resume.json

{
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      "secondary": ["#6c7781", "#ccd0d4"],
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    "order": [
        "work",
        "volunteer",
        "publications",
        "education",
        "projects",
        "awards",
        "certificates",
        "skills",
        "languages",
        "interests",
        "references"
      ]
  },
  "basics": {
    "name": "Anish Govind",
    "label": "Computer Engineer",
    "image": "https://www.gravatar.com/avatar/aca52d9e9cc2f33d091b28eb6ba42639.png?s=512",
    "summary": "An Electrical and Computer Engineering and Mathematics junior at University of California, San Diego seeking to conduct research in the fields of electronics, computers architecture, or mathematics. Interested in driver development, optimization, high performance computing, or computer graphics but open to exploring other areas.",
    "website": "https://anishgovind.com",
    "email": "anish@anishgovind.com",
    "location": {
      "city": "Bay Area",
      "countryCode": "US",
      "region": "California"
    },
    "profiles": [ 
      {
        "url": "https://github.com/anishg24",
        "username": "anishg24",
        "network": "GitHub"
      },
      {
        "url": "https://linkedin.com/anish-govind",
        "username": "Anish Govind",
        "network": "LinkedIn"
      }
    ]
  },
  "education": [
    {
      "startDate": "2021-09-28",
      "endDate": "2024-06-13",
      "area": "Computer Engineering",
      "studyType": "Bachelors of Science",
      "score": "3.7",
      "institution": "University of California San Diego"
    }
  ], 
  "skills": [
    {
      "name": "Hardware",
      "level": "Skilled",
      "keywords": [
        "Verilog", "SystemVerilog", "VHDL", "Verilator", "AMD Vivado", "Intel Quartus", "ModelSim", "LogicWorks", "Minecraft Redstone"
      ]
    },
    {
      "name": "High Performance Computing",
      "level": "Skilled",
      "keywords": [
        "NVIDIA CUDA", "AMD HIP", "SYCL", "OpenMPI", "OpenMP", "MVAPICH2", "Slurm", "Singularity", "Modules", "Spack", "Microsoft Azure"
      ]
    },
    {
      "name": "Machine Learning/Data Science",
      "level": "Skilled",
      "keywords": [
        "TensorFlow", "PyTorch", "NumPy", "Pandas", "Numba", "Dask", "OpenCV", "SciPy"
      ]
    },
    {
      "name": "Programming Languages",
      "level": "Proficient",
      "keywords": [
        "C", "C++", "Python", "Java", "JavaScript", "HTML", "CSS", "OpenGL", "MATLAB", "Bash"
      ]
    },
    {
      "name": "DevOps",
      "level": "Experienced",
      "keywords": [
        "Git", "Docker", "Gradle", "NGINX", "SSH", "CMake", "Prometheus", "Grafana", "DigitalOcean"
      ]
    },
    {
      "name": "Operating Systems",
      "level": "Experienced",
      "keywords": [
        "Arch Linux", "Ubuntu", "Raspbian", "CentOS", "Debian", "macOS", "Gentoo"
      ]
    }
  ],
  "awards": [
    {
      "title": "Highest HPL Score",
      "date": "2022-11-17",
      "awarder": "Student Cluster Competition 2022"
    },
    {
      "title": "3rd Place Overall",
      "date": "2022-11-17",
      "awarder": "Student Cluster Competition 2022"
    }
  ],
  "publications": [
    {
      "name": "Comparing Power Signatures of HPC Workloads: Machine Learning vs Simulation",
      "publisher": "ACM",
      "releaseDate": "2023-11-20",
      "url": "https://doi.org/10.1145/3624062.3624274"
    }
  ],
  "work": [
    {
      "name": "HPGeoC",
      "position": "HPC Engineer",
      "url": "https://hpgeoc.sdsc.edu/wiki/index.php/Main_Page",
      "startDate": "2022-11-02",
      "highlights": [
        "A team managed by Professor Yifeng Cui dedicated to developing and optimizing a world-class earthquake simulation application, and preparing software for future exascale supercomputing facilities",
        "Ported the team's current stencil code to AMD HIP and optimized it for exascale systems"
      ]
    },
    {
      "name": "Lawrence Berkeley National Laboratory",
      "position": "Student Assistant",
      "url": "https://www.nersc.gov/about/nersc-staff/advanced-technologies-group/",
      "startDate": "2023-06-18",
      "endDate": "2023-09-08",
      "highlights": [
        "Student assistant in ATG @ NERSC",
        "Analyzed power consumption on NERSC's current Supercomputer Perlmutter to aid in future supercomputing system procurement",
        "Presented findings in a poster to the lab's Computing Sciences Area",
        "Published results to SC23 Sustainable Computing Workshop",
        "Presented additional findings on reduced precision to Computing Sciences Area"
      ]
    },
    {
      "name": "Nike",
      "position": "Software Engineer",
      "url": "https://nike.com",
      "startDate": "2022-06-22",
      "endDate": "2022-09-10",
      "highlights": [
        "Aggregated product data from 12 different internal sources and converted the raw information into experiences for our consumers",
        "Refined the continuous delivery build pipeline and autmated analysis to ensure easier global delivery and scalability of our platform",
        "Developed performant AWS Lambdas with high-throughput architecture",
        "Exposed additional metadata of API calls to data consumers for error handling",
        "Consolidated several modules into a single repository for ease of deployment on AWS Waffle"
      ]
    }
  ],
  "volunteer": [ 
    {
      "organization": "2MuchCache",
      "position": "Competition Team",
      "url": "https://www.studentclustercompetition.us/2022/Teams/2MuchCache/index.html",
      "startDate": "2022-04",
      "endDate": "2022-12",
      "summary": "2MuchCache is UCSD's competition team for the Student Cluster Competition 2022. The SCC22 competition involved running several HPC benchmarks and applications on a custom system we request from sponsors. We must be able to run those workloads as high performance as we can, yet only consume a maximum of 3000W.",
      "highlights": [
        "Helped setup system monitoring and cooling solution for our cluster",
        "Optimized AMD EPYC CPUs and AMD Instinct Accelerators to run efficiently based on the workload by adjusting clock frequencies",
        "Developed scripts to reproduce a high performance Python framework on our cluster and on Microsoft Azure",
        "Placed 1st in HPL score among 10 teams",
        "Placed 3rd overall among 12 teams",
        "Published a paper to IEEE's Transactions on Parallel and Distributed Systems"
      ]
    },
    {
      "organization": "TritonLLC",
      "position": "Mentor",
      "url": "https://hpc-students.sdsc.edu/scc/scc23/",
      "startDate": "2023-09",
      "endDate": "2023-12",
      "summary": "TritonLLC is UCSD's competition team for the Student Cluster Competition 2023.",
      "highlights": [
        "Helped setting up MLPerf"
      ]
    },
    {
      "organization": "Hot Chips",
      "position": "Volunteer",
      "url": "https://hotchips.org",
      "startDate": "2023-08-26",
      "endDate": "2023-08-29",
      "highlights": [
        "Helped setup and tear down the Hot Chips conference at Stanford",
        "Listened to keynotes from several hardware companies",
        "Met John Hennessy"
      ]
    },
    {
      "organization": "ElectroTriton",
      "position": "Full-Stack Engineer",
      "startDate": "2022-03",
      "endDate": "2023-01",
      "highlights": [
        "2-person team managed by Professor Curt Schurgers tasked with developing a website to teach students about difficult analog circuit concepts",
        "Redesigned the frontend for ease of use by students and optimized the backend to send only required data instead of the entire record",
        "Started to port the application from server side rendering to an API with client side rendering",
        "Improved the data validation from user file inputs"
      ]
    },
    {
      "organization": "UCSD Engineers for Exploration",
      "position": "Embedded Systems Engineer",
      "startDate": "2022-02",
      "endDate": "2022-12",
      "highlights": [
        "Worked on a non-invasive way to track animals in the wild for better understanding of their habits",
        "Developed a performant library to run with minimal power consumption on embedded systems"
      ]
    } 
  ],
  "projects": [
    {
      "name": "XORiginal Processor ISA",
      "startDate": "2023-03",
      "endDate": "2023-06",
      "description": "XORiginal Processor ISA (or XORPI for short) is an instruction set architecture that 2 other members and I developed. It was designed for quickly solving complex problems posed to us in our CSE 141L course at UCSD. The ISA was sketched out by us, then developed with SystemVerilog and simulated using a combination of Verilator and ModelSim. Finally, the processor was synthesized with Intel Quartus.",
      "highlights": [
        "Developed a whitepaper for an ISA capable of performing parity encoding and decoding as well as pattern matching",
        "Developed the processor model with SystemVerilog, including our custom built XOR unit",
        "Simulated and tested the processor with Verilator",
        "Verified our results with the provided SystemVerilog testbenches in ModelSim",
        "Synthesized our model with Intel Quartus",
        "Built an assembler and debugger for our ISA in C++"
      ]
    },
    {
      "name": "Equitable Elevator Controller MK. VII",
      "startDate": "2023-05",
      "endDate": "2023-06",
      "description": "Equitable Elevator Controller MK. VII is a model written in VHDL designed for CSE 143 at UCSD. The controller features input processing, direction determination, stop prioritization, floor arrival and direction adjustment, continuous operation, and door control.",
      "highlights": [
        "Developed using VHDL",
        "Simulated with ModelSim",
        "Wrote a whitepaper describing the elevator controller",
        "Wrote a comprehensive testbench in VHDL and verified the model with ModelSim",
        "Presented my work to 30 peers"
      ]
    },
    {
      "name": "8-bit CPU on Breadboards",
      "startDate": "2021-06",
      "endDate": "2021-08",
      "highlights": [
        "Built, tested, and debugged a working 8-bit CPU from scratch using only ICs, hookup wire, and breadboards",
        "Two 8-bit general purpose registers",
        "One 8-bit ALU register",
        "Two conditional jump instructions",
        "Adjustable clock speed (1Hz to 70Hz)",
        "Consumes 10W of power"
      ],
      "url": "https://drive.google.com/file/d/1SkDrlYZS4vhczlkxpkTZ0qkgF1Ma3-pm/view?usp=sharing"
    }, 
    {
      "name": "InteractiveMNIST",
      "startDate": "2020-07",
      "endDate": "2020-07",
      "highlights": [
        "Built a full-stack deep learning classification web application",
        "Trained a CNN on MNIST using Keras and achieving a validation accuracy of 98.84% after 10 epochs",
        "Converted Keras model to tensorflow.js for deployment",
        "Developed frontend with P5.js, Chart.js, and Bootstrap"
      ],
        "url": "https://github.anishgovind.com/InteractiveMNIST/"
    }
  ],
  "interests": [
    {
      "name": "Programming"
    },
    {
      "name": "Basketball"
    },
    {
      "name": "Making Tea"
    },
    {
      "name": "Operating System Tweaking"
    },
    {
      "name": "Homelab",
      "keywords": [
        "Bitwarden",
        "Grafana",
        "Cal.com",
        "Authentik",
        "Minecraft",
        "HomeAssistant"
      ]
    }
  ],
  "certificates": [
    {
      "name": "Getting Started with DeepStream for Video Analytics on Jetson Nano",
      "issuer": "NVIDIA DLI",
      "date": "2021-05-10",
      "url": "https://courses.nvidia.com/certificates/f4555fee94c54ee8822315b8c3d94645/"
    },
    {
      "name": "Fundamentals of Accelerated Computing with CUDA Python",
      "issuer": "NVIDIA DLI",
      "date": "2021-01-15",
      "url": "https://courses.nvidia.com/certificates/1cf4c926a62b460d9c56f21722e809c9/"
    },
    {
      "name": "Accelerating CUDA C++ Applications with Concurrent Streams",
      "issuer": "NVIDIA DLI",
      "date": "2020-11-10",
      "url": "https://courses.nvidia.com/certificates/2af373db5e9d454a87d2074f4928771d/"
    }, 
    {
      "name": "Deep Learning: GANs and Variational Autoencoders",
      "issuer": "Udemy",
      "date": "2020-11-30",
      "url": "https://www.udemy.com/certificate/UC-63320aff-d469-4651-b0b7-8fd428652347/"
    },
    {
      "name": "Getting Started with AI on Jetson Nano",
      "issuer": "NVIDIA DLI",
      "date": "2020-09-04",
      "url": "https://courses.nvidia.com/certificates/1881f8b3f5f24f39ad08d4e66dff9a31/"
    }
  ]
}