CV

PhD in Electrical and Computer Engineering

• Advisor: Prof. Kaushik Roy.
• Research Topic: hardware-software co-design for brain-inspired AI systems.
• GPA: 3.9.

BS in Electronics Engineering

• GPA: 3.5.
• Rank: 3/28.

Postdoctoral Researcher

• Advisor: Prof. Charlotte Frenkel.
• Research on hardware-algorithm co-design for NeuroAI.

Graduate Research Assistant

• Advisor: Prof. Kaushik Roy.
• Conduct research on neuro-inspired machine learning algorithms for emerging hardware technologies, with emphasis on scalability and energy efficiency in neuromorphic systems.
• Developed CODE-CL, a continual learning framework using conceptor-based gradient projection, enabling knowledge retention and forward transfer in sequential tasks.
• Designed an ADC-less in-memory computing hardware for Spiking Neural Networks, achieving 2–7× energy savings and 9–24× latency reduction over conventional architectures through HW/SW co-design.
• Proposed novel spatial, temporal, and fully local learning rules (LLS, S-TLLR, TESS), inspired by biologically plausible mechanisms such as STDP, synchronization, and eligibility traces; matched backpropagation performance at significantly lower computational cost.

Visiting Researcher

• Advisor: Prof. Charlotte Frenkel.
• Conducted a three-month research visit on custom digital hardware accelerators for on-device learning using local learning rules in artificial neural networks, supported by the NSF AccelNet NeuroPAC Fellowship.

Systems Engineering Intern

• Conducted research into hardware-aware neural architecture and quantization search, leveraging evolutionary optimization algorithms to facilitate the deployment of deep learning models on low-power devices. Achieved a 10x reduction in model search time and a 5% increase in model performance for keyword spotting tasks.

Research Assistant in Computer Vision

• Developed energy-efficient machine learning models for diverse applications, including timber species identification, underwater acoustic inversion, satellite cloud segmentation, and river level estimation.
• Integrated ML algorithms into low-power embedded systems, enabling real-time inference for precision agriculture applications.
• Designed a lightweight CNN achieving >90% accuracy in timber species recognition under open-set conditions.
• Secured three software copyrights in remote sensing and health monitoring.
• Published one journal paper and three conference papers.

Best Student Paper Award, WACV 2026

• Awarded for "Feedback Alignment Meets Low-Rank Manifolds -- A Structured Recipe for Local Learning" in the algorithms track of IEEE/CVF WACV 2026.

NSF AccelNet NeuroPAC Fellowship

• Selective international fellowship supporting cross-border collaborations in neuromorphic computing; awarded to conduct research on digital on-chip learning hardware accelerators at TU Delft.

Graduate Peruvian Fellowship "Beca Generacion del Bicentenario"

• Prestigious national fellowship fully funded by the Peruvian Ministry of Education; awarded to top scholars across Peru to pursue graduate studies abroad.

Julio Urbina Arias Award

• Recognition for outstanding research and leadership contributions as an active member of the IEEE Student Branch, National University of Engineering, Lima, Peru.

SM-GROVER

• Geo-referenced monitoring system for COVID-19 with virtual assistant and respiratory-rate estimation. Software IP registration, INDECOPI 00376-2022. Co-developer.

SINIM-1

• Cloud identification in multispectral satellite imagery. Software IP registration, INDECOPI 00740-2021. Co-developer.

KASPI

• Mobile application for identification of Peruvian timber species. Software IP registration, INDECOPI 00294-2021. Co-developer.

Instructor, Short Course on Digital Image Processing (24 hours)

• Designed and delivered a 24-hour short course on digital image processing for early-career engineers and students.

Workshop Instructor, IEEE Student Branch

• Taught hands-on workshops on signal and image processing and introductory machine learning for undergraduate audiences as part of the IEEE Signal Processing Society and Robotics & Automation Society student chapters.

Mentor, Talento Guía (PRONABEC, Peru National Scholarship Program)

• Mentor for incoming Peruvian graduate students abroad (Beca Generación del Bicentenario Fellows), providing academic, cultural, and professional guidance for their transition to international graduate programs.

Mentor, Serendipity: Mentorship in Science Program

• Mentored Peruvian undergraduate students in STEM on career development, research opportunities, and pathways to graduate school.

Speaker - STEM Outreach

• Invited speaker at IEEE and university events in Peru, promoting undergraduate research and STEM engagement.

Vice Chair, IEEE Signal Processing Society Student Chapter

• Co-founded the first IEEE Signal Processing Society Student Chapter in Peru; promoted undergraduate-led research projects in signal and image processing.

Research Director, IEEE Robotics and Automation Society Student Chapter

• Led student research groups in robotics and computer vision; organized national robotics competitions, technical talks, and workshops.

LatinX in AI (LXAI) Travel Grant - NeurIPS

• Competitively awarded grant supporting participation and presentation at the LatinX in AI Research Workshop co-located with NeurIPS.

ICCV Broadening Participation Travel Grant

• Awarded for conference participation based on scientific contribution, need, and commitment to broadening participation within the ICCV community.

Energy-Efficient Brain-Inspired Learning in Deep Neural Networks

Local Learning for Deep Neural Networks

Neuromodulation on Brain and Machines

Hardware/Software Co-design with ADC-Less In-Memory Computing for SNNs

Enabling High-Performance ADC-Less In-Memory Computing for Deploying SNNs Through Hardware-Aware Training

Experiencia estudiando un posgrado en EEUU - Becas y oportunidades

Interview in APTC La Revista (magazine of the Peruvian Telecommunications Association)

• "El cerebro humano es la computadora más eficiente" ["The human brain is the most efficient computer"].

Telluride Neuromorphic Cognition Engineering Workshop

• Highly selective international workshop; hands-on projects on neuromodulation mechanisms for synaptic plasticity and reinforcement learning.

SRC TECHCON

• Semiconductor Research Corporation's flagship annual conference, Austin, TX, engaging with industry leaders on advances in semiconductor and AI research.

Neuromatch Academy - Computational Neuroscience Summer School

• Intensive online summer school on computational neuroscience, exploring parallels between artificial neural networks and in-vivo brain responses to visual stimuli.