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General Information

Full Name Camille Dunning
Date of Birth 19th June 2001
Languages English

Education

  • 2023
    B.S. in Data Science
    University of California, San Diego
    • Coursework in probabilistic modeling, computer vision, differential equations, deep learning for NLP, statistical methods, data visualization, databases, systems for scalable analytics, data structures and algorithms, graph theory, mathematical reasoning.

Experience

  • 2023
    Data Science Intern
    Tesla, Fremont, CA
    • Quality Data Engineering team.
  • 2022 - 2023
    Undergraduate Researcher
    Existential Robotics Lab, UC San Diego, La Jolla, CA
    • Inverse reinforcement learning with tacto_learn, stable_baselines3, robosuite, OpenAI mujoco physics engine.
  • 2022 - 2023
    Undergraduate Researcher
    Cool Star Lab, UC San Diego, La Jolla, CA
    • Working on classifying spectral binaries in large database of brown dwarfs, and using multi-label classification to decompose known and synthetic spectral binaries into primary and secondary types.
    • Evaluating performance of tree-based models by system/spectral type and signal-to-noise ratio. Streamlined scikit-learn model spot-checking with PyCaret.
    • First-author research note published to RNAAS, working on full first-author paper to publish.
  • 2022
    Computer Vision Intern
    NVIDIA, Santa Clara, CA
    • Created synthetic dataset for semantic segmentation, and object generation using NVIDIA Omniverse Replicator, based on real objects reconstructed with NVIDIA Instant NeRF.
    • Engineered a production-ready transfer learning pipeline using NVIDIA TAO that trains a YOLO-v4 ResNet model on the synthetic dataset for CV task.
    • Presented solution to NVIDIA Solution Architects, official blog in the process of being published to NVIDIA's Developer Blog and Medium.
  • 2022
    Software Engineering Intern (Security)
    Salesforce, San Francisco, CA
    • Wrote string-matching rules in YARA to detect phishing in applications deployed to Heroku.
    • Tested rules in real-time canary state, analyzed causes of false positives chosen from Splunk logs.
    • Helped team decide feasibility of brand-based, as opposed to actor-based approach when writing phishing detection scripts.
  • 2022
    Deep Learning Intern
    San Diego Supercomputer Center, La Jolla, CA
    • Machine learning for cyber-infrastructure (Voyager and Expanse supercomputers).
    • Prototyping VGG and MobileNet models on image datasets in data-parallel multi-GPU environment using PyTorch Lightning and CUDA.
  • 2021
    Co-Founder & CTO
    Cluvii, La Jolla, CA
    • Served as core backend framework and AI developer to up-and-coming mobile app.
    • Brainstormed marketing and design strategies, participant in The Basement Incubator and F6S Rady StartR Accelerator.
    • Handled asynchronous tasks in a Django RESTful API with Celery and Redis as a message broker.
    • Following the Infrastructure as Code (IaC) paradigm and handling DevOps deployment automation with Terraform, AWS (EC2, ALB, ECS, ECR, VPC, RDS, and S3) and creating a GitLab CI/CD pipeline in a Docker image.
    • Stored logs in Amazon CloudWatch and AWS Certificate Management to secure HTTP connections to Amazon Load Balancer.
  • 2021
    NLP Intern
    Tangible AI, San Diego, CA
    • Given a set of linear dialogs, I aimed to create a single graph structure that “forks” when the dialogue intent changes, and a multi-degree node when two dialogs reach the same state.
    • Credited as a contributing author to “Natural Language Processing in Action, 2nd Ed.”
  • 2021
    Undergraduate Research Scholar
    Halıcıoğlu Data Science Institute, UC San Diego, La Jolla, CA
    • One of 20 students to be awarded the competitive $2,500 Undergraduate Research Scholarship.
    • Using Deep Q learning, policy networks for adaptive quantitative group testing by randomly sampling rows of the Walsh-Hadamard matrix. By doing this, we aim to restore a pre-determined binary vector of length 2^N with 2^K ones.
    • Implemented an algorithm utilizing binary expansions of rows and index summing to arrive at the correct solution exponentially faster than previous research and for larger values of N.
  • 2021
    Data Engineering Intern
    BlackRock, San Francisco, CA
    • Built an “Integrated Snow Report”, a prototype for a cloud data warehouse and its integration with reporting systems.
    • Used Camel Seda to parallelize data queries to Snowflake cloud platform.
    • Stack - Java, SQL, Spring Framework, Spring Boot, Apache Camel (integration), Apache Ignite, Apache Spark, Python.
  • 2020 - 2021
    NLP Intern
    Blooma AI, San Diego, CA
    • Used FastAPI to build a classification API for lending documents based on metadata specified in a document. Model achieved 90% accuracy.
    • Project would classify and assign categories to documents for further classification, reducing time for data labeling procedure from weeks to seconds.
  • 2020
    Research Intern
    Scripps Research Translational Institute, La Jolla, CA
    • Examine cross-correProject would classify and assign categories to documents for further classification, reducing time for data labeling procedure from weeks to seconds.lation between ECG and vital signals, develop models to predict body temperature from RR intervals, contribute to the development of wearable monitoring systems.
    • Present on the capability of Deep Neural Networks (DNNs) of classifying incident atrial fibrillation directly from ECG traces, potentially helping prevent associated strokes.
  • 2020
    Data Science Intern
    BD, San Diego, CA
    • One of two UCSD undergraduates to be awarded a $10,000 scholarship and an opportunity to work in quantitative analysis and foster a data-driven approach to solving problems in medical research.
    • Internship rescinded due to COVID-19.
  • 2019
    Machine Learning Intern
    RapidAI, San Mateo, CA
    • Devised an algorithm (utilizing k-means clustering among other methodologies) to help characterize CT perfusion image artifacts. Extracted metadata from datastores and normalized images.

Honors and Awards

  • 2021
    • First place and perfect score, Advanced Track, DataHacks 2021
  • 2020
    • HDSI Undergraduate Research Scholarship
    • First Place, Data Science Alliance Data Visualization Competition
    • HDSI Industry-Sponsored Research Scholarship

Academic Interests

  • Reinforcement learning
    • Inverse reinforcement learning for robotics.
    • Reinforcement learning for sparse signal recovery and NLP.
  • Graph neural networks
    • Improving message-passing graph neural network architectures for long-range dependencies.

Other Interests

  • Hobbies: Electronic music production and sound design (Phase Plant, Serum, Vital, Ableton, etc.). Realism drawing - when I was in middle school, I published an art tutorial that went viral and was adopted by international art universities in their academics!