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Phi Labs: Where Science Meets Transformation
Phi Labs is Quantiphi’s R&D powerhouse, driving next-generation AI innovation with real-world impact. From pioneering advances in generative AI and digital twins to solving complex challenges in life sciences, Phi Labs explores emerging frontiers before they become mainstream.
Our multidisciplinary teams of researchers and engineers collaborate to translate deep scientific exploration into enterprise-ready solutions—strengthening Quantiphi’s position as a leader in applied AI and setting new standards for responsible, future-ready innovation.
Phi Labs Growth Journey
2018-2020
Q R&D Established
2021
First Patent Filed, Kaggle Success
2022
Advanced Research & Strategic Collaborations
2023
GenAl Innovations
2024
Leadership in Al Research
2025
Continuing Breakthrough Research
Foundations & First Milestones
- Speech-to-Text for Finance
- 3D-GANs for seismic imaging
- No-Code MLOps
- Sign language detection Real-time demographic analysis
- Few-shot crop disease detection
- Lung disease AI-explanations
- Blood disorder detection
Research Publications
Explore groundbreaking research published by Phi Labs in leading journals, publications, and conferences.
Search-Based Risk Feature Discovery in Document Structure Spaces under a Constrained Budget
ACM GECCO, San José, July 2026
Stop Thinking, Start Looking: Efficient Post-Training for Multimodal Document Question Answering via Reasoning-Free Alignment
EMM-QA Workshop, ICML, Seoul, July 2026
APLE: A Framework for Adaptable and Personalized Live Explainability for Recommender Systems
ACM Web Science Conference, Germany, May 2026
PROTEUS: SLA-Aware Routing via Lagrangian RL for Multi-LLM Serving Systems
EuroMLSys, Edinburgh, April 2026
Memories that Discriminate: Detecting and Correcting Bias in Personalized Hiring Agents
ICLR AFAA Workshop, Rio de Janeiro, April 2026
How AI Learns the Laws of Physics: Building Smarter Engineering Systems
Invited Talk at American Society of Mechanical Engineers (ASME) E-Fest Tech Connect (Virtual), Mar 2026
From Personalization to Prejudice: Bias and Discrimination in Memory-Enhanced AI Agents for Recruitment
ACM International Conference on Web Search and Data Mining (WSDM), San Diego, Feb 2026
State of Health Estimation of Batteries Using a Time-Informed Dynamic Sequence-Inverted Transformer
AI for Time Series (AI4TS) Workshop at AAAI Conference 2026, Singapore, Jan 2026
DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting
Deployable AI Workshop at AAAI Conference 2026, Singapore, Jan 2026
Intelligent Human-Machine Partnership for Manufacturing: Enhancing Warehouse Planning through Simulation-Driven Knowledge Graphs and LLM Collaboration
International Workshop on Addressing Challenges and Opportunities in Human-Centric Manufacturing at AAAI Conference 2026, Singapore, Jan 2026
Enhanced Neo-antigen prioritization for CAR-T Therapy byfusion of Protein Language Model embeddings with PSSM Scores
International Conference on Genome Informatics ISCB-Asia (GIW XXXIV ISCB-Asia 2025), Hong Kong, Dec 2025
GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
International Conference on Applied AI and Scientific Machine Learning (CASML), IISc Bengaluru, Dec 2025
Thinking in Many Modes: How Composite Reasoning Elevates Large Language Model Performance with Limited Data
NeurIPS 2025 Workshop on Efficient Reasoning, San Diego, Dec 2025
ORPO-Distill: Mixed-Policy Preference Optimization for Cross-Architecture LLM Distillation
NeurIPS 2025 Workshop on Efficient Reasoning, San Diego, Dec 2025
GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
International Conference on Applied AI and Scientific Machine Learning (CASML), IISc Bengaluru, Dec 2025
A Multi-Objective Genetic Algorithm for Healthcare Workforce Scheduling
MODeM 2025 Workshop at the European Conference on Artificial Intelligence (ECAI), Bologna, Oct 2025
IDPFlow: A No-Code Agentic Framework for Multimodal Intelligent Document Processing
Industry Demos, ACM Multimedia, Dublin, Oct 2025
AMR-CSI: Adaptive Multimodal RAG for Cold Start Indexing
MMGR Workshop at ACM Multimedia, Dublin, Oct 2025
DocAnnot: Accelerating the Creation of Key Information Extraction Datasets with GenAI-Powered Auto-Annotation
ICDAR, China, Sep 2025
Leveraging Knowledge Graphs and LLM Reasoning to Identify Operational Bottlenecks for Warehouse Planning Assistance
KDD 2025 Workshop on AI for Supply Chain 2025, Toronto, Aug 2025
GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations
CO-BUILD Workshop at ICML 2025, Vancouver Convention Center, Canada, July 2025
HI-SQL: Optimizing Text-to-SQL Systems through Dynamic Hint Integration
IJCNN, Rome, June-July 2025
Knowledge Graph Based Repository-Level Code Generation
ICSE Conference Workshop (LLM4Code), Ottawa, May 2025
Evolutionary Policy Gradient Based Optimization For Small Molecule Drug Discovery
GEM workshop at ICLR, Singapore, April 2025
Accelerated Gradient-Based Design Optimization via Differentiable Physics Informed Neural Operator for Composite Materials Processing
AI for Materials (AI4MAT) Workshop at ICLR, Singapore, April 2025
An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study
Engineering Applications of Artificial Intelligence, Volume 142, 109886, Feb 2025
FB-HyDON: Parameter-Efficient Physics-Informed Operator Learning of Complex PDEs via Hypernetwork and Finite Basis Domain Decomposition
Machine Learning for Physical Sciences Workshop (ML4PS), Neural Information Processing Systems (NeurIPS), Vancouver, Dec 2024
A Hyper Physics-Informed Neural Network For Predicting Heat Transfer Patterns During The Curing Process In Aerospace Composite Manufacturing
ASME International Mechanical Engineering Congress and Exposition (IMECE), Portland, Nov 2024
Leveraging Latent Evolutionary Optimization for Targeted Molecule Generation
IEEE WCCI Yokohama, Japan, July 2024
An Advanced Physics-Informed Neural Operator for Comprehensive Design Optimization of Highly-Nonlinear Systems: An Aerospace Composites Processing Case Study
AI for Science workshop (AI4Science), International Conference on Machine Learning (ICML), Vienna, June 2024
Mitigating Factual Inconsistency and Hallucination in Large Language Models
WSDM Mérida, Yucatán, March 2024
Automated Tailoring of Large Language Models for Industry-Specific Downstream Tasks
WSDM Mérida, Yucatán, March 2024
Accelerating Pharmacovigilance using Large Language Models
WSDM Mérida, Yucatán, March 2024
Synergistic Fusion of Graph and Transformer Features for Enhanced Molecular Property Prediction
CNB-MAC Workshop Houston, ACM-BCB Conference Houston, Texas, Sep 2023
PINNs for Astrophysical shocks in gravitationally stratified environments
Machine Learning: Science and Technology, IOP Publishing Group, Volume 4, Aug 2023
Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents
Journal of Anaesthesia and Pain Medicine, ISSN: 2474-9206, May 2023
Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents
IEEE Conference on Big Data - Osaka, Japan, Dec 2022
Our Patents
Explore Quantiphi’s granted and filed patents driving innovation in AI-first digital engineering.
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