Vetted Research Assistants

“Robotics engineer who built a smart campus tour robot on a Kobuki Turtlebot using ROS 1, implementing a full navigation stack (semantic world model, A* planner, tour executor, path follower) and integrating SLAM (gmapping) plus a hybrid reactive safety controller. Experienced taking systems from Gazebo simulation to real hardware, including extensive real-world debugging and Docker-based development to handle ROS/Ubuntu version constraints; planning a move to ROS 2 on Turtlebot 4.”

“Robotics/perception engineer who led and owned ARC, a cooperative perception system for autonomous vehicles that aligns and fuses multi-vehicle LiDAR point clouds in real time. Built a ROS-based multi-node pipeline with grid-based spatial reasoning and motion-compensated data sharing, achieving <20 ms compute latency and sub-7 cm alignment error; accepted to ACM SenSys 2026.”

“Frontend engineer who led Bentley’s flagship design system from a greenfield codebase to adoption across every major Bentley product, emphasizing maintainability and high UX polish. Built complex React+TypeScript interfaces like a Figma/Photoshop-style layers tree, applying advanced performance techniques (skeleton-first loading, transitions, memoization, deferred rendering) and iterative feature-flagged rollouts driven by user feedback.”

“Graduate researcher who builds production-grade AI systems spanning LLM security evaluation and on-device RAG. Created HoneyLearner, a self-learning attack framework using GPT-4-class models as structured black-box attackers against honeywords defenses, with rigorous metrics and reproducible orchestration (Airflow/Spark/Kafka/Docker). Also partnered with agriculture scientists at Texas A&M–Corpus Christi to deliver UAV + 3D point-cloud crop-stress maps that cut time-to-insight ~40% and enabled ~30% earlier interventions.”

“Backend/DevX engineer with startup experience who built internal JavaScript SDKs for POS integrations, including a daily GMV calculation feature standardized across multiple POS providers. Strong in performance debugging (used Jaeger to resolve legacy WebSocket bottlenecks) and developer enablement—built a cronjob migration tool (ArgoWorkflow to internal platform) with documentation that let teams migrate in ~30 seconds, plus handled on-call and internal support.”

“Defense-domain AI engineer who built a production ReAct-style RAG system for military training data/material generation, scaling to ~1000 users and cutting generation time by 50%. Also has experience designing GPU-cluster parallel computation with PyTorch and handling production incidents involving database performance and schema design.”

“Enterprise customer success/implementation leader focused on AI-driven operational intelligence deployments in complex environments (e.g., large international airports). Has led end-to-end rollouts across 1200+ camera feeds and multiple airport systems, driving adoption stabilization within 90 days, influencing product roadmap (configurable alerts), and partnering with Sales to expand from initial congestion monitoring into additional operational modules.”