Kartik Kirankumar Vadhawana
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Kartik Kirankumar Vadhawana

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New York, United States

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Résumé

Jobs verified_user 0% verified
  • S
    Software Developer
    Stony Brook University (PoliTech Research Group)
    Aug 2025 - Dec 2025 (5 months)
    • Built scalable district plan simulations as measured by 5K+ Monte Carlo outputs by coding pipelines in Python on Seawulf HPC. • Automated comparative election analysis as measured by probability distributions by simulating FRA and SMD outcomes with Python and Flask. • Generated reproducible datasets by scripting extraction and cleaning in Python.
  • iNeuron.ai
    Machine Learning Intern
    iNeuron.ai
    Nov 2023 - Feb 2024 (4 months)
    • Built RUL prediction model for turbofan engines using TensorFlow & Scikit-Learn, reducing MAE by 15% and improving failure forecasting. • Engineered features with moving averages, exponential smoothing, and signal normalization to improve fault detection. • Fine-tuned MLP model in PyTorch using cross-validation and grid search to achieve R2 = 0.69. • Integrated the model into a FastAPI-based API with sub-300ms latency for real-time aircraft monitoring.
  • C
    Data Analyst Intern
    Cinch Automation
    May 2023 - Jul 2023 (3 months)
    • Designed ETL workflows with Apache Airflow,using OOD/UML to reduce manual IoT process by 30%. • Analyzed trends using SQL & Tableau, enabling inventory optimization and reducing shortages by 18%. • Debugged Firebase queues, boosting real-time notification delivery speed by 40%.
Education verified_user 0% verified
  • S
    M.S. in Computer Science
    Stony Brook University
    Aug 2024 - Current (1 year 6 months)
Projects (professional or personal) verified_user 0% verified
  • S
    Scalable Real-Time Data Pipeline
    Feb 2025 - Current (1 year)
    • Developed large-scale, real-time infrastructure handling 1000+ events/second with Apache Kafka, Spark Streaming, and Airflow. • Designed microservices with Docker achieving 99.9% uptime through automated failover. • Engineered ETL pipelines across PostgreSQL and Cassandra using Airflow for 50K+ user records.
  • F
    Fault-Tolerant Distributed Job Scheduler
    May 2024 - Jul 2024 (3 months)
    • Developed a master-worker job scheduling system in Go with PostgreSQL and gRPC, supporting retry queues and fault handling. • Achieved 99.9% uptime through heartbeat-based scaling and failover-safe execution. • Dockerized all components and used a custom bridge network for seamless RPC and service discovery.
  • C
    Cloud-Native CI/CD Platform
    May 2024 - Current (1 year 9 months)
    • Engineered a modular CI/CD platform using GitHub Actions and Docker to automate multi-service deployments on GCP. • Configured YAML workflows for dynamic build triggers, secrets management, caching, and health checks. • Built reusable Bash-based test harnesses with logging and rollback mechanisms, enabling 70% faster recovery from failed deploys.