aysha@portfolio:~$ ./choose-path
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Software Engineer & AI Researcher
Hi, I’m Aysha. I’m a software engineer who loves building projects and learning how things work. Check out some of my projects, research, and open-source contributions.
Open-source work merged into GNU, Google Gemini CLI, NVIDIA Sirius, and Rust coreutils.
Every project has taught me something and made me a better programmer and engineer.
I built a dependency-free TCP/IP stack in Rust, then drove it through Linux TUN/TAP to prove Ethernet, ARP, IPv4, ICMP, UDP, and TCP interoperability end to end.
Impact7.6 Gbps read · 4.6 Gbps write through Linux TAP · 1,024 concurrent TCP connections · 28 protocol + Linux interoperability checks
I built a durable C++ key-value store that combines an LSM engine, key-value separation, crash recovery, and Raft consensus behind a small API.
Impact33,800 replicated writes/s · 8 clients · 12× faster writes for 16 KiB values · 65× throughput gain from group commit
I implemented a 135M-parameter decoder-only language model in PyTorch, matched the reference model, then added optimized decoding, LoRA fine-tuning, and DPO preference alignment.
Impact100% top-1 reference agreement · 8.50× faster decode throughput · 0.73% trainable parameters with LoRA
I liked how Charmbracelet’s Wish could turn a Go terminal app into an SSH experience, but I could not find that bridge for Python’s Textual ecosystem. So I created Textish and remain its active maintainer: import a Textual app, call serve, and let anyone open it with an ordinary SSH client.
Impact3,000+ PyPI downloads · One shared Python interpreter · Real SSH + PTY load harness
I like research that leaves the lab: work shaped with the people it affects, tested in the messiness of real use, and written clearly enough for someone else to build on.
ACM CHI 2026 · CO-AUTHOR
How can a health assistant earn trust when privacy, stigma, and misinformation shape what people are willing to ask?
I helped co-design and build the assistant, then translated what we learned in the field into concrete requirements for safer, culturally appropriate health AI.
ARXIV PREPRINT · 2026
When an AI coding agent produces plausible systems code, what evidence would make us trust it?
I designed the multi-agent methodology, built a Go-based tool to analyze source reachability through Clang, DWARF, and the linker, and rebuilt a legacy fuzzer as a concurrent, resumable, checkpointed Go tool for faster testing.
Formal study across computer systems, databases, AI, and production engineering.
/education/graduate/education/fellowship/education/undergraduateThe coffee and books keeping me curious away from the editor.
I love collaborating and working on interesting problems. If you have a research question, systems problem, or a good technical rabbit hole, I’d love to hear about it.
Prefer a terminal? Boot the command-line edition of my portfolio over SSH.