Oshani Seneviratne
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    • Enhancing Web Spam Detection through a Blockchain-Enabled Crowdsourcing Mechanism
    • The Feasibility of a Smart Contract "Kill Switch"
    • Enhancing Biomedical Collaboration through Advanced Data Sharing Mechanisms
    • Fed-RD: Privacy-Preserving Federated Learning for Financial Crime Detection
    • LLM-Based Code Generation for Querying Temporal Tabular Financial Data
    • Smart Contracts, Smarter Payments: Innovating Cross Border Payments and Reporting Transactions
    • Transforming Personal Health AI: Integrating Knowledge and Causal Graphs with Large Language Models
    • Harnessing the Future of Computing: Opportunities, Challenges, and Innovations
    • Using Large Language Models for Generating Smart Contracts for Health Insurance from Textual Policies
    • Deciphering Crypto Twitter
    • Navigating the Chaos: The Sandbox Network Analysis
    • A Differentially Private Blockchain-Based Approach for Vertical Federated Learning
    • Decentralized, Explainable, and Personalized Mental Health Monitoring
    • Effective Data Distillation for Tabular Datasets
    • Explanations of Symbolic Reasoning to Effect Patient Persuasion and Education
    • LLM-powered Preference Learning from Natural Language
    • Neurosymbolic Methods for Food Computing
    • Predicting Depression and Anxiety: A Multi-Layer Perceptron for Analyzing COVID-19 Mental Health Impact
    • Support and Scandals in GameFi DApps: A Network Analysis of The Sandbox Transactions
    • Towards Computable and Explainable Policies Using Semantic Web Standards
    • Using Large Language Models for Generating Smart Contracts for Health Insurance from Textual Policies
    • Semantics-based Framework for Incentivized Research Data Sharing
    • A Concise Ontology to Support Research on Complex, Multimodal Clinical Reasoning
    • Accountable Bench-to-Bedside Data-Sharing Mechanism for Researchers
    • Assessing Scientific Contributions in Data Sharing Spaces
    • Challenges and Insights for US Initial Coin Offerings
    • Characterizing Common Quarterly Behaviors in DeFi Lending Protocols
    • Decentralization: The Future of Online Social Networking
    • Decentralized Data Collection via Swarm Contracts: Study on Crowd-Sourced Google Maps
    • Decentralized Framework for Collection and Secure Storage of Google Street View Data: Case Study
    • DeFi Survival Analysis: Insights into Risks and User Behaviors
    • DeFi Survival Analysis: Insights Into the Emerging Decentralized Financial Ecosystem
    • Enabling Cross-Language Data Integration and Scalable Analytics in Decentralized Finance
    • Enabling Data Interoperability for Decentralized, Smart, and Connected Health Applications
    • Explanation Ontology: A General-Purpose, Semantic Representation for Supporting User-Centered Explanations
    • Exploring the Use of Large Language Models for Generating Decision Logic and Smart Contracts for Healthcare Processes from Natural Text
    • Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes
    • Linking the World's Information: Essays on Tim Berners-Lee’s Invention of the World Wide Web
    • LLM-augmented Preference Learning from Natural Language
    • MentalHealthAI: Utilizing Personal Health Device Data to Optimize Psychiatry Treatment
    • Personal health knowledge graph construction using Internet of Medical Things
    • PredictChain: Empowering Collaboration and Data Accessibility for AI in a Decentralized Blockchain-based Marketplace
    • Semantically Enabling Clinical Decision Support Recommendations
    • Tim Berners-Lee's Research at the Decentralized Information Group at MIT
    • Translating Clinical Decision Logic Within Knowledge Graphs to Smart Contracts
    • Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination
    • Web 3.0 Meets Web3: Exploring the Convergence of Semantic Web and Blockchain Technologies
    • Towards Smarter, Efficient and Trusted Insurance Marketplaces through Computable Contracts
    • Blockchain and IoT Enhanced Clinical Workflow
    • Blockchain for Social Good: Combating Misinformation on the Web with AI and Blockchain
    • Blockchain Interoperability Landscape
    • Collaboratively Learning Optimal Patient Outcomes Using Smart Contracts in Limited Data Settings
    • Data-driven Analysis of Remote Work in China during the COVID-19 Pandemic
    • Development of AI-Enabled Apps by Patients and Domain Experts Using the Punya Platform: A Case Study for Diabetes
    • Explainable Clinical Decision Support: Towards Patient-Facing Explanations for Education and Long-Term Behavior Change
    • Health Data Management for Internet of Medical Things
    • Incentivized Research Data Sharing, Reusing and Repurposing with Blockchain Technologies
    • Managing Collaborative Tasks within Heterogeneous Robotic Swarms using Swarm Contracts
    • Semantic Technologies for Clinically Relevant Personal Health Applications
    • Significant Digits: Using Large-Scale Blockchain Data to Predict Fraudulent Addresses
    • Simplifying Complex Healthcare Needs With Blockchain and Internet of Medical Things
    • BlockIoT: Blockchain-based Health Data Integration using IoT Devices
    • Applying personal knowledge graphs to health
    • Blockchain-Based Mechanism for Robotic Cooperation Through Incentives: Prototype Application in Warehouse Automation
    • BlockIoT-RETEL: Blockchain and IoT Based Read-Execute-Transact-Erase-Loop Environment for Integrating Personal Health Data
    • Data Provenance and Accountability on the Web
    • Designing for AI Explainability in Clinical Context
    • Enhancing Clinical Relevance of Health Behavior Insights via Semantics
    • Healthy Food Recommendation and Explanation Generation using a Semantically-Enabled Framework
    • Identifying Ingredient Substitutions Using a Knowledge Graph of Food
    • Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case
    • Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case
    • Mobile App Development for the Semantic Web of Things with Punya
    • Personal Health Data Integration and Intelligence through Semantic Web and Blockchain Technologies
    • Personal health knowledge graph for clinically relevant diet recommendations
    • Provenance in Data Science
    • Rapid Prototyping of Mobile Apps for Clinical Research using Semantic Web Technologies.
    • Semantic Modeling for Food Recommendation Explanations
    • Smart Contracts Enabling Future of Work
    • The Punya Platform: Building Mobile Research Apps with Linked Data and Semantic Features
    • Towards a Framework for Data Excellence in Data-Centric AI: Lessons from the Semantic Web
    • A Descriptive Analysis of US Initial Coin Offerings
    • A Survey on Personal Health Knowledge Graphs
    • A Two-Step Framework for Parkinson’s Disease Classification: Using Multiple One-Way ANOVA on Speech Features and Decision Trees
    • Applying Learning and Semantics for Personalized Food Recommendations?
    • Directions for Explainable Knowledge-Enabled Systems
    • Explanation Ontology in Action: A Clinical Use-Case
    • Explanation Ontology: A Model of Explanations for User-Centered AI
    • Foundations of Explainable Knowledge-Enabled Systems
    • Knowledge Extraction of Cohort Characteristics in Research Publications
    • Semantic Graph Analysis to Combat Cryptocurrency Misinformation on the Web
    • Semantics-driven ingredient substitution in the FoodKG
    • Swarm Contracts: Smart Contracts in Robotic Swarms with Varying Agent Behavior
    • Reflections on Successful Research in Artificial Intelligence: An Interview with Yolanda Gil
    • Reflections on Successful Research in Artificial Intelligence: An Introduction
    • Reflections on the Ingredients for Success in AI Research: An Interview with Arvind Gupta
    • Visualization of provenance data
    • A Proposal for Account Recovery in Decentralized Applications
    • A Semantic Platform for Developing Data-Intensive Mobile Apps
    • Abductive Reasoning over Health Data and Clinical Guidelines
    • Automating Population Health Studies through Semantics and Statistics Semantic Statistics
    • Enabling Trust in Clinical Decision Support Recommendations through Semantics
    • FoodKG Enabled Q&A Application
    • FoodKG: A Semantics-driven Knowledge Graph for Food Recommendation
    • G-Prov: Provenance management for clinical practice guidelines
    • Improving Transparency of Clinical Guidelines Through Semantic Knowledge Representation and Reasoning
    • IoT Application Development Using MIT App Inventor To Collect and Analyze Sensor Data
    • Leveraging Standards Based Ontological Concepts in Distributed Ledgers: A Healthcare Smart Contract Example
    • Making Study Populations Visible through Knowledge Graphs
    • Making Study Populations Visible Through Knowledge Graphs
    • Making Study Populations Visible Through Knowledge Graphs
    • Modeling and Analyzing Cohort Descriptions in Research Studies
    • Ontology Aided Smart Contract Execution for Unexpected Situations
    • Ontology-Enabled Analysis of Study Populations
    • Ontology-Enabled Breast Cancer Characterization
    • Representing study populations in scientific literature in knowledge graphs
    • Strengthening Smart Contracts to Handle Unexpected Situations
    • G-PROV: A Provenance Encoding Structure for Guideline Evidence
    • Improving Identified Comorbidities using Semantically Annotated Disease Graph
    • Knowledge Integration for Disease Characterization: A Breast Cancer Example
    • Knowledge Representation and Reasoning for Breast Cancer
    • Ontology-enabled Breast Cancer Characterization.
    • Semantic Modeling of Cohort Descriptions in Research Studies
    • Making Computer Science Attractive to High School Girls with Computational Thinking Approaches: A Case Study
    • Augmenting Provenance Records with Trust in Enterprise Applications
    • Accountable Systems: Enabling Appropriate Use of Information on the Web
    • Developing Mobile Linked Data Applications
    • Enabling privacy through transparency
    • Democratizing mobile app development for disaster management
    • Policy Aware Geospatial Data
    • Augmenting the web with accountability
    • Policy Aware Social Miner
    • WebBox: Supporting Decentralised and Privacy-respecting Micro-sharing with Existing Web Standards
    • Usage Restriction Management for Accountable Data Transfer on the Web
    • HTTPA: Accountable HTTP
    • Remix Culture on the Web: A Survey of Content Reuse on Different User-Generated Content Websites
    • Detecting Creative Commons License Violations on Images on the World Wide Web
    • Framework for Policy Aware Reuse of Content on the WWW
    • On integration issues of site-specific apis into the web of data
    • Policy-Aware Content Reuse on the Web
    • Public Policy: Mashing-up Technology and Law
    • The Point of View Axis: Varying the Levels of Explanation Within a Generic RDF Data Browsing Environment
    • An Extensible Computer Vision Application for Blood Cell Recognition and Analysis
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Reflections on the Ingredients for Success in AI Research: An Interview with Arvind Gupta

Nov 1, 2019·
Arvind Gupta
,
Biplav Srivastava
,
Daby Sow
,
Ching-Hua Chen
,
Oshani Seneviratne
· 0 min read
Cite DOI URL
Type
Journal article
Publication
AI Magazine
Last updated on Nov 1, 2019
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