Hi folks 👋! I’m Manuel Parra

I’m a Postdoctoral Researcher at the Instituto de Astrofísica de Andalucía (IAA-CSIC), working at the intersection of
radio astronomy, data-intensive science, cloud computing, and semantic technologies.

My work focuses on scalable scientific infrastructures, HI data analysis, and end-to-end workflows for next-generation astronomy projects such as the SKA Regional Centre Network (SRCNet).

⚡ Fun fact
I enjoy working at both extremes: from petabyte-scale scientific infrastructures down to bare-metal programming on 1980s hardware.

🔭 Current work

• 🛰️ Neutral Hydrogen (HI) science

  • Characterisation and automatic classification of HI profiles
  • Large-scale processing of radio astronomy datasets
  • Working with legacy surveys (e.g. Arecibo) and preparing workflows for SKA-era data

• ☁️ Scientific infrastructures & cloud computing

  • Kubernetes-based platforms for data-intensive science
  • Storage-centric workflows (CephFS, Rucio, object & POSIX storage)
  • Hybrid cloud & on-prem infrastructures (OpenStack, bare metal)

• 🔄 End-to-end scientific workflows

  • Science Gateway → Jupyter → data preparation → analysis → visualisation
  • Reproducibility, automation, and scalability by design

Teaching & lecturing

• Cloud Computing & Intelligent Systems.
• Digital Transformation and Smart Agriculture.
• Databases.
• Cybersecurity: Virtual Machines and Containers.

🌱 Currently exploring

• Applied AI/ML for:
  • Automated classification of astronomical signals
  • Intelligent brokering and resource optimisation in distributed infrastructures
• Semantic models for scientific workflows and services
• Advanced GitOps patterns for scientific platforms
• Performance benchmarking and optimisation in heterogeneous environments

🧠 Research & technical interests

• Radio astronomy & SKA science platforms
• Artificial Intelligence for scientific data analysis
• Semantic Web, RDF, JSON-LD, Linked Data
• Workflow description & interoperability
• Distributed systems & cloud-native architectures
• Data provenance, reproducibility, and FAIR principles

🧩 Selected topics I enjoy discussing

• Designing scalable science platforms
• Turning research workflows into production-ready services
• Semantic descriptions of infrastructures and workflows
• Bridging astronomy + cloud + AI
• Performance vs reproducibility trade-offs

🧪 Side projects & hobbies

• 🕹️ Retro-computing

  • Amiga 500 (m68k, Kickstart 1.3)
  • Low-level C/C++ programming, ASM.
  • Graphics, bitplanes, sprites, and hardware-close development

• 🧱 Systems tinkering

  • Benchmarking compute & storage
  • Exploring unconventional architectures

• 📚 Reading & technical writing

  • Research papers
  • Documentation-driven development