Take the red pill. Take the blue pill.


Currently Lecturer at UCL. Previously PhD with Laura Toni and Tim Rocktäschel

Hi there, I am Eduardo,
researcher in AI.

I am currently a Lecturer at UCL in the Integrated Machine Learning Systems Master's programme. Previously, I completed a PhD at UCL under the supervision of Laura Toni and Tim Rocktäschel in the Learning and Signal Processing (LASP) group. Before that, I was a postdoctoral researcher at Imperial College London with Anil Bharath, and served as Machine Learning Lead at BuroHappold Engineering.
My research is at the intersection of Deep Reinforcement Learning and Large Language Models, with a focus on the Credit Assignment Problem. I am particularly interested in how AI evaluates actions, and in scaling reinforcement learning to enable open-ended learning and real-world generalisation.

Publications

  1. Aya Kayal, Eduardo Pignatelli, Laura Toni(2025). The impact of intrinsic rewards on exploration in Reinforcement Learning. arXiv preprint arXiv:2501.11533 . [Link] [PDF]
  2. Konstantinos Ntagiantas, Eduardo Pignatelli, Nicholas S Peters, Chris D Cantwell, Rasheda A Chowdhury, Anil A Bharath(2024). Estimation of fibre architecture and scar in myocardial tissue using electrograms: an in-silico study. Biomedical Signal Processing and Control 89 , 105746. [Link] [PDF]
  3. Eduardo Pignatelli, Johan Ferret, Tim Rockäschel, Edward Grefenstette, Davide Paglieri, Samuel Coward, Laura Toni(2024). Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL. arXiv preprint arXiv:2409.12798 . [Link] [PDF]
  4. Eduardo Pignatelli, Jarek Liesen, Robert Tjarko Lange, Chris Lu, Pablo Samuel Castro, Laura Toni(2024). Navix: Scaling minigrid environments with jax. arXiv preprint arXiv:2407.19396 . [Link] [PDF]
  5. Davide Paglieri, Bartłomiej Cupiał, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Łukasz Kuciński, Lerrel Pinto, Rob Fergus, others(2024). Balrog: Benchmarking agentic llm and vlm reasoning on games. arXiv preprint arXiv:2411.13543 . [Link] [PDF]
  6. Eduardo Pignatelli, Johan Ferret, Matthieu Geist, Thomas Mesnard, Hado Hasselt, Olivier Pietquin, Laura Toni(2023). A survey of temporal credit assignment in deep reinforcement learning. arXiv preprint arXiv:2312.01072 . [Link] [PDF]
  7. Aya Kayal, Eduardo Pignatelli, Laura Toni(2023). Does behavioral diversity in intrinsic rewards help exploration?. Second Agent Learning in Open-Endedness Workshop . [Link] [PDF]
  8. N Wong, S Meshkinfamfard, V Turbé, M Whitaker, M Moshe, A Bardanzellu, T Dai, E Pignatelli, W Barclay, A Darzi, others(2022). Machine learning to support visual auditing of home-based lateral flow immunoassay self-test results for SARS-CoV-2 antibodies. . [Link] [PDF]
  9. Konstantinos Ntagiantas, Eduardo Pignatelli, Nicholas S Peters, Chris D Cantwell, Rasheda A Chowdhury, Anil A Bharath(2022). Estimating Cardiac Tissue Conductivity from Electrograms with Fully Convolutional Networks.. CoRR . [Link] [PDF]
  10. Stathi Fotiadis, Eduardo Pignatelli, Mario Lino Valencia, Chris Cantwell, Amos Storkey, Anil A Bharath(2020). Comparing recurrent and convolutional neural networks for predicting wave propagation. arXiv preprint arXiv:2002.08981 . [Link] [PDF]
  11. Mario Lino, Chris Cantwell, Stathi Fotiadis, Eduardo Pignatelli, Anil Bharath(2020). Simulating surface wave dynamics with convolutional networks. arXiv preprint arXiv:2012.00718 . [Link] [PDF]
  12. Mario Lino Valencia, Chris D Cantwell, Eduardo Pignatelli, Stathi Fotiadis, Anil Anthony Bharath(2020). Fully Convolutional Approach for Simulating Wave Dynamics. arXiv preprint arXiv:2006.16934 .
  13. Mario Lino Valencia, Chris D Cantwell, Stathi Fotiadis, Eduardo Pignatelli, Anil A Bharath(2020). Simulating Surface Wave Dynamics with Convolutional Networks.. arXiv . [Link] [PDF]
  14. Gabriele Mirra, Eduardo Pignatelli, Serafino Di Rosario(2018). An automated design methodology for acoustic shells in outdoor concerts. . [Link] [PDF]
  15. Eduardo Pignatelli, Gabriele Mirra, Sergio Pone(2017). InFormer: designing forming actions in post-formed gridshells by means of MOGAs. Proceedings of IASS Annual Symposia 2017 (17) , 1–10. [Link] [PDF]
  16. Eduardo Pignatelli, Gabriele Mirra, Gabriella Lucci(2016). Computational morphogenesis and construction of an acoustic shell for outdoor chamber music. Proceedings of IASS Annual Symposia 2016 (17) , 1–10. [Link]
  17. Sergio Pone, G Mirra, E Pignatelli, D Lancia, Sofia Colabella, others(2016). Specialised algorithms for different project stages in a post-formed timber gridshell design. Proceedings of the 3rd International Conference on Structures and Architecture , 259\sck266. [Link] [PDF]
  18. Eduardo Pignatelli, Sofia Colabella, Serafino Di Rosario, Sergio Pone(2015). A wooden acoustic shell for open-air chamber music concert. Proceedings of IASS Annual Symposia 2015 (25) , 1–12. [Link] [PDF]
  19. S Di Rosario, B Parenti, E Pignatelli, G Mirra, Sergio Pone, others(2015). Res, resonant string shell, development and design of an acoustic shell for outdoor chamber music concerts.. AUDITORIUM ACOUSTICS , 354–373. [Link] [PDF]
  20. S Fotiadis, E Pignatelli, ML Valencia, C Cantwell, A Storkey, AA Bharath(2002). Comparing recurrent and convolutional neural networks for predicting wave propagation (2020). arXiv preprint arXiv . [Link] [PDF]

Experience

University College London

Assistant Professor (UK Lecturer, Teaching)

September 2024 – Present

London, UK

I teach the Data Acquisition and Processing Systems within the Integrated Machine Learning Master at UCL. The module is an introduction on how to structure a machine learning project: data acquisition using web API and sensors; data storage, SQL and noSQL databases; statistical data processing including sampling, normalisation, and linear projections; deep learning. Secondly, I am responsible for the coordination of the student’s final thesis project across the department. Finally, I supervise postgraduate students in their final projects.

Imperial College London

Research Assistant

September 2019 – November 2020

London, UK

I conducted research to shorten the computational time for predictive modelling of surgical interventions in cardiology. Statistical modelling, specifically deep learning, is central in the approach. The deep networks take advantage of accepted numerical modelling techniques to generate training data and are optimised to infer approximate solutions in about 1% of time necessary to standard models. The position was founded by the Rosetrees Trust, in collaboration with the ElectroCardioMaths program, a multidisciplinary initiative that brings together the National Heart and Lung Institute, and the Departments of Bioengineering, Aeronautics, Computing and Physics to address key challenges in the diagnosis and treatment of complex cardiac arrhythmia.

BuroHappold Engineering

Machine Learning and Decision Analytics Lead

August 2018 – October 2020

London, UK

I led the applied research in Machine Learning to help understand how AI can create value for the business. We democratised the access to Deep Learning technologies to allow every employee to access the knowledge and the tools. We exploited Visual Programming, a recognised and diffused tool for design, to create a framework that interoperates between the most common deep learning libraries, tensorflow, keras, pytorch, numpy. The position was part of the wider computational core team that brings together discipline leads into a centralised research team bhom.xyz. The BHoM is currently adopted in different companies and is at the base of the project funded by Innovate UK, github.com/aecdeltas, which I advise for.

BuroHappold Engineering

Computational/Machine Learning Engineer

August 2017 – August 2018

London, UK

For 50% of my time, I have been applying deep learning for computer vision to the analysis of security footage for the Premier League. To monitor the number of standing fans during a football match we created a database of more than 400,000 annotated images and trained a convolutional deep network to identify them. We then exploited principal component analysis, hierarchical clustering and bespoke data visualisation to gather insights from the resulting probability distribution. For the remaining 50% of my time, I have been designing a framework for data sharing and co-creation in design, for the architecture, engineering and construction industry, bhom.xyz.

We created a software-agnostic model to link together the capabilities of existing software and allow seamless interoperability between them. A short-cycles, distributed scrum development model, and an entity-component-system architecture allowed independent contributions from more than 50 users. My main responsibility has been to lead the UI and support the framework leadership of the project.

BuroHappold Engineering

Intern Computational Engineer

April 2017 – August 2017

Bath, UK

I provided computational support for the Stadia Atmosphere project and helped introduce deep learning into the current offer for sports venues design. We used pre-trained deep neural networks for Natural Language Processing to perform sentiment analysis on news regarding a specific football team.

Gianni Ranaulo Design

Architect

September 2016 – December 2016

Dubai, UAE

I provided support for the parametric modelling of a façade in a multi-purpose shopping centre.

Gridshell.it

Computational Architect

September 2015 – September 2016

Naples, Italy

I conducted research on the application of computational tools to recover the use of traditional low-tech construction techniques. I used generative modelling to provide cost-effective, environmentally efficient, and functionally viable structure. Using genetic algorithms, particle-spring system models and dynamic relaxation we designed and built 13 prototypes of timber post-formed gridshells. Taking advantage of recognised acoustic modelling techniques, we generatively designed three temporary acoustic shells for outdoor classical concerts, the last of which has won the Peter Lord Award.

Gridshell.it

Computational Architectural Assistant

July 2014 – September 2015

Naples, Italy

CRC – Constructions Restorations and Consolidations

Intern Architect

September 2012 – December 2012

Naples, Italy

I provided support for the preparation of compliance documentation for a multi-storey parking building. My main responsibility was to ensure the fire compliance of the building.