CV

Basics

Name Pehuén Moure
Label Machine Learning and Neuroscience Researcher
Email pehuen@ini.ethz.ch
Summary Researcher at the intersection of machine learning and neuroscience, specializing in developing robust AI systems that generalize across domains: from neuroprosthetic control to multi-agent robotics. Passionate on translating theoretical advances into practical solutions, demonstrated through implementations at Amazon Robotics and interdisciplinary work in visual prostheses at ETH Zurich.

Work

  • 2022.10 - Present
    PhD Candidate in Information Technology and Electrical Engineering
    ETH Zurich - Institute of Neuroinformatics
    • Developing novel deep learning approaches for controlling neural activity in visual prostheses
    • Created end-to-end optimization framework for prosthetic vision using spiking neural network
    • Built method for improving generalization in RL through regulation of Bayesian neural networks
    • Leading development on automated speech recognition tool for children with speech impairments
  • 2018.06 - 2021.10
    Data Scientist & Software Engineer
    Amazon Robotics
    • Utilized reinforcement learning policy techniques to improve sortation center throughput
    • Developed adaptive sampling evolutionary algorithm for optimizing fulfillment center maps
    • Designed and developed data compute engine and data lake using Elastic Map Reduce cluster
    • Simulated new robotic solutions and calculated impact at fulfillment centers
  • 2017.06 - 2017.08
    Strategy and Modeling Summer Analyst
    Morgan Stanley Quantitative Finance
    • Developed chat-bot assistant to facilitate traders' data processing using common language (NLP)
    • Implemented hierarchical clustering algorithm to automate trade recommendations
    • Conducted technical research for trade flow prediction based on client correlation algorithm
  • 2017.02 - 2018.05
    Chief Technology Officer
    Suna Breakfast
    • Built startup providing affordable breakfast delivery options to Cornell students
    • Directed a 20-person team in building React Native applications and backend in AWS

Education

  • 2022.10 - Present
    PhD
    ETH Zurich - Institute of Neuroinformatics
    Information Technology and Electrical Engineering
  • 2020.10 - 2022.05
    Masters of Science
    University of California Los Angeles
    Electrical and Computer Engineering
  • 2014.09 - 2018.06
    Bachelor of Science
    Cornell University
    Computer Science

Awards

Publications

2025

  1. Deep Learning-Based Control of Electrically Evoked Activity in Human Visual Cortex
    Pehuen Moure*, Jacob Granley*, Fabrizio Grani*, Leili Soo, Antonio Lozano, and 6 more authors
    Preprint at bioRxiv
    [2025]
  2. Variational Low-Rank Adaptation for Personalized Impaired Speech Recognition
    Pehuen Moure*, Niclas Pokel*, Roman Böhringer, Shih-Chii Liu, and Yingqiang Gao
    Preprint at arXiv
    [2025]
  3. Temporally-Varying Stimulations for Cortical Visual Neuroprosthetic using Spiking Neural Networks
    Pehuen Moure, Tatyana Pak, Jasper Steveninck, and Shih-Chii Liu
    In International Conference of Engineering in Medicine and Biology Society
    EMBC [2025]
  4. A Behavioral Study of Event-based Depth-Filtered Prosthetic Vision in Simulated Dynamic Environments
    Niklas Hahn, Pehuen Moure, and Shih-Chii Liu
    In International Conference of Engineering in Medicine and Biology Society
    EMBC [2025]
  5. Adaptive Neural Control with Implicit Online Inference of Privileged Parameters
    Marcin Paluch, Florian Boli, Pehuen Moure, Xiang Deng, and Tobi Delbruck
    In Learning for Dynamics and Control Conference
    L4DC [2025]
  6. Adapting Foundation Speech Recognition Models to Impaired Speech: A Semantic Re-chaining Approach for Personalization of German Speech
    Niclas Pokel, Roman Böhringer*, Yingqiang Gao*, and Pehuen Moure*
    In Disfluency in Spontaneous Speech Workshop: Interspeech
    DISS [2025]
  7. Data-Efficient ASR Personalization for Non-Normative Speech Using an Uncertainty-Based Phoneme Difficulty Score for Guided Sampling
    Niclas Pokel*, Roman Böhringer*, Yingqiang Gao*, and Pehuen Moure*
    Preprint at arXiv
    [2025]

2024

  1. Regularized Parameter Uncertainty for Improving Generalization in Reinforcement Learning
    Pehuen Moure, Longbiao Cheng, Joachim Ott, Zuowen Wang, and Shih-Chii Liu
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
    CVPR [2024]
  2. Bio-inspired parameter reuse: Exploiting inter-frame representation similarity with recurrence for accelerating temporal visual processing
    Zuowen Wang, Longbiao Cheng, Joachim Ott, Pehuen Moure, and Shih-Chii Liu
    In Proceedings of UniReps: the First Workshop on Unifying Representations in Neural Models
    NeurIPS [2024]
  3. DeltaDEQ: Exploiting Heterogeneous Convergence for Accelerating Deep Equilibrium Iterations
    Zuowen Wang, Longbiao Cheng, Pehuen Moure, Niklas Hahn, and Shih-Chii Liu
    In Neural Information Processing Systems
    NeurIPS [2024]

2021

  1. A Computational Design and Evaluation Tool for 3D Structures with Planar Surfaces
    Chang Liu, Wenzhong Yan, Pehuen Moure, Cody Fan, and Ankur Mehta
    In International Conference on Robotics and Automation
    ICRA [2021]

2018

  1. Can Interactive Systems Be Designed for Conviviality? A Case Study
    Marc Choueiri, Schuyler Duffy, Sanjay Guria, Conrad McCarthy, Pehuen Moure, and 4 more authors
    In Proceedings of the 2018 ACM Conference Companion Publication on Designing Interactive Systems
    DIS [2018]

Volunteer

  • 2019.09 - 2020.08
    Pediatric Oncology Research Assistant
    Dana Farber Cancer Institute
    • Developed pipeline for automating analysis of chip-seq and RNA-seq data
    • Interacted with team of scientists to build tools that speed up production of results

Skills

Machine Learning
Reinforcement Learning
Deep Neural Networks
Bayesian Neural Networks
Computer Vision
Software Engineering
Python
AWS
Agile Development
ROS

Languages

English
Fluent
Spanish
Native

Projects

  • 2024.01 - 2024.06
    Speech Recognition for Children with Speech Impairments
    Developed tool for improving speech recognition accuracy in children with speech impairments
    • Implemented Whisper model with bayesian mechanism to improve accuracy on small datasets
    • Coordinated team of 5 students to develop tool for real-time speech recognition
  • 2016.07 - 2018.08
    Autonomous Bicycle Project
    Co-founded and led software team for autonomous bicycle development
    • Built object avoidance system using SLAM algorithm in ROS with TX-1 and ZED stereo camera
    • Managed team of 12 students working to create centralized code structure across 4 sub-teams