Aishwarya Tomer

Software Engineer & Open Source Contributor

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Competitive Programming: LeetCode

163
Easy
32
Medium
2
Hard

Experience

Open Source Contributor at Independent Researcher

Oct 2024 - Present
  • Cloud & Generative AI Foundations: Completed Google Cloud's Introduction to Generative AI Learning Path (Sep 2025) covering LLM architectures and Responsible AI.
  • Enterprise Software Practices: Completed The Linux Foundation's Open Source Software Development Methods (Aug 2025).
  • Algorithmic Problem Solving: Solved 500+ LeetCode problems focused on advanced data structures, achieving a Top 3.7% global rank.

Software Engineering Intern (Backend) at Samsara

Jun 2024 - Sep 2024
  • Engineered the "Global Speed Limit Overrides" system to address inaccurate third-party map data, reducing false-positive speeding alerts by a projected 40%.
  • Designed and implemented a consensus algorithm by analyzing a dataset of 5,000+ road samples against the Google Maps API.
  • Developed a high-performance concurrent polling worker in Go and designed an optimized SQL schema to ingest high-volume override data.

Education

Bachelor of Science (Hons.), Computer Science

Sep 2023 - Aug 2024
Goldsmiths, University of London
  • Classification: Upper Second Class Honours (2:1)
  • Selected Coursework: Machine Learning (83% - Distinction), Data Mining, Game AI, Databases.

Bachelor of Science, Computer Science (Years 1 & 2)

Oct 2021 - Aug 2023
University of London (Worldwide)
  • Completed 240 credits (Level 4 & 5) via distance learning before transferring to Goldsmiths for final year.
  • Coursework: Data Structures & Algorithms, Discrete Mathematics, Agile Software Projects, Computer Security.

Projects

Thermographic Fever Detection & Temperature Prediction

Python, Scikit-learn
  • Developed a custom ML pipeline to predict oral temperatures and classify fever instances using infrared thermographic sensor data of 1,000+ subjects, achieving a classification accuracy exceeding 95%.
  • Engineered robust spatial representations using K-Means clustering to capture nonlinear spatial thermal distributions.
  • Optimized model hyperparameter tuning via RandomizedSearchCV to ensure robust generalization across varying thermal profiles.

Autonomous Tetris Agent (AI & Heuristic Optimization)

C#, Genetic Algorithms
  • Built an autonomous AI agent capable of clearing an average of 682 lines per game by implementing a linear evaluation function based on six weighted board-state factors.
  • Utilized a Genetic Algorithm to optimize decision-making, training the model over multiple generations to converge on an ideal set of weights.
  • Conducted ablation studies across diverse scenarios to refine decision-making and prevent local optima convergence.

Skills

Languages

Python, Go (Golang), C-sharp, JavaScript, SQL, Java

Foundations

Data Structures, Algorithms, Distributed Systems, Operating Systems, OOP

ML/Data & Tools

Scikit-learn, Pandas, NumPy, Jupyter, Git, Linux, GitHub, Unity Game Engine