Groups
Intelligent Computer Systems Research Institute (ICSRI)
Research Fellow
Approaching its 40th anniversary, the ICSRI has grown alongside AI’s return to the mainstream, assembling leading researchers in machine learning, platforms, personalized medicine, blockchain, and—central to all of these—ethics, to advance theoretical, computational, and neuro-symbolic AI while probing the behavioral and human dynamics of how people interact with intelligent systems. Its members apply AI across healthcare, material science, and transportation, and engage the field’s deeper questions—machine rights, sentience, corporate robotics ethics, and the validation challenge of ensuring systems are no more biased than the humans they replace—where computational AI overlaps with social data science and cognitive neuroscience. As a center of excellence, the Institute advises businesses and policymakers worldwide, conducts and disseminates leading-edge research, consults for industry, government, and NGOs, trains corporate boards and executives, evaluates healthcare policy and economics, and convenes conferences and workshops for the wider community.
Associated works
edgar-sec-dev-team
Founder & Lead Developer
The edgar-sec-dev-team is a research-oriented engineering group building high-quality, open-source infrastructure for the acquisition, transformation, and analysis of U.S. SEC EDGAR filings, with an emphasis on reliable, reproducible, model-ready data systems spanning structured extraction, XBRL parsing, and the reconstruction of consistent financial time series across filings, companies, and reporting regimes. Its flagship project, edgar-sec, is a modular Python toolkit that abstracts EDGAR’s raw data formats behind a clean, extensible interface for researchers, developers, and quantitative analysts, emphasizing deterministic and reproducible pipelines, robust API and SDK design, cross-filing normalization and entity resolution, time-series reconstruction from disclosures, and integration with modern data workflows including pandas, polars, and dask. The team’s philosophy is grounded in research-grade software engineering, combining econometrics, machine learning, and systems design to produce tools suitable for both academic research and production-grade analytics.