Ernesto Sola-Thomas

Designed a custom processor based on the open-source RISC-V architecture to create an interactive calculator with hardware-accelerated mathematical operations on the Basys 3 FPGA board.

• Developed a fully functional calculator performing addition, subtraction, multiplication, and division operations with custom hardware acceleration.
• Gained extensive experience in logic architecture design and decision-making within processor customization.
• Implemented comprehensive verification using Universal Verification Environment (UVM) to ensure RTL performance met project specifications.
• Successfully integrated custom firmware to drive peripherals including switches, push buttons, and 7-segment displays.

Developed a smart wheelchair customized from a commercially available manual chair, featuring dual control modes with joystick navigation and hands-free autonomous routing through indoor environments.

• Created low-cost, lightweight solution accessible to broader user base beyond wealthy demographics.
• Demonstrated autonomous navigation through indoor hospital facilities and general indoor locations.
• Published open-source design files enabling public reproduction and broader accessibility.
• Provided dual control options with manual joystick and hands-free autonomous navigation.

Designed an Ultra-Low-Power Smart Wearable Multisensory Stereo Camera system with AI-enabled capabilities for blind navigation, featuring dual 5MP cameras and onboard neural network processing.

• Published at IEEE SoutheastCon 2021 with complete open-source design for reproduction by researchers.
• Achieved time-synchronized stereo capture with onboard object detection and image recognition.
• Implemented distributed processing architecture with machine learning core offloading decision tree classification.
• Contributed to open-source blind navigation system development with complete schematic and layout files.

Developed a prosthetic hand powered by EMG sensors, translating muscle intent into multi-grip actuation.

• Provided customizable grip profiles for diverse users.
• Highlighted the potential of biofeedback loops in assistive tech.

Built an electronic piano using 555 timers to generate tuned oscillations—training the ear and hand in circuit design.

• Deepened intuition for timing circuits and harmonics.
• Inspired later work exploring signal processing and music tech.

Science fair project combining electrolysis and electronics to detect water quality after discovering algae in the school supply.

• Delivered actionable insights to administrators on water infrastructure upkeep.
• Built confidence in translating lab discoveries into real-world instruments.

Built GPU-accelerated Monte Carlo simulations in Python to model portfolio risk and derivative pricing scenarios.

• Delivered 40x speed-ups vs. CPU baselines for client prototypes.
• Equipped stakeholders with faster decision support dashboards.

Orchestrated Django, Supabase, and Stripe ecosystems with Dockerized deployment across Azure Kubernetes Service and Cloudflare.

• Delivered reliable billing and auth flows for multi-tenant applications.
• Automated build and release pipelines, enabling weekly iteration with confidence.

My first shipped app—an early iOS calculator built in Xcode that sharpened product intuition and event-driven thinking.

• Sparked a lifelong habit of building and shipping personal tools.
• Established an experimentation mindset that carries through larger systems today.

Building reusable verification environments and analytics to accelerate AI accelerator bring-up and coverage closure.

• Reduced test debug time through targeted stimulus and health dashboards.
• Improved confidence in floating point paths for production delivery.

Enhanced emotion recognition accuracy using wearable electrocardiogram (ECG) data and machine learning models to classify emotions across valence, arousal, and dominance dimensions.

• Demonstrated superior performance of random forests with carefully selected ECG features for emotion classification.
• Advanced feature engineering techniques for physiological emotion recognition systems.
• Contributed to personalized mental health monitoring and human-computer interaction applications.
• Established framework for real-time emotion detection using wearable ECG devices.

Implemented vision-based automated control for prosthetic hands using FPGA processors, featuring an RGB camera interfaced to Zynq UltraScale+ MPSoC with object detection deep learning models.

• Addressed high-power consumption limitations in sophisticated robotics through power-efficient FPGA implementation.
• Developed advanced image processing pipeline from scratch for prosthetic hand applications.
• Created publicly available repository with thorough implementation documentation.
• Enabled vision sensors to artificially sense objects from wrist position for sophisticated grabbing control.