Ida Khiavi

B.Eng. , M.Sc. in computer Science

Resume

👩‍💻 About Me

Engineer by training, explorer by instinct. I’ve navigated worlds as different as real-time air traffic control systems, AI-powered shipyard analytics, and multi-omics genomic research.
I’m happiest at the intersection of hard technical challenges and big-picture problem-solving — whether it’s squeezing performance out of a protocol stack, turning raw environmental data into insights, or translating genomic complexity into clear visual models.
My career and research share the same philosophy: make it work, make it elegant, make it useful.

💼 Experience

Software Engineer — Frequentis QC, Canada (Jan 2024 – Present)

  • Develop and maintain high-assurance embedded software for VoIP gateways in air traffic control, using C++, Java, and shell scripting in mission-critical, real-time environments.
  • Design secure, low-latency SIP protocols for Air-Ground and Ground-Ground communications.
  • Build Qt-based graphical interfaces optimized for resource-constrained embedded systems.
  • Conduct full-system lab validation: integrate hardware, simulate real-time calls, capture and analyze network traffic with Wireshark, and verify system performance under operational loads.

Software Developer / Data Engineer — Genoa Design International NL, Canada (Feb 2021 – Sep 2023)

  • Developed interactive dashboards and visualizations with SQL, Power BI, Python, and C#, integrating machine learning (PyTorch, Scikit-learn) for KPI forecasting, anomaly detection, and data imputation.
  • Designed REST API-driven microservices and optimized SQL access for improved reporting.
  • Built robust ETL pipelines (SSIS, shell scripts, Python, C#) for integrating, cleaning, and transforming ship design and construction data.
  • Implemented multi-dimensional OLAP cubes (SSAS) to deliver sub-second querying for complex operational and financial reporting.

Web Developer — Canadian Integrated Ocean Observing Systems (Nov 2019 – Jul 2020)

  • Created Python/FastAPI applications to merge real-time weather and ocean data from multiple APIs.
  • Applied deep learning to forecast oceanic trends and detect climate-related anomalies.
  • Designed Streamlit dashboards to allow researchers and policymakers to interact with climate datasets in real time.

Research & Teaching Assistant — Memorial University (Jan 2018 – Dec 2020)

  • Developed an R-based interactive visualization library for my Master’s thesis, enabling multi-layered exploration of protein structures by integrating structural and sequence data.
  • Applied machine learning to genomic datasets to identify sequence motifs, predict gene regulation patterns, and classify tumor types.
  • Mentored students in Computer Logic, Algebra, and Graph Theory, turning abstract concepts into practical tools.

🛠 Technical Skills

Languages & Frameworks:
C++ (Qt, real-time systems, SIP), Java (Spring Boot, Kafka), Python (Pandas, Scikit-learn, PyTorch, FastAPI, Streamlit), C# (MVC, APIs), SQL (SSIS, SSAS), Power BI
Tools & Platforms: Azure CI/CD, Azure Data Factory, Containerization, Git, Wireshark
Approaches: Microservices, Data Pipelines, ETL, Machine Learning, Visualization

🎓 Education & Publications

Master of Science in Computer Science — Memorial University of Newfoundland (GPA: A)

My Master’s research sat at the crossroads of bioinformatics, mathematical modeling, and visual analytics.
I designed computational tools to analyze multi-omics datasets, focusing on transcription factor dimer binding sites — regions of DNA where pairs of proteins regulate gene expression. Traditional models often ignored heterogeneity in binding affinities; my work introduced a novel “forked” position weight matrix approach to capture these complexities.

This led to:

  • First co-author publication: Representing Transcription Factor Dimer Binding Sites Using Forked-Position Weight Matrices and Forked-Sequence Logos (under review, Nucleic Acids Research).
  • Conference presentation at Applied Bioinformatics in Life Sciences, showcasing interactive visualizations that made genomic regulatory patterns accessible to non-specialists.

Bachelor of Engineering in Computer Hardware Engineering

Specialized in microprocessors, FPGA design, signal processing, and VLSI architecture.
This foundation in hardware-level thinking informs my work in embedded systems today — from optimizing memory footprints to understanding real-time constraints at the silicon level.

🌱 Interests

Philosophy, cinema, hiking, travel, culinary adventures, classic literature — and drawing unexpected parallels between poetry and system architecture.