3. Data, Science & AI

Builds scalable data pipelines, ETL/ELT systems, and data infrastructure using Spark, Airflow, and dbt for data modeling and orchestration.

Extends transformer model context windows using RoPE, YaRN, ALiBi, and position interpolation for processing long documents (32k-128k+ tokens).

Provides a library for training and experimenting with reinforcement learning agents using algorithms like PPO and SAC in Gym environments.

Framework for building, simulating, and executing quantum circuits, supporting quantum algorithms and hardware integration.

Provides production-grade PDF processing for forms, tables, OCR, and batch operations with robust validation and error handling.

Comprehensive toolkit for building AI data pipelines including ETL workflows, vector embeddings, and knowledge graphs via CocoIndex library.

Provides genomic data analysis and visualization for NGS workflows, including BAM to bigWig conversion, QC metrics, and heatmaps for ChIP-seq, RNA-seq, and ATAC-seq.

Comprehensive reference for designing PostgreSQL database schemas, including data types, indexing, constraints, and performance patterns.

Generates evidence-based clinical decision support documents with statistical analysis, biomarker stratification, and regulatory compliance for pharmaceutical research.

Provides programmatic access to COSMIC database for querying cancer mutations, gene fusions, and mutational signatures in precision oncology research.

Enables exact symbolic computation in Python for algebra, calculus, equations, and mathematical expressions without numerical approximation.

Data framework for building LLM applications with RAG, featuring document ingestion, indexing, and querying for knowledge retrieval systems.

AI-powered speech-to-text model for multilingual transcription, translation, and language identification.

Creates scientific visualizations including line plots, bar charts, heatmaps, and 3D graphs for publication-ready figures in multiple formats.

Enables efficient out-of-core processing and analysis of massive tabular datasets (billions of rows) with lazy evaluation and visualization.

Programmatic PDF toolkit for extracting text and tables, creating, merging, splitting, and filling forms to enable document data analysis.

Python library for geospatial vector data analysis, enabling spatial operations, coordinate transformations, and map visualization with common formats.

Generates music and sound effects from text descriptions using AI models (MusicGen and AudioGen) built on PyTorch.

Provides molecular featurization tools for machine learning, including ECFP, MACCS, and ChemBERTa, to convert SMILES into features for QSAR and molecular ML.

Processes FCS flow cytometry files, extracting events and metadata into NumPy arrays and DataFrames for scientific data preprocessing.

Enables production deployment, monitoring, and scaling of ML models with MLOps, RAG systems, and LLM integration for enterprise AI solutions.

Optimizes AI model inference on CPU/GPU by quantizing models to 2-8 bits using GGUF format and llama.cpp, enabling deployment on consumer hardware.

Enables real-time AI-powered web searches using Perplexity models for current information, scientific literature, and source-cited answers via OpenRouter API.

Provides API access to openFDA data for drugs, devices, adverse events, recalls, and regulatory submissions to support safety research and analysis.