2026 Conference Season
Active Causal Hypothesis Testing with Bayesian Generative Models for Drug Discovery
Oral presentation at the AIDD Workshop — fewer than 2% of AAAI submissions receive this honor. Integrates Bayesian optimization with generative AI and causal discovery for autonomous drug target identification.
Verified Agentic Pipelines: Self-Falsification in Multi-Agent Scientific Discovery
Oral at the LMReasoning Workshop. Polyculture agent ensembles with built-in self-falsification — every claim verified against ground truth before propagation, eliminating hallucination cascades.
Financial AI, Legal Tech, Drug Design & Materials Science
Nine additional papers across AIDD, AI4Research, AI-LAW, FinAI, and LMReasoning workshops spanning echo chamber detection in markets, neuro-symbolic regulation, de novo drug design, and physics-informed materials property prediction.
Biomedical AI, Drug Discovery & Verified Molecular Generation
Fourteen papers across 3 workshop tracks at the #2 ranked AI conference globally (Google Scholar h5-index: 304). Alzheimer's drug discovery, biomedical reasoning, causal molecular generation, and verified synthesis planning. Publishing alongside Google DeepMind and OpenAI.
Applied AI for Science: From Brain Resilience to Cancer Treatment
Six papers at the Applied AI for Science conference including 2 oral presentations. Topics spanning brain resilience modeling, high-content cell painting analysis, AI-optimized cancer treatment scheduling, and materials property prediction — all leveraging our ACHT and VAP architectures.
6 papers, 2 oral
Applied AI conference
2025 Conference Season
Active Causal Hypothesis Testing for Drug Target Discovery
Selected for the AI4D3 Drug Discovery Workshop at NeurIPS — the #1 ranked AI conference globally (Google Scholar h5-index: 337). Workshop organized by Harvard Medical School, Genentech/Roche, and AbbVie's Prescient Design team.
Architectural Immune System: Correcting Synthetic Fallacies in AI-Driven Science
Paper accepted at Stanford's Agents4Science Workshop. Advisory board includes Guido Imbens (Nobel Laureate, Stanford), Barbara Cheifet (Chief Editor, Nature Biotechnology), and Eric Topol (Scripps Research). Our framework for detecting and correcting AI hallucinations in scientific discovery.
Physics-Informed Surrogates for Verified Molecular Simulation
Poster at the European Machine Learning excellence network's ML4Molecules workshop. Physics-informed surrogate models that accelerate molecular dynamics by 100–1,000x while maintaining DFT-level accuracy.
Financial AI, Legal Reasoning & Graph-Based LLMs
Three papers at ACM's premier information and knowledge management conference across the FinAI and GMLLM workshops. Echo chamber detection in financial markets and neuro-symbolic regulatory compliance with provenance tracking.
AI for Robotics in Scientific Discovery
Invited speaker at the AIR4S Workshop at the premier robotics conference. Presenting our Verified Agentic Pipeline architecture for autonomous scientific experimentation.
Alzheimer's Drug Discovery & Causal Molecular Reasoning
Three papers at the ICLR-affiliated MLGenX workshop focused on Alzheimer's drug discovery. Generative models for neuroprotective compound design with causal ADMET prediction and verified synthesis planning.
ICLR-affiliated
Alzheimer's focus
Validated at the same venues where Google DeepMind, OpenAI, and Meta FAIR publish
NeurIPS (#1 GS h5:337)
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ICLR (#2 GS h5:304)
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AAAI (#4 GS h5:220)
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Stanford
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ELLIS
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CIKM
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IROS
Publishing alongside:
Google DeepMind
OpenAI
Meta FAIR
Microsoft Research
Stanford
MIT
CMU
Founded by David Scott Lewis
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AI Researcher Since the 1990s
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Former META EVP
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Stanford Affiliate