Kavishka Bartlett

- Building a compiler for neural-atom quantum computers that maps quantum circuits onto actual hardware, models qubit movement and scheduling constraints, and estimates runtime by predicting delays - Simulating how large quantum programs execute on physical hardware to identify bottlenecks and optimize architecture design

- Building a research publishing platform using game-theory to overhaul current incentives and directly reward rigorous peer review, replication, and rectification - Designing, training, and deploying ML models to classify papers, score author contributions, quantify peer-review impact, and optimize user searching

- Collaborating with Duke, USC, and NASA researchers to replace ~72-hour CFD simulation with relatively instant AI/neural network predictions, improving runtimes by over ~1,000,000x in high dimensional fluid flow modeling - Coded custom CFD Solver (20+ files) and diffusion models to generate large, tailored datasets for training ML-based surrogate models - Programmed performance-portable parallelism (using CUDA, Kokkos, MPI) in CFD code, accelerated simulation runtime by ~100x - Currently parallelizing Duke Aeroelasticity CFD code running on High Performance Clusters - Analyzing viability of physics-informed neural networks, surrogate models, operator networks, and a combinations of all 3 to replace CFD code - Targeting paper publication and presentation at 2026 NASA High Fidelity CFD Workshop at Lockheed Martin’s Center of Innovation

- Built local LLM system to analyze natural-language requests, query company database (AS/400), evaluate results, and present non-technical teams with live reports (Python) - Developed security protocols to prevent data leaks and ensure compliance with government contracts Traveled to other divisions, analyzing workflows, identifying inefficiencies, and both proposing and implementing solutions. Projects Include: - Bill of Materials (BOM) Mapping: Automated the process of engineers manually parsing through 100,000+ page aircraft BOMs to find specific part numbers, assembly instructions, quantities, etc. enabling executives to identify product and market opportunities while cutting an ~80 hour weekly process down to minutes - Bearing Identifier System - Tool allowing Sales to input customer requirements and instantly retrieve matching RBC parts, eliminating need to consult engineers, saving ~12 hours per week - Automating Reports: Built fully automated pipelines (database processing, file retrieval, and email delivery) for manual sales, engineering, and process reports (4), saving 3 hours per week per report - AI Integration: After attending Google GenAI at Work conference in LA, I traveled to RBC divisions giving presentations on how to practically implement AI in the workday

- Built plant inspection system by integrating 100+ gauging instruments with database (SQL), translating raw measurement data into intuitive metrics, and presenting them to executives via dashboards (Ignition) - Created custom tooling models in Solidworks for highly specialized and precise aerospace bearings - Coded, troubleshoot, and handled daily set-up for 12 Fanuc robots - Developed distinct equipment and programs for testing flight-critical bearing characteristics (torque, load capacity, friction, surface finish, dimensional accuracy)

-Worked at the register in Old Navy and Banana Republic as a summer job -Became lead cashier after breaking the record for most Old-Navy credit card sign-ups in my second week - Won employee of the week numerous times

- Founded SOS Tutoring LLC to connect high school tutors and clients seeking affordable classes - Built company awareness through marketing (designing logo, website, business cards, pens, flyers) - Developed financial strategies through optimized pricing and dynamic tutor - Created scheduling algorithms to optimize the tutor-student pairing process - Handled tutoring operations during Covid-19 by researching and using various virtual tools

- Courses in Mathematical Finance, Financial Derivatives, Probability, Quantum Computing, Space System Design, AI/ML in CFD, PINN & Surrogate Model Analysis, Proof-Based Engineering Math (Linear, Differential Equations, etc.)

Selected as one of two undergraduates in USC FOCEX’s 42-member team of PhD students and professors focused on improving computation fluid dynamic modeling using parallelism, optimization, and neural networks Worked with the following: - NVIDIA CUDA Programming: Coded to allow vectorized calculations on NVIDIA GPUs - C++ Kokkos Library: Used to allow performance portable programming, ie, code will work on GPUs, CPU, clusters, hybrid models, etc. - Open MPI: Coded programs to run on HPC clusters, enabling parallelization and communication across multiple independent CPUs - Gradient Descent Optimization: Implemented iterative routines to minimize loss functions, creating ideal weights for neural networks - Unstructured Grid Generation: Used Delaunay Triangulation algorithms to generate unstructured grids for complex geometries, allowing for higher accuracy in real-world fluid flow modeling

- Studied abroad in first semester junior year - Enrolled in various clubs, classes, and events - Spent majority of time traveling and experiencing Australia, Vietnam, Thailand, New Zealand, and Laos among other

-Graduated with an IB diploma and an AP Scholar with Distinction certificate -Wrote a research paper on quantum mechanics, parallel universes and the effects of their inaccurate portrayals in modern movies on public perception -Wrote a paper on the extent of objectiveness in the production and acquisition of knowledge -Awards of excellence in math (2), chemistry (1), music (3), and history (1)

-One of only 4 eighth graders invited to participate in the Symphony, the highest of all 3 orchestras and typically reserved for 9-12 graders -Participated in weekly workshops, sectionals, and music theory -Club Tennis -Played in the 7/8 grade orchestra