Mansoor Mamnoon

B.A. Computer Science — EECS Honors Program  ·  GPA 3.973

Selected coursework: Operating Systems (162) · Compilers (164) · Database Systems (186) · Algorithms (170) · Machine Learning (189) · Optimization (EECS 127) · Computer Vision (180) · Probability (Data 140) · Abstract Linear Algebra (Math H110)

Software Engineering Intern — Traffic Platform

• Developing dynamic network interface attachment for GCP-provisioned VMs, enabling transparent enforcement of customer network isolation guarantees across multi-tenant cloud infrastructure.
• Implementing cloud provider integrations within an internal network control plane, interfacing with service network layers to maintain workload boundary semantics at scale.
• Designed and validated a proof-of-concept by manually provisioning and configuring VMs end-to-end, confirming architectural feasibility before full implementation.
• Collaborating with senior infrastructure engineers on architecture design, presenting implementation plans for review prior to development.

Go · Rust · GCP · Network Control Plane · Virtual Machines · Multi-tenant Infrastructure

Undergraduate Researcher

• Working with postdoctoral researchers on extensions to Robo-DM, a data management toolkit for large-scale robot learning datasets (affiliated with UC Berkeley AUTOLab / BAIR).
• Exploring efficient dataset compression, retrieval, and integration with ML training pipelines.
• Applying prior experience in real-time event pipelines to robotics data loading and systems optimization.

Python · PyTorch · Data Engineering · Robot Learning

Software Development Engineer Intern — Backend & Distributed Systems

• Architected and shipped an end-to-end, real-time occupancy monitoring platform — from ingesting live data from 100+ IoT sensors to frontend visualization — piloted across 4 Amazon buildings.
• Built a scalable, fault-tolerant backend pipeline using AWS Lambda, SQS, DynamoDB, and Timestream, processing 10K+ streaming events/min with P99 latency < 900ms.
• Automated multi-region deployment workflows via AWS CDK (TypeScript), cutting infrastructure provisioning time by 85% and enabling horizontal scaling under peak load.
• Engineered a real-time React dashboard with live occupancy visualizations (<1s data freshness), enabling operations teams to monitor usage across facilities in real time.
• Integrated CloudWatch logs, alarms, and metrics dashboards, reducing debugging time by ~40% during integration tests.
• Authored a detailed design document and executive one-pager; presented and reviewed with a panel of SDE2s and SDE3s during design review cycles.

TypeScript · AWS Lambda · ECS Fargate · DynamoDB · SQS · Timestream · CDK · React · CloudWatch

Software Engineering Intern

• Engineered a scraping and ranking system using Python, Beautiful Soup, and pandas, optimized via custom trie-based prefix matching and vectorized scoring — reducing runtime by 5× across 200+ client profiles.
• Designed a weighted lead ranking algorithm scoring prospects on post frequency, keyword density, and engagement signals, enabling automated prioritization in outreach workflows.
• A/B tested targeted outreach across Apollo CRM, LinkedIn, and email, improving contact conversion by 25% and pipelining feedback into internal analytics dashboards.
• Built a reusable data ingestion module and led documentation and interface design for intern handoff.
• Delivered live technical demos at SF Tech Week to 40+ clients, collecting real-time user feedback.

Python · Beautiful Soup · pandas · Apollo CRM · Data Pipelines

eBPF VXLAN MTU Blackhole Diagnostic Tool

• Built an eBPF-based CLI in Go + C that diagnoses silent VXLAN packet-drop bugs caused by MTU mismatches — a class of issue that is invisible to standard tooling and common in k3s/Flannel and Calico deployments.
• Implemented 4 BPF programs (TC sched_cls ingress/egress + kprobes on icmp_rcv and ip_do_fragment) producing 6 diagnostic verdicts; TC attach/detach is identity-verified and rollback-safe on error.
• Shipped interfaces and collect-environment subcommands; packaged arm64 + amd64 binaries; 41/41 qualification gates PASS on Linux 5.15 kernel (Ubuntu 22.04).

Go · C · eBPF · Linux TC · kprobes · cilium/ebpf · netlink

MCP Security Proxy — Prompt Injection Defense

• Built a four-layer signal pipeline: heuristic denylist, hashed feature vectors for semantic drift detection (no external model, sub-ms), taint-aware capability gating, and document instruction density scoring.
• Self-play red-team pipeline generates 500+ adaptive attacks across 7 classes via a 3-round mutation loop; reduced attack success rate from 100% to 16% on local eval suite of 4,200+ cases (vs. no-filter baseline).
• Threshold calibration via FPR-constrained sweep holds false positive rate to 8.3%. 783 tests. p95 latency < 1ms.

Python · FastAPI · MCP Protocol · NumPy · pytest

Exchange-Style High-Frequency Matching Engine

• Built a C++20 matching engine with intrusive FIFOs, slab allocators, and cache-hot ladders, achieving 20M+ msgs/sec throughput with sub-µs median latency; validated determinism via snapshot/resume replay proof with bit-for-bit fill equivalence.
• Designed an end-to-end analytics + backtesting pipeline (Python, Parquet, Docker, Streamlit) to replay real Binance BTCUSDT data, compute microstructure metrics (spread, microprice, volatility, impact curves, order-flow autocorr), and evaluate VWAP/TWAP/POV/Iceberg strategies with reproducible PnL & risk metrics.

C++20 · Python · Docker · Streamlit · GitHub Actions

Custom Reinforcement Learning System for Latency-Constrained Deployment

• Developed a custom Gym environment with dual observation channels and delayed reward functions, simulating high-dimensional control tasks with ~10⁵ state transitions per training run.
• Implemented an offline RL training pipeline in PyTorch, featuring a prioritized replay buffer (α=0.6, β=0.4), batch reward normalization, and dynamic ε-greedy exploration — achieving ~92% average reward recovery from expert trajectories.
• Benchmarked Conservative Q-Learning (CQL) and DQN across 8 random seeds, analyzing variance, convergence speed, and sample efficiency; achieved ~30% lower regret compared to baseline DQN under identical rollout constraints.

PyTorch · OpenAI Gym · NumPy · TensorBoard

Multi-Cloud Serverless IDE

• Engineered a desktop IDE using Electron, React, and TypeScript to deploy serverless APIs across AWS Lambda@Edge, Cloudflare Workers, and Vercel Functions via one-click multi-cloud workflows.
• Integrated infrastructure-as-code (IaC) generation using Terraform, dynamic configuration, and live preview via Monaco Editor — enabling production-grade deployments with zero CLI interaction.
• Designed a fully offline-compatible build pipeline, benchmarked to support 1K+ concurrent requests/sec, simulating cold-start behavior and cross-cloud latency tradeoffs in edge environments.

Electron · React · TypeScript · Pulumi · Terraform · Monaco Editor

Senior Mentor & Content Lead — Computer Science Mentors

• Authored weekly worksheets covering RISC-V assembly, C, memory hierarchy, caching, pipelining, and parallelism for 300+ students.
• Led small-group sections and office hours; promoted to Content Lead (Dec 2025) to drive curriculum development.

RISC-V · C · Memory Hierarchy · Pipelining · OpenMP

Course Tutor

• Led weekly tutoring groups (7 students each), hosted lab sessions for 40+ students, and held office hours serving 300+ enrolled students.
• Contributed to a library of instructional videos based on past exams; achieved above-average feedback ratings.

Python · NumPy · pandas · Statistical Analysis

Selective academic honors track recognizing top-performing CS students. Includes advanced coursework, research components, and honors thesis option.

Judged and awarded by Intuit product marketing leadership for a go-to-market proposal targeting SMBs and solopreneurs.

Qualified from 74,000+ Senior Math Challenge participants. A* in Further Mathematics A-Level.