data.json

{
  "version": "3.1.0",
  "personalInfo": {
    "name": "Rahul Yedida",
    "suffix": "",
    "contact": {
      "email": "hello@ryedida.me",
      "phone": "+1 (206) 660-7542"
    },
    "links": [
      {
        "display": "Website",
        "url": "https://ryedida.me"
      },
      {
        "display": "GitHub",
        "url": "https://github.com/yrahul3910"
      },
      {
        "display": "LinkedIn",
        "url": "https://www.linkedin.com/in/rahul-yedida/"
      },
      {
        "display": "Google Scholar",
        "url": "https://scholar.google.com/citations?user=0lP2AvkAAAAJ&hl=en"
      }
    ]
  },
  "education": [
    {
      "institution": "North Carolina State University",
      "location": "Raleigh, NC",
      "degree": "Ph.D. Computer Science -- Advisor: Dr. Tim Menzies",
      "dates": ["2019-08-01", "2024-07-30"]
    },
    {
      "institution": "PES University",
      "location": "Bangalore, India",
      "degree": "B.E. Computer Science",
      "dates": ["2015-08-01", "2019-05-01"]
    }
  ],
  "employment": [
    {
      "organization": "LexisNexis Legal \\& Professional",
      "location": "Raleigh, NC",
      "positions": [
        {
          "position": "Senior Data Scientist I",
          "dates": ["2024-05-24", null],
          "details": [
            "\\textbf{Performance improvements:} Improved customer-facing product runtime by 24.8\\% through various inefficiency fixes based on profiling results. Reduced peak memory usage duration by 21.3\\% by implementing lazy-loading and code-splitting.",
            "\\textbf{Drafting improvements:} Helped improve complaint drafting results by 46 percentage points of usefulness through various improvements",
            "\\textbf{Workflow improvement:} Led initiative to use Bayesian optimization for prompt tuning.",
            "\\textbf{Technology:} Python, Litestar, React, TypeScript, Tailwind"
          ],
          "tags": ["ml_emp"]
        },
        {
          "position": "Senior Data Scientist I",
          "dates": ["2024-05-24", null],
          "details": [
            "Profiled LLM calls and fixed inefficiencies, leading to a 10\\% reduction in runtime.",
            "Refactored and parallelized code for a 16.4\\% speedup.",
            "Complaint improvements: 40\\% --> 70\\% --> 86\\% usefulness.",
            "Proposed tabu search and Bayesian optimization methods for prompt tuning.",
            "\\textbf{Workflow improvement:} Led initiative to use Bayesian optimization for prompt tuning.",
            "\\textbf{Technology:} Python, Litestar, React, TypeScript, Tailwind"
          ],
          "tags": ["hidden"]
        }
      ]
    },
    {
      "organization": "Amazon",
      "location": "New York, NY / Bellevue, WA",
      "positions": [
        {
          "position": "Software Dev Engineer Intern",
          "dates": ["2023-05-15", "2023-08-04"],
          "details": [
            "Implemented profile locks for Prime Video on Echo Show devices.",
            "\\textbf{Technology:} React Native, TypeScript"
          ],
          "tags": ["sde_emp"]
        },
        {
          "position": "Software Dev Engineer Intern",
          "dates": ["2022-05-09", "2022-07-15"],
          "details": [
            "Developed a full-stack system to publish announcements in scorecards used by delivery service partners (DSPs).",
            "\\textbf{Technology:} React/Redux, TypeScript, Redux Saga, DynamoDB, Java Spring"
          ],
          "tags": ["sde_emp"]
        }
      ]
    },
    {
      "organization": "North Carolina State University",
      "location": "Raleigh, NC",
      "positions": [
        {
          "position": "PhD Student",
          "dates": ["2019-08-16", "2024-07-30"],
          "details": [
            "\\textbf{State-of-the-art hyper-parameter optimization:} Proposed a novel hyper-parameter optimization method that outperforms prior work and is 200-700\\% faster.",
            "\\textbf{Better, faster deep learning for SE:} Improved defect prediction by up to 123\\% (F-1 score), code smell detection by up to 30\\% (AUC), issue lifetime prediction by up to 76\\% (accuracy), automated microservice partitioning by up to 285\\% (modularity)",
            "\\textbf{Semi-supervised learning:} Achieved state-of-the-art results (up to 100\\% improvement in AUC) on static code warnings analysis using 10\\% of the labels.",
            "\\textbf{Teaching:} Teaching assistant for 830 students in total, over 5 semesters, for CSC 230 (C and Software Tools), CSC 510 (Software Engineering), and CSC 591/791 (Automated Software Engineering)"
          ],
          "tags": ["phd"]
        },
        {
          "position": "Graduate Teaching Assistant",
          "dates": ["2023-08-16", "2024-05-12"],
          "details": [
            "TA (with 2 others) for 52 students for a graduate Automated Software Engineering course.",
            "TA (with 4 others) for 289 students for a graduate Software Engineering course."
          ],
          "tags": ["ml_emp", "ta"]
        },
        {
          "position": "Graduate Teaching Assistant",
          "dates": ["2022-08-16", "2023-05-15"],
          "details": [
            "TA (with 3 others) for 97 students for a graduate Automated Software Engineering course.",
            "TA (with 4 others) for 233 students for a graduate Software Engineering course."
          ],
          "tags": ["ml_emp", "ta"]
        },
        {
          "position": "Graduate Research Assistant",
          "dates": ["2020-01-01", "2022-05-15"],
          "details": [
            "\\textbf{Better, faster deep learning for SE:} Improved defect prediction by up to 123\\% (F-1 score), code smell detection by up to 30\\% (AUC)",
            "\\textbf{Semi-supervised learning:} Achieved state-of-the-art results on static code warnings analysis using 10\\% of the labels."
          ],
          "tags": ["ml_emp", "ta"]
        },
        {
          "position": "Graduate Teaching Assistant",
          "dates": ["2019-08-16", "2019-12-31"],
          "details": [
            "TA (with 1 other) for 159 students for an undergraduate C and Software Tools course."
          ],
          "tags": ["ml_emp", "ta"]
        }
      ]
    }
  ],
  "projects": [
    {
      "title": "RAG Agent for Zotero",
      "dates": ["2024-10-25", null],
      "skills": ["Rust", "SQLite"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/zotero-rag/"
        }
      ],
      "details": [
        "WIP: Building a PDF parser and a RAG agent for academic papers by linking to the user's Zotero library."
      ],
      "tags": ["sde", "ml"],
      "hidden": true
    },
    {
      "title": "Programmable Resumes",
      "dates": ["2023-08-01", null],
      "skills": ["Python"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/programmable-resumes"
        }
      ],
      "details": [
        "Developed a specification and implementation for modular, customizable resumes with support for two popular LaTeX templates. Wrote this resume using this tool."
      ],
      "tags": ["sde"]
    },
    {
      "title": "pysh",
      "dates": ["2021-05-01", "2024-12-31"],
      "skills": ["C++", "TMLanguage"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/pysh"
        }
      ],
      "details": [
        "Developed a superset of Python that allows running Shell code natively, with a VS Code syntax highlighting extension."
      ],
      "tags": ["sde"]
    },
    {
      "title": "RAISE",
      "dates": ["2020-08-01", null],
      "skills": ["Python", "Keras"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/raise"
        },
        {
          "display": "PyPI",
          "url": "https://pypi.org/project/raise-utils/"
        }
      ],
      "details": [
        "Sole developer for a PEP8-compliant, ML Python package used by our research lab and others for replicable results. Downloaded 43k times."
      ],
      "tags": ["ml"]
    },
    {
      "title": "Google/Meta Data Mining",
      "dates": ["2021-02-01", "2021-05-01"],
      "skills": ["Python", "Keras"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/google-takeout-data-mining"
        }
      ],
      "details": [
        "Data science project to use Google Takeout and Meta user data to suggest products to advertise to a user from Amazon best-sellers using DistilGPT-2, and achieved 0.6 F-1 score."
      ],
      "tags": ["ml"]
    },
    {
      "title": "Threaded Discussions Website",
      "dates": ["2021-02-01", "2021-06-01"],
      "skills": ["MongoDB", "Node.js", "React"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/threaded-discussions"
        }
      ],
      "details": [
        "Companion website for video calls that allows for Reddit-style, threaded discussions."
      ],
      "tags": ["sde"]
    },
    {
      "title": "NearConnect",
      "dates": ["2020-11-01", "2021-03-01"],
      "skills": ["iOS", "SwiftUI"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/socialqr"
        },
        {
          "display": "App Store",
          "url": "https://apps.apple.com/us/app/nearconnect/id1547157546"
        }
      ],
      "details": [
        "iOS app to connect with people nearby using multicast peer-to-peer connections."
      ],
      "tags": ["sde"]
    },
    {
      "title": "Novel Drug Repurposing Hypotheses",
      "dates": ["2019-10-01", "2020-02-01"],
      "skills": ["Python", "PyTorch"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/drug-repurposing-textmining"
        }
      ],
      "details": [
        "Identified novel drug repurposing hypotheses using text mining of radio transcripts, and verified results using a knowledge graph."
      ],
      "tags": ["ml"]
    },
    {
      "title": "Personalized Chatbot",
      "dates": ["2019-05-01", "2019-05-01"],
      "skills": ["Python", "Keras"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/custom-chatbot"
        }
      ],
      "details": [
        "Fine-tuned a GPT-2 345M model on 730k messages from Telegram logs to create a personalized chatbot."
      ],
      "tags": ["ml"]
    },
    {
      "title": "Intelligent Tutoring System",
      "dates": ["2018-09-01", "2019-05-01"],
      "skills": ["Python"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/student-modeling-project"
        }
      ],
      "details": [
        "Implemented an Intelligent Tutoring System backend using Bayesian Knowledge Tracing and a novel question selection algorithm."
      ],
      "tags": ["ml"]
    },
    {
      "title": "Human Activity Data Project",
      "dates": ["2018-10-01", "2018-11-01"],
      "skills": ["Python", "Keras"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/ActivityDataProject"
        }
      ],
      "details": [
        "Collected personal activity data for 9 months, grouped tasks into 21 categories. Analyzed most productive hours of the day."
      ],
      "tags": ["ml"]
    },
    {
      "title": "Astronomy Image Restoration",
      "dates": ["2018-08-22", "2018-11-08"],
      "skills": ["Python", "Keras"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/astro-image-restoration"
        }
      ],
      "details": [
        "Developed a machine learning approach to restore astronomical images affected by PSF anisotropy and smearing in crowded-field photometry,  improving data retention and accuracy in differential imaging analysis of long-baseline optical time series."
      ],
      "tags": ["ml"]
    },
    {
      "title": "JournalBear",
      "dates": ["2017-01-01", "2019-02-01"],
      "skills": ["JavaScript, Electron"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/journal"
        },
        {
          "display": "Softpedia",
          "url": "https://www.softpedia.com/get/Office-tools/Diary-Organizers-Calendar/JournalBear.shtml"
        }
      ],
      "details": [
        "Cross-platform journal application with AES-256 encryption. Rated 4/5 by Softpedia."
      ],
      "tags": ["sde"]
    },
    {
      "title": "Results Scraper",
      "dates": ["2018-03-01", "2018-08-01"],
      "skills": ["MongoDB", "Express.js", "React", "Node.js"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/results-scraper-node"
        }
      ],
      "details": [
        "Website for scraping university examination results and displaying charts and printable reports, with caching."
      ],
      "tags": ["sde"]
    },
    {
      "title": "Video Sharing Website",
      "dates": ["2017-10-01", "2017-12-01"],
      "skills": [
        "MySQL",
        "Express.js",
        "React",
        "Node.js",
        "Sass",
        "Elasticsearch"
      ],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/video-sharing-site"
        }
      ],
      "details": [
        "Simplified implementation of a video-sharing website with subscriptions and custom searching."
      ],
      "tags": ["sde"]
    },
    {
      "title": "Xtreme Calculations",
      "dates": ["2013-04-01", "2017-10-01"],
      "skills": ["VB.NET", "Python"],
      "links": [
        {
          "display": "Softpedia",
          "url": "https://www.softpedia.com/get/Science-CAD/Xtreme-Calculations.shtml"
        }
      ],
      "details": [
        "Windows math software to solve scientific and mathematical problems, with over 30k downloads across multiple sites."
      ],
      "tags": ["sde"]
    },
    {
      "title": "Video Indexer",
      "dates": ["2017-06-01", "2017-09-01"],
      "skills": ["C++", "Qt", "Sphinx"],
      "links": [
        {
          "display": "GitHub",
          "url": "https://github.com/yrahul3910/video-indexer"
        }
      ],
      "details": [
        "Cross-platform desktop application to detect the time(s) a given keyword was spoken in a video."
      ],
      "tags": ["sde"]
    },
    {
      "title": "Web development projects",
      "dates": ["2017-01-01", "2017-11-01"],
      "skills": ["MongoDB", "Express.js", "React", "Node.js", "Sass", "D3.js"],
      "links": [
        {
          "display": "CodePen",
          "url": "https://codepen.io/yrahul"
        }
      ],
      "details": [
        "Projects include URL shortener, rogue-like dungeon crawler game, voting application, Simon game, land surface temperature heatmap, and mapping meteorite impacts across the globe."
      ],
      "tags": ["sde"]
    }
  ],
  "publications": [
    "Baldassarre, M. T., Ernst, N., Hermann, B., Menzies, T., \\& \\textbf{Yedida, R.} (2023). (Re)use of Research Results (is Rampant). \\textit{Communications of the ACM, 66(2), 75-81}.",
    "\\textbf{Yedida, R.}, Kang, H. J., Tu, K., Lo, D., \\& Menzies, T. (2023). How to Find Actionable Static Analysis Warnings: A Case Study with FindBugs. \\textit{IEEE Transactions on Software Engineering, (01), 1-17}.",
    "\\textbf{Yedida, R.}, Krishna, R., Kalia, A., Menzies, T., Xiao, J., \\& Vukovic, M. (2023). An Expert System for Redesigning Software for Cloud Applications. \\textit{Expert Systems with Applications}.",
    "\\textbf{Yedida, R.}, Menzies, T. (2022). How to Improve Deep Learning for Software Analytics (a case study with code smell detection). In \\textit{2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR). IEEE, 2022.}",
    "\\textbf{Yedida, R.}, \\& Menzies, T. (2021). On the Value of Oversampling for Deep Learning in Software Defect Prediction. \\textit{IEEE Transactions on Software Engineering, doi: 10.1109/TSE.2021.3079841}",
    "Agrawal, A., Yang, X., Agrawal, R., \\textbf{Yedida, R.}, Shen, X., \\& Menzies, T. (2021). Simpler Hyperparameter Optimization for Software Analytics: Why, How, When?. \\textit{IEEE Transactions on Software Engineering, doi: 10.1109/TSE.2021.3073242}",
    "Yang, X., Chen, J., \\textbf{Yedida, R.}, Yu, Z., \\& Menzies, T. (2021). Learning to recognize actionable static code warnings (is intrinsically easy). \\textit{Empirical Software Engineering, 26(3), 1-24}.",
    "\\textbf{Yedida, R.}, Krishna, R., Kalia, A., Menzies, T., Xiao, J., \\& Vukovic, M. (2021). Lessons learned from hyper-parameter tuning for microservice candidate identification. \\textit{Proceedings of the thirty-sixth IEEE/ACM International Conference on Automated Software Engineering (ASE)}",
    "\\textbf{Yedida, R.}, \\& Saha, S. (2021). Beginning with Machine Learning: A Comprehensive Primer. \\textit{The European Physical Journal Special Topics}, 230(10), 2363-2444.",
    "Saha, S., Nagaraj, N., Mathur, A., \\textbf{Yedida, R.}, \\& Sneha, H. R. (2020). Evolution of novel activation functions in neural network training for astronomy data: habitability classification of exoplanets. \\textit{The European Physical Journal Special Topics, 229(16), 2629-2738}.",
    "\\textbf{Yedida, R.}, Saha, S., \\& Prashanth, T. (2020). LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence. \\textit{Applied Intelligence, 1-19}.",
    "Sridhar, S., Saha, S., Shaikh, A., \\textbf{Yedida, R.}, \\& Saha, S. (2020, July). Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. In \\textit{2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE}.",
    "Khaidem, L., \\textbf{Yedida, R.}, \\& Theophilus, A. J. (2019, November). Optimizing Inter-nationality of Journals: A Classical Gradient Approach Revisited via Swarm Intelligence. In \\textit{International Conference on Modeling, Machine Learning and Astronomy (pp. 3-14). Springer, Singapore}."
  ],
  "talks": [
    {
      "title": "Improving deep learning performance using theoretical ML",
      "event": "IEEE AI Symposium",
      "date": "2024-02-17",
      "location": "BITS Pilani, KK Birla Goa Campus, India"
    }
  ],
  "skills": [
    {
      "name": "Python",
      "type": "Languages"
    },
    {
      "name": "TypeScript",
      "type": "Languages"
    },
    {
      "name": "Java",
      "type": "Languages"
    },
    {
      "name": "C++",
      "type": "Languages"
    },
    {
      "name": "Gleam",
      "type": "Languages"
    },
    {
      "name": "Flask",
      "type": "Frameworks"
    },
    {
      "name": "Keras",
      "type": "Frameworks"
    },
    {
      "name": "PyTorch",
      "type": "Frameworks"
    },
    {
      "name": "Node.js",
      "type": "Frameworks"
    },
    {
      "name": "React",
      "type": "Frameworks"
    },
    {
      "name": "MySQL",
      "type": "Databases"
    },
    {
      "name": "MongoDB",
      "type": "Databases"
    },
    {
      "name": "DynamoDB",
      "type": "Databases"
    },
    {
      "name": "Google Compute Engine",
      "type": "Cloud"
    },
    {
      "name": "S3",
      "type": "Cloud"
    },
    {
      "name": "Google Cloud Storage",
      "type": "Cloud"
    },
    {
      "name": "EC2",
      "type": "Cloud"
    }
  ],
  "honors": [
    {
      "date": ["2023-07-25", null],
      "title": "Google Cloud Champion Innovator - Cloud AI/ML"
    },
    {
      "date": "2022-12-21",
      "title": "Google Cloud Research Innovators Mentor"
    },
    {
      "date": "2022-10-20",
      "title": "Google Cloud Champion Innovator"
    },
    {
      "date": "2022-02-24",
      "title": "Google Cloud Research Innovator"
    }
  ],
  "funding": [
    {
      "amount": "\\$5,000",
      "title": "Google Cloud Academic Research Grant",
      "date": "2022-02-24"
    }
  ],
  "service": [
    {
      "title": "Guest Editor",
      "details": "EMSE Special Issue on Replications and Negative Results (RENE) 2025"
    },
    {
      "title": "Co-Chair",
      "details": "Workshop on Replications and Negative Results (RENE) at ASE 2024"
    },
    {
      "title": "Reviewer",
      "details": "TMLR 2024; ICML 2024-2025; Neural Processing Letters 2023-2024; Neural Computing \\& Applications (NCAA), 2023-2025; Artificial Intelligence Review 2023; ICLR 2024-2025; NeurIPS 2023; Journal of Big Data, 2023; Automated Software Engineering (ASE), 2023; Empirical Software Engineering (EMSE), 2021; IEEE Symposium Series on Computational Intelligence (SSCI) 2020"
    },
    {
      "title": "PC Member",
      "details": "AAAI 2025; AI Foundation Models and Software Engineering (FORGE) at ICSE 2024; Automated Software Engineering (ASE) Artifact Evaluation Track, 2022; International Conference on Software Maintenance and Evolution (ICSME) Artifact Evaluation Track, 2021-2023; International Conference on Modeling, Machine Learning, and Astronomy (MMLA), 2019"
    },
    {
      "title": "Student Volunteer",
      "details": "Automated Software Engineering (ASE) 2021",
      "hidden": true
    }
  ]
}