Multidisciplinary Software & Systems Engineer

I build secure, high-performance systems across AI, infrastructure, and hardware.

I work across distributed systems, security engineering, AI/ML infrastructure, performance engineering, and hardware/software integration. My work spans Java, Python, Rust, C/C++, Linux, cloud-native services, AI evaluation, post-quantum security, and physical computing systems.

Philadelphia, PA · U.S. Permanent Resident · No employment sponsorship required.
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Featured engineering work

Proof across the stack.

These case studies show how I move between distributed infrastructure, security, AI systems, performance engineering, and hardware/software boundaries without treating them as separate worlds.

Research systemPublic repository

Quantum Entropy-as-a-Service

A secure distributed service exposing hardware-generated quantum entropy to authenticated clients while measuring security, concurrency, and performance trade-offs.

IoT Client→Axum / Tokio API→QRNG
Signed Requests+Replay Defense+PQC

What I owned

I defined the service architecture from NIST guidance and physical QRNG constraints, evaluated C, Go, and Rust, and selected Rust based on measured engineering and performance trade-offs.

What I built

  • Authenticated Axum/Tokio APIs with signed requests, nonces, replay protection, rate limiting, quotas, and freshness controls.
  • Kyber/Dilithium post-quantum identity workflows through liboqs.
  • Direct QRNG, hybrid CSPRNG, and parallel delivery modes with benchmark clients for latency and concurrency analysis.
  • An eight-shard Rust entropy pool that reduced representative request latency from 3,053 to 2,615 microseconds at concurrency 10.
  • Deployment workarounds around legacy Linux drivers, kernel compatibility, and physical PCIe hardware constraints.
~14%Latency reduction
8 shardsIn-process entropy pool
RustAxum · Tokio
View repositoryResearch context
Active developmentPrivate repository

Amealia AI Platform

An AI-powered nutrition platform connecting mobile product flows, Java services, PostgreSQL data models, and a dedicated AI recommendation layer.

React Native / Expo→Spring Boot
PostgreSQL↔Spring Data JPA
Spring Boot↔FastAPI AI Engine

My role

Co-Founder & Lead Software Engineer. I help lead a six-person team across design, frontend, backend, AI, QA, and business while remaining hands-on across architecture, APIs, integration, evaluation, testing, and technical reviews.

What I built

  • Cross-service workflows across React Native/Expo, Java 21 Spring Boot, PostgreSQL, and FastAPI AI services.
  • REST APIs for authentication, onboarding, meal planning, feedback, recipe swaps, grocery lists, and recommendations.
  • An automated AI evaluation harness with 29 passing tests to catch model and recommendation regressions before release.
  • API testing practices covering authentication, contract validation, negative cases, smoke tests, and regression behavior.
29 testsAI evaluation harness
6 peopleCross-functional team
4 layersMobile · API · Data · AI
Request a walkthroughDiscuss the architecture
Performance studyPublic repository

Parallel & Heterogeneous Image Processing

A CPU/GPU performance study comparing sequential, multithreaded, multiprocessing, and CUDA-accelerated image-processing pipelines.

Sequential CPU↔Threads↔Processes
CPU↔CUDA / GPU

Engineering question

When does adding parallelism or GPU acceleration actually improve a pipeline, and when do scheduling, synchronization, transfer, and launch overhead erase the expected gain?

What I evaluated

  • Runtime, throughput, worker scaling, CPU behavior, synchronization overhead, and workload partitioning.
  • GPU inefficiencies caused by kernel-launch overhead, repeated host-device transfers, and low compute intensity.
  • Parallel speedup limits using Amdahl’s Law and the effect of serial work on scaling.
  • Optimization directions including batching, kernel fusion, vectorization, and reducing transfer/launch overhead.
4 modesSequential · threads · processes · GPU
CUDAHeterogeneous compute
AmdahlScaling analysis
View repository
Hardware/security researchPublic repository

FPGA / QRNG Security Research

Hardware/software research around quantum-randomness post-processing, statistical validation, and secure key-generation workflows.

QRNG / Simulated Source→FPGA Conditioning
VHDL→Validation Tooling→Security Analysis

Cross-layer focus

This work connects hardware description, physical randomness, statistical validation, systems software, and secure-computing requirements.

What I built and analyzed

  • VHDL-based post-processing components and testbenches for randomness-processing workflows.
  • Python and shell-based statistical validation and analysis tooling.
  • Entropy-quality and randomness evaluation for secure-system applications.
  • FPGA-based QRNG conditioning and cryptographic key-generation architecture concepts.
View repositoryResearch profile
Additional work

More evidence, different layers.

Additional projects across machine learning, Java security architecture, trusted computing, computer vision, and product engineering.

Python · BERT · ResNet

Multimodal Classification

Built text and image pipelines spanning preprocessing, feature extraction, embeddings, multimodal fusion, training, and quantitative evaluation.

Java 21 · Spring Boot · Security

QRNG-Backed Authentication

Built layered controller, service, adapter, and DTO boundaries integrating hardware-backed entropy into OTP identity workflows.

Trusted Computing · IoT Security

Quantum Trusted Platform Module

Contributed research code and datasets connecting QRNG hardware, trusted-computing concepts, and secure IoT workflows.

Django · OpenCV · jQuery

Warehouse Monitoring

Integrated camera APIs and OpenCV/Python workflows into database-backed warehouse and inventory software.

React · TypeScript · APIs

Reusable Product Interfaces

Built tested React and React Native components, documented them in Storybook, and coordinated frontend/backend API behavior.

React · API Data · Charts

Campaign Monitoring Dashboard

Integrated the PropellerAds API with React and Google Charts to deliver near-real-time campaign status and performance views.

Engineering strengths

One foundation, multiple layers.

I am most useful on problems that cross boundaries: application to infrastructure, software to hardware, performance to security, or research to production.

Systems & performance

Distributed systems, Linux, Rust/C/C++, concurrency, async systems, benchmarking, profiling, CPU/GPU analysis, and PCIe integration.

Security engineering

Authentication, signed requests, replay defenses, rate limiting, Zero Trust, post-quantum cryptography, secure APIs, and threat-driven design.

AI & product systems

AI evaluation, FastAPI services, Java/Spring platforms, PostgreSQL, multimodal ML, API contracts, testing, and product integration.

Cross-layer systems

Computer architecture, RISC-V, SystemVerilog/VHDL, FPGA, networking, embedded concepts, frontend/backend contracts, and hardware/software boundaries.

Selected experience

Engineering, research, and technical leadership.

My experience spans startup product development, secure distributed systems research, university teaching, full-stack delivery, and hardware/software experimentation.

Co-Founder & Lead Software Engineer
Amealia AI
2026 – Present

Lead cross-functional engineering across Java/Spring Boot, PostgreSQL, FastAPI AI services, React Native, product integration, AI evaluation, API testing, technical reviews, and mentoring.

Research Associate
Morgan State University
Jan 2025 – Present

Rust distributed services, authenticated APIs, PQC, Linux/PCIe integration, concurrency, performance engineering, Zero Trust research, and benchmark-driven architecture.

Adjunct Professor — Computer Science
Morgan State University
Dec 2024 – May 2026

Taught Python, OOP, data structures and algorithms, computer architecture, RISC-V, SystemVerilog, debugging, and systems reasoning across multiple course sections.

Research Assistant — Secure Computing & Hardware Validation
Morgan State University
Jan 2023 – Dec 2024

Linux QRNG integration, NIST SP 800-22 validation, statistical analysis, research software, hardware benchmarking, and trusted-computing/IoT experiments.

Frontend Software Engineer / Team Lead
Hanspet Technologies
Nov 2021 – Aug 2022

React, React Native, TypeScript, Jest, Storybook, reusable components, code reviews, mentoring, and frontend/backend integration.

Junior Software Engineer
Mul-T-Lock Nigeria Ltd.
Feb 2021 – Jun 2021

Django, jQuery, camera APIs, OpenCV/Python, database-backed inventory workflows, debugging, and application integration.

Research crossover

Research that sharpens systems engineering.

My academic work strengthens how I reason about trust boundaries, cryptographic systems, failure modes, experimental design, performance measurement, and hardware/software constraints.

Current research direction

I am pursuing a Ph.D. in Advanced and Equitable Computing at Morgan State University. My qualifying proposal, Trust as a Systems Resource: A QEaaS-Backed Trust Architecture for Post-Quantum, TEE-Based Distributed Systems, explores how trust, attestation freshness, and cryptographic resources can become explicit runtime concerns in distributed infrastructure.

Google ScholarDiscuss my research
Developing Quantum Trusted Platform Module to Advance IoT SecurityFuture Internet, 2025 Representative CPS Application DomainsAcademic Press, 2025 Comparative Analysis and Applications of Quantum Random Number GeneratorsMaster’s thesis, 2024
Let’s build something difficult

Systems that are secure, fast, and useful.

I am open to full-time opportunities across systems and infrastructure, security engineering, AI/ML systems, platform/backend engineering, research engineering, and forward-deployed engineering. I am authorized to work in the United States without employment sponsorship.

Email me LinkedIn GitHub