution FLIM image dataset from tissue samples at the ESRIC facilities, which will be utilised in future publications and funding proposals.

Following this work, I participated in the 2021-2022 second round of the University’s Data-Driven Entrepreneurship (DDE) Venture Builder Incubator, a programme run by Cancer Research UK in partnership with the University of Edinburgh Incubator, further supporting the translation of research into impact.

The Creation of the Next Generation of Clinical Assessment for Huntington’s Disease (EPSRC IAA Secondment) As the Principal Investigator, I collaborated with ClearSky MD on this project, which aimed to develop the next generation of clinical assessments for Huntington’s Disease. The goal was to transform conventional clinical assessments, such as the Montreal Cognitive Assessment (MoCA), which can be subjective, somewhat unreliable, and insufficiently sensitive to serve as universal screening tools.

This project focused on digitising conventional clinical assessments to create a robust, unsupervised "in-the-wild" assessment platform. The solution integrates data collected from sensors, including eye-tracking and finger-tapping tasks, and processes it using advanced machine learning and deep learning models. This approach seeks to improve the reliability, sensitivity, and scalability of clinical assessments for Huntington’s Disease.

Press Profile

I have actively participated in various public engagement activities aimed at promoting science, engineering, and robotics to diverse audiences. In 2023, I served as a Co-Investigator and Data and Evaluation Lead for the Rubbish Robots: Making Robots from Rubbish project, funded by the Royal Academy of Engineering’s Ingenious Public Engagement Award (£30,000). This initiative focused on encouraging creativity and sustainability by engaging participants in building robots using recycled materials. Additionally, I contributed to the flagship event of the UK Festival of Robotics, UK-RAS Robot Lab Live, which is a virtual showcase of cutting-edge robotics technology designed to inspire and educate audiences about the latest advancements in robotics.

That same year, I acted as a referee for the National Mining Museum and Rescuers Engineering Competition, where P7 pupils from six schools competed to design and construct innovative machines or vehicles for rescue missions. This competition provided young learners with an opportunity to explore engineering concepts in a hands-on and collaborative setting. I was also awarded an Athena Swan Summer Scholarship to mentor a female undergraduate student in creating an interactive lecture series on medical data for school pupils, contributing to efforts to inspire more women to pursue careers in STEM fields.

One of the highlights of my public engagement work was participating in the Dr Who Event at the National Museum of Scotland. This science exhibition provided a fun and engaging platform to share our robotics research with families and young audiences. I led the interaction sessions with Miro, a pet companion robot, allowing children to touch and play with the robot while learning about its applications in research. Similarly, in 2020, I hosted P7 pupil visits at the Robotic Assisted Living Testbed at Heriot-Watt University, a ‘living lab’ designed to develop robotic solutions for healthy ageing and independent living. During these visits, pupils were introduced to Pepper and Tiago robots and learned about their use in advancing independent living technologies.

Earlier in 2018, I served as a Co-Investigator and Data and Evaluation Lead for the Robosense project, which was also funded by the Royal Academy of Engineering’s Ingenious Public Engagement Award (£28,050). This project aimed to engage diverse audiences with robotics and sensor technologies, fostering curiosity and understanding of these emerging fields.

Through these activities, I have consistently demonstrated a commitment to inspiring and educating the public, particularly younger audiences, about the exciting possibilities in science, engineering, and robotics.

Research Group Contact Details

The lead of the ML-Healthcare group

https://martavallejo.github.io/ML-Health/

Key Research Words/Phrases

Machine Learning, Deep Learning, Evolutionary Algorithms, Neurodegenerative Diseases, Parkinson's Disease, Huntington's Disease, ALS, Motor Neuron Disease, Lung Cancer

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 11 - Sustainable Cities and Communities
  • SDG 15 - Life on Land

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Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
  • Research Culture Recognition Award

    Vallejo, M. (Recipient), 10 Jun 2024

    Prize: Prize (including medals and awards)

    File
  • Spirit of Heriot-Watt Awards 2017, Outward Looking

    Lane, D. M. (Recipient), Lohan, K. S. (Recipient), Vargas, P. A. (Recipient), Hastie, H. (Recipient), Broz, F. (Recipient), Vijayakumar, S. (Recipient), Hermann, M. (Recipient), Foster, M. E. (Recipient), Hauert, S. (Recipient), Couceiro, M. S. (Recipient), Baillie, L. (Recipient), Erden, M. S. (Recipient), McEwen, I. J. (Recipient), McConnell, A. C. (Recipient), Goodfellow, R. (Recipient), Dragone, M. (Recipient), Mastrogiovanni, F. (Recipient), Dondrup, C. (Recipient), Lim, M. Y. (Recipient), Murphy, S. A. (Recipient), Vallejo, M. (Recipient), Duncan, S. (Recipient) & Hassan, M. K. A. (Recipient), 1 Jul 2017

    Prize: Prize (including medals and awards)