3. Data, Science & AI

Analyzes time series data and generates forecasts using statistical and machine learning models.

Converts natural language problem descriptions into structured graph representations for data modeling and analysis in AI and data science workflows.

Performs Bayesian probabilistic reasoning including prior specification, posterior computation, and iterative belief updating in statistical models.

Optimizes experimental designs using Design of Experiments (DOE) principles for efficient data collection and analysis in scientific research.

Provides computational guidance for engine emissions calibration and aftertreatment system optimization using physics-based modeling.

Processes survey data for point clouds, generates Digital Terrain Models (DTMs), and handles coordinate transformations in geospatial applications.

Provides AI-driven pacing control and dynamic difficulty adjustment in game development to enhance player experience.

Validates medical imaging systems against DICOM standards to ensure interoperability and correct data handling in healthcare environments.

Assists in electric motor and drive unit design and optimization using computational physics simulations for electromagnetic and thermal analysis.

Optimizes LLM input prompts by compressing them to reduce token count and lower AI model costs.

Bioinformatics tool for detecting gene fusions in cancer genomic data using integrated detection algorithms for oncology research and diagnostics.

Provides Aspen HYSYS integration for dynamic simulation of chemical processes, including pressure-flow networks and process dynamics.

Analyzes power consumption data from embedded systems using power analyzers to optimize battery life and energy efficiency.

Processes mass spectrometry data for protein identification and quantification using the MaxQuant platform.

Enriches company and contact data by integrating with Clearbit's API for enhanced business intelligence and data quality.

Performs functional profiling of metagenomic data to identify metabolic pathways and microbial community functions.

Creates clear, actionable visual representations of analytical data to support informed decision-making processes.

Automates thermodynamic property model selection based on component characteristics and operating conditions for accurate property prediction.

Monitors data drift, model performance, and target drift in production ML systems with automated reporting.

Uses machine learning to predict customer churn and monitor engagement signals for proactive retention strategies.

Defines high-level specifications for program synthesis across multiple paradigms, enabling automated code generation from constraints.

Computational engine for simulating rainfall-runoff processes, flood frequency analysis, and watershed dynamics in hydrological systems.

Creates customizable dashboards for tracking essential startup metrics and KPIs, enabling data-driven decision making.

Sets up Microsoft Semantic Kernel for building AI agents that orchestrate multiple models and plugins in LLM-based workflows.