3. Data, Science & AI

Applies statistical methods to correct for multiple comparisons in hypothesis testing, reducing false positive rates in data analysis.

Provides fast detector simulation for high-energy physics phenomenology and Beyond Standard Model (BSM) research studies.

Enables formalization of classical mathematical proofs and theorems through an interface with Isabelle/HOL.

Identifies structural genomic variants including CNVs, inversions, translocations, and complex rearrangements in genomic data.

Assesses space debris collision risks and plans mitigation strategies using orbital data and computational models.

Automates hypothesis generation through AI-powered abductive reasoning and knowledge graph traversal for research and analysis.

Enables symbolic computation, algebra, and calculus operations through seamless integration with Mathematica/Wolfram Language.

Optimizes project portfolio selection using mathematical optimization to maximize returns under specified constraints.

Generates comprehensive model cards adhering to Google's model card framework for transparent AI model documentation.

Enables synthesis and verification workflows using Counterexample-Guided Abstraction Refinement (CEGAR).

Validates Jupyter notebook reproducibility by checking code execution, dependencies, and data sources for consistent results.

Analyzes customer reference calls, NPS scores, and churn patterns to identify retention opportunities and improve customer experience.

Performs BLAST-based sequence similarity searches, homology detection, and database queries for bioinformatics analysis.

Analyzes social network structures using centrality measures, community detection, and visualization tools for network dynamics insights.

Provides AI/ML model security testing including adversarial example generation, robustness analysis, and ART framework integration.

Enables LabVIEW-based control of instruments and real-time data acquisition for DAQ systems and hardware integration.

Generates constitutional AI prompts and safety guardrails to ensure ethical, aligned LLM outputs and prevent harmful behavior.

AI-driven tool to maximize warehouse labor efficiency through optimized workforce planning and task assignment.

Configures observability and debugging for LangChain and LangGraph agents in LLM applications using LangSmith.

Enables programmatic access to the zbMATH Open database for searching and retrieving mathematical literature and reviews.

Develops trajectory planning and motion control algorithms for robotics and autonomous systems.

Analyzes microbiome data through QIIME2 for 16S rRNA profiling and microbial diversity metrics in biological research.

Provides expert guidance on MongoDB schema design, aggregation pipelines, indexing strategies, and performance tuning for optimal data management.

Generates text embeddings in batches with caching, rate limiting, and multi-provider support for efficient RAG pipeline implementation.