About me

I am a Ph.D. student specializing in Computer Vision and Deep Learning at the RoPeRT research group, University of Zaragoza, Spain. My academic journey began with a B.Sc. in Mathematics, followed by an M.Sc. in Robotics, Graphics, and Computer Vision, both of which I completed with honors.

Ph.D. Student in Computer Vision and Deep Learning

I am finishing the second year of my Ph.D. thesis, focusing on various tasks in video understanding, such as action recognition, temporal grounding, and video question answering in challenging scenarios like extremely long-duration videos, event-based data, and egocentric perspectives. I am also interested in applying Bayesian deep learning to computer vision tasks and transferring sota computer vision and deep learning models to robotics.

Video understanding

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    Temporal grounding

    Can we temporally localize actions in egocentric videos?

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    Action recognition

    Can we recognize actions in low-light videos?

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    Visual Question Answering

    Can we answer fine-grained questions about long videos?

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    VLMs

    How can we adapt vision-language models to handle long videos?

Other topics of interest

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    Bayesian Deep Learning

    Can BDL techniques increase the performance and calibration of current DL models?

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    Robotics

    How can we leverage sota deep learning models for robotics?

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    Event cameras

    Are event cameras particularly well-suited for low-light scenarios?

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    Generative models

    Can we leverage generative models to drone shows?

Resume

Education

  1. Ph.D. Student in Computer Vision and Deep Learning

    2023 — Present

    Ph.D. student at the RoPeRT research group, University of Zaragoza, Spain. Supervised by Ana C. Murillo and Rubén Martínez-Cantín.

  2. M.Sc. in Robotics, Graphics and Computer Vision

    2021 — 2022

    Grade: 9.5/10: Honours distinction in 56% of the courses, including Master's Thesis, Computer Vision, SLAM, Machine Learning or Applications of Deep Learning.

  3. B.Sc. in Mathematics

    2017 — 2021

    Grade: 9.1/10: Honours distinction in 38% of the courses, including Bachelor’s Thesis, Graph Theory and Combinatorics, Operations Research or Regression Techniques.

Experience

  1. Ph.D. student at the RoPeRT research group, University of Zaragoza, Spain.

    Jan. 2023 — Present

    Video understanding, including action recognition, temporal grounding, and video question answering in challenging scenarios such as long-duration, event-based, and egocentric.

  2. Junior researcher at the RoPeRT research group, University of Zaragoza, Spain.

    Sep.2022 — Dec.2022

    Analysis of the primary Bayesian deep learning techniques and usage in the context of active exploration in reinforcement learning for robotic manipulation.

  3. Internship at Bitbrain Technologies, Spain.

    Feb.2022 — Jun.2022

    EEG decoding from brain-computer interfaces in order to classify motor activities such as different types of object grasping.

  4. Junior Researcher at the Stochastic Models Group, University of Zaragoza, Spain.

    Sep.2020 — Jun.2021

    Data analysis for studying the evolution of COVID-19 in Aragón, Spain by way of survival analysis models and clustering algorithms.

Awards

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    Step Grounding Ego4D Challenge Winner

    Winner of the Step Grounding Challenge organized by EgoVis Workshop at CVPR 2024.

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    Second Place at Elevator Pitch Contest Unizar

    Second Place in the Elevator Pitch Contest at the VIII Triple Helix Meeting with Unizar.

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    Extraordinary Award in M.Sc.

    Award for the best academic record in the Robotics, Graphics and Computer Vision M.Sc.

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    García Galdeano Award in Mathematics B.Sc.

    García Galdeano Award for achieving the second-best academic record in the Mathematics B.Sc.

Grants

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    Predoctoral Researcher Grant

    Granted by the Government of Aragón and Spain to support predoctoral researchers in their Ph.D. studies.

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    Scholarship Grant at the University

    Scholarship granted by the Spain government to collaborate with a University department.

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    Undergraduate Grant to study at the University

    Grant to study at the University thanks to undergraduate studies finished with the highest honours.

Daniel lewis

Daniel lewis

sdvf

Languages

  • Spanish (Mother tongue)
    100%
  • English
    80%
  • French
    50%

Programming Languages

  • Python
    90%
  • R
    50%
  • C/C++
    50%
  • SQL
    30%

Publications

Teaching

Computer Science B.Sc.

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    Artificial Intelligence

    29 hours of practice.

Robotics, Graphics and Computer Vision M.Sc.

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    Machine Learning

    69 hours of practice.

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    Applications of Deep Learning

    6 hours os practice.

Contact

Contact Form