Parsa's personal web

Parsa's personal web

Bioinformatician

Ownership

less than 1 minute read

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I am sitting in an airplane. The guy next to me came earlier; he claims that he owns the armrest that we are supposed to share. I think about ownership. Can someone gain ownership because they came earlier?

I get off and sit on a metro, see a pregnant woman, and give her my seat. Can someone pass ownership to someone else?

Finally, I am home, watching a movie which is nothing but a long number made of 0s and 1s. Can someone own a number?

My girlfriend calls; she cheated on me. I get angry—do I feel I own her?

She is pregnant and wants an abortion. Does she own the baby?

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PeriodTime / wkAdvanced programmingSoftware devRLBayesianDeliverable
Q1 (Sep–Nov 2025)11h (4/3/2/2)Python internals (C-API, buffer protocol), NumPy/SciPy memory model; vectorization & numba; pick C++20+pybind11 or Rust+pyo3 for extensions; profiling basics (cProfile, perf)Git strategies, pytest + coverage, mypy/ruff, packaging with poetry/pdm; CLI design; docs with Sphinx/MkDocs; CI via GitHub Actions & pre-commitRefresher: MDPs/bandits; implement tabular DP/MC, ε-greedy; Gymnasium intro; clean-from-scratch codeProbability refresher; conjugate models; prior/posterior predictive checks; PyMC or Stan basics; ArviZ diagnosticsTiny PyPI package (bio kernel or parser), benchmarks + doc site
Q2 (Dec 2025–Feb 2026)10h (4/2/2/2)Native acceleration: C++/Rust ext modules; cache-aware data layouts; PyTorch custom ops shim; flamegraphs; microbenchmarks; intro GPU via Triton or CUDA kernelsRepro/data: DVC for datasets, dataset cards; semantic versioning; release wheels (Linux/Mac)Policy Gradient (REINFORCE) from scratch; advantage baselines; experiment tracking (MLflow/W\&B)Hierarchical models; GLMs; HMC/NUTS tuning; LOO/WAIC model comparisonAccelerated op (e.g., k-mer tally/UMI dedupe) as a PyTorch/JAX extension + reproducible DVC pipeline
Q3 (Mar–May 2026)11h (3/3/3/2)GPU depth: memory coalescing, warp/wavefront basics; streams & async; JAX jit/pjit mental modelWorkflow engines: Snakemake/Nextflow + Docker; config mgmt with Hydra; API sketch with FastAPIValue-based RL: DQN (clean-room), target nets, replay buffers; sanity-check OOD & reward scalingGaussian Processes for time-series expression; sparse/inducing points; calibrationEnd-to-end pipeline (Nextflow) producing features → API serving a GPU-accelerated op; DQN repo with reproducible results
Q4 (Jun–Aug 2026)10h (3/2/3/2)HPC touches: SIMD/AVX, OpenMP; SLURM; distributed training intro (FSDP/torch.distributed)Observability: metrics/logging/tracing; perf budgets; simple K8s deploy or autoscaling containerPPO/A2C with robust training loops; eval protocol; basic safe/constrained tricksBayesian deconvolution for multi-omics; VI/ADVI; prior sensitivity & SBCYear-capstone: open-source “fast-omics-kernels” + preprint-style tech report OR “RL-guided assay selection (sim)” with Bayesian uncertainty; public demo & docs

Exploring Spatial Multi-Omics Integration: An Interactive Infographic

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This infographic translates complex scientific concepts into an easily digestible visual narrative, covering everything from data acquisition challenges to the latest deep learning integration methods and their applications in disease understanding.