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Research Topics in AI/ML/DL, Neural Networks, Computer Vision, Robotics

Washington DC_100423A
[Washington DC, USA]
 
 

1. Knowledge Representation and Reasoning (KR)

  • Reasoning and inference
  • Real-time inference
  • Commonsense reasoning
  • Qualitative reasoning, reasoning about physical systems
  • Reasoning about actions and change, action languages
  • Reasoning about constraints, constraint programming
  • Reasoning about knowledge, beliefs, and other mental attitudes
  • Computational aspects of knowledge representation
  • Concept formation, similarity-based reasoning
  • Contextual reasoning
  • Decision making
  • Argumentation
  • Belief revision and update, belief merging, information fusion
  • Description logics
  • Explanation finding, diagnosis, causal reasoning, abduction
  • Geometric, spatial, and temporal reasoning
  • Inconsistency- and exception-tolerant reasoning, paraconsistent logics
  • KR and autonomous agents and multi-agent systems
  • KR and cognitive robotics
  • KR and cyber security
  • KR and education
  • KR and game theory
  • KR and machine learning, inductive logic programming, knowledge acquisition
  • KR and natural language processing and understanding
  • KR and the Web, Semantic Web
  • Knowledge graphs and open linked data
  • Knowledge representation languages
  • Logic programming, answer set programming
  • Modeling and reasoning about preferences
  • Multi- and order-sorted representations and reasoning
  • Nonmonotonic logics, default logics, conditional logics
  • Ontology and epistemology
  • Ontology evolution and dynamics
  • Ontology formalisms and models
  • Ontology-based data access, integration, and exchange
  • Applications of KR
  • Philosophical foundations of KR
  • Uncertainty, vagueness, many-valued and fuzzy logics 
  • Knowledge-based systems (knowledge acquisition, knowledge discovery and data mining, knowledge representation and management)
  • Knowledge media technologies


2. Smart Technology

  • Pervasive computing and ambient intelligence 
  • Hybrid intelligent systems 
  • Intelligent system architectures 
  • Intelligent machinima generation
  • Explainable recommendation and search
  • Intelligent visual computing
  • Intelligent tutoring systems 
  • Intelligent disaster warning system
  • Intelligent user interfaces
  • Visual intelligence
  • Neuromorphic computing and AI
  • Anticipatory computing
  • Bayesian networks 
  • Knowledge-base and theory refinement
  • Graph mining
  • Knowledge discovery (data mining, text mining, and web mining)
  • Data mining and knowledge management  
  • Large scale distributed knowledge management
  • Information fusion for decision making under uncertainty
  • Secure distributed learning
  • Data and knowledge representation standards
  • Domain-driven actionable knowledge discovery 
  • AI-optimized Hardware 
  • Biometrics 
  • Multimedia & cognitive informatics 
  • Pattern recognition 
  • Data clustering
  • Computational social science 
  • Computational ecology 
  • Computational behavioral science 
  • Computational medicine
  • Reasoning and evolution 
  • Evolutionary computation
  • Computational intelligence 
  • Neural computation
  • Brain-computer interfaces & computational neuroscience


3. Social Computing and Web Intelligence: Theory and Applications

  • Social media analytics
  • Social media mining
  • Web intelligence
  • Web search engines
  • Intelligent web mining and applications
  • Intelligent web personalization
  • Web intelligence applications & search 
  • Semantic web techniques and technologies 
  • Web mining and ontology construction
  • Social informatics
  • Mobile crowdsourcing
  • Crowdsourcing to understand website privacy policies
  • Learning algorithms for gleaning semantic and structured knowledge from massive social media and web data
  • Information extraction
  • Intelligent web-based systems


    4. Embodies and Ambient Intelligence  

    • Embodied Intelligence, Sensors and Robotics
    • Computer Vision
    • Ontology
    • Pervasive computing
    • Augmented reality
    • Radio frequency identification
    • health care system
    • Smart cities
    • Internet of Things
    • Ambient asisted living
    • Smart healthcare
    • Intelligent transportation
    • Data science
    • Sensing and sensor networks
    • Affective computing
    • Agents and multi-agent systems
    • Context-aware pervasive systems


    Venice_Italy_020321A
    [Venice, Italy - Civil Engineering Discoveries]

    4. Artificial Intelligence (AI)

    • AI models
    • Responsible and explainable AI
    • AI environments
    • Self-supervised representation learning 
    • Human activity recognition
    • Action understanding 
    • Game theory 
    • AI at scale
    • Wireless AI perception
    • Physics Informed Deep Learning
    • Physics Informed Machine Learning
    • Multi-agent systems
    • Multi-Agent systems and distributed AI
    • Emerging intelligent technologies and applications 
    • Intelligent computer networks and systems
    • Collective intelligence
    • Commonsense reasoning
    • Probabilistic reasoning 
    • Computer model (simulator) and model uncertainty
    • AI algorithms 
    • On-device AI
    • Generative AI and Large Language Models (LLMs) 
    • AI tools & applications
    • AI accelerators 
    • Photonic Accelerators for AI
    • Heuristic and AI planning strategies and tools 
    • Computational theories of learning
    • Artificial narrow intelligence (ANI), Artificial general intelligence (AGI), Artificial superintelligence (ASI)
    • Artificial intelligence and information agents on the Internet
    • Artificial intelligence systems integration
    • Hybrid intelligent systems
    • Artificial life (ALife or A-Life)
    • Conscious AI
    • AI hallucinations
    • AI and Intelligent agents
    • State-space problem representations
    • Uninformed and heuristic search
    • Game playing and adversarial search
    • Logical agents
    • Constraint satisfaction problems
    • New learning systems and styles
    • Intelligent user interfaces
    • Brain–computer interface/Mind-machine interface
    • Social computing and crowdsourcing systems
    • Defense AI technology
    • AI for social good 
    • Decision management 
    • Knowledge management and business intelligence
    • Learning algorithms for gleaning semantic and structured knowledge from massive social media and web data
    • Business intelligence systems
    • Business process management and workflow mining
    • Genetic algorithms and evolutionary computing
    • Pattern discovery (association analysis, anomaly detection, and cluster analysis) 
    • Spatiotemporal data analysis
    • Data mining and predictive modeling
    • Engineering informatics
    • Cheminformatics
    • Materials informatics
    • Approximate inference for graphical models
    • Multimedia techniques for enhanced accessibility systems
    • Modeling and organizing large-scale Internet image collections
    • Feedback motion planning for robotics
    • Financial and stock market monitoring and prediction
    • Emerging intelligent technologies

    -- Quantum AI

    • Quantum machine learning,
    • Quantum-inspired soft computing,
    • Hybrid classical-quantum neural network models,
    • Qubit- and qutrit-based quantum-inspired neural network models,
    • Quantum optimization,
    • Hybrid classical-quantum algorithms
    • Variational quantum algorithms
    • Quantum metaheuristics


    5. Machine Learning (ML)

    • Supervised learning
    • Unsupervised learning
    • Semi-supervised learning
    • Deep learning vs. shallow learning
    • Machine learning algorithms and theory 
    • Learning and inference
    • Feature engineering
    • Feature selection 
    • Feature transformations
    • Shapley value in machine learning
    • Causal modeling and machine learning 
    • Causal structure learning and inference 
    • Characterization of causal information in observational data 
    • Understanding machine learning tasks in light of causality 
    • Machine learning methods exploiting causal knowledge 
    • Efficient causal discovery in large-scale data 
    • Real-world problems for causal analysis.
    • Applied machine learning
    • Learning dynamical systems
    • Learning algorithms for latent variable models 
    • Fine tuning and transfer learning in ML
    • Latent social characteristics learning
    • Machine learning for intelligent IoT
    • Reinforcement learning
    • Advanced learning technologies
    • Data mining and machine learning tools
    • Machine learning in signal processing
    • Reducing dimensionality with principal component analysis (PCA)
    • Ontology
    • Storytelling in games 
    • Style transfer
    • Ethical computing
    • Affective computing
    • Cognitive machines
    • Cognitive computing systems
    • Cognitive modeling
    • Medical and diagnostic systems
    • Bioinformatics using intelligent and machine learning techniques
    • Autonomous multi-robot systems
    • Automated planning and scheduling
    • Automatic control 
    • Robotic process automation
    • Robot planning and control
    • Human-robot interaction
    • Machine perception (machine vision, machine hearing, machine touch)
    • Multi-modality 
    • Sensor machine learning 
    • Vision intelligence and machine learning
    • Machine deception
    • Machine perception
    • Machine learning platforms 
    • Distributed algorithms in machine learning
    • Machine listening and learning
    • Machine reading
    • Optimization methods for machine learning
    • Markov decision process
    • Sequential decision making
    • Interactive machine learning
    • Embedding and representation learning
    • Active learning
    • Transfer learning
    • Spectral learning
    • Statistical relational learning
    • Statistical methods for machine learning
    • Bayesian learning
    • Bayesian statistics
    • Improving learning efficiency 

     

    Budapest_Hungary_020421A
    [Budapest, Hungary - Civil Engineering Discoveries]

    6. Deep Learning (DL)

    • Deep learning and representation learning 
    • Neural networks and deep learning
    • Deep neural networks
    • Convolutional neural network
    • Manifold learning
    • Deep visualization
    • Deep learning and computer vision
    • Deep learning platforms
    • Deep learning hardware accelerators (GPUs, FPGAs, and TPUs)
    • Deep generative models
    • Deep reinforcement learning
    • Deep hashing
    • Deep reranking
    • Query expansion
    • Deep token pooling 

    -- The Main ML Disciplines

    • Regression
    • Classification
    • Clustering
    • Dimensionality Reduction
    • Ensemble Methods
    • Neural Nets and Deep Learning
    • Transfer Learning
    • Reinforcement Learning
    • Natural Language Processing
    • Word Embeddings


    7. Algorithms for ML/DL

    -- Commonly Used ML/DL Algorithms

    • Linear Regression
    • Logistic Regression
    • Decision tree
    • Linear Discriminant Analysis
    • Classification and Regression Trees
    • Naive Bayes
    • K-Nearest Neighbors (KNN)
    • Learning Vector Quantization (LVQ)
    • Support Vector Machines (SVM)
    • Random Forest
    • Boosting
    • AdaBoost
    • SVM
    • K-means Clustering
    • Apriori Learning Algorithm
    • PCA (Principal Component Analysis)
    • Dimensionality reduction 
    • Gradient boosting algorithm and AdaBoosting
    • Stable Diffusion algorithm (text-to-image)

    -- Statistical Methods for Machine Learning

    • Density Estimation 
    • Nonparametric Regression 
    • Linear Regression 
    • Sparsity
    • Nonparametric Sparsity
    • Linear Classifiers
    • Nonparametric Classifiers
    • Random Forests
    • Clustering 
    • Graphical Models 
    • Directed Graphical Models 
    • Causal Inference 
    • Minimax Theory 
    • Nonparametric Bayesian Inference 
    • Conformal Prediction 
    • Differential Privacy 
    • Optimal Transport and Wasserstein Distance 
    • Two Sample Testing 
    • Dimension Reduction 
    • Boosting 
    • Support Vector Machines 

     

    8. Artificial Neural Networks

    • Convolutional neural networks (CNNs)
    • Recurrent neural networks (RNNs)
    • Deep learning algorithms
    • Multi-layer feedforward neural networks
    • Adaptive Learning
    • Patter extraction and detection
    • Semantic meaning extraction from imprecise data 
    • Feedforward Neural Networks
    • Radial Basis Function Networks
    • Time delay neural network
    • Regulatory feedback network
    • Probabilistic neural network
    • Genetic Scale RNN
    • Holographic Associative Memory
    • Spiking Neural Networks
    • Cascading Neural Networks
    • Dynamic Neural Networks
    • Neuro-Fuzzy Networks
    • One Shot Associative Memory
    • Instantaneously Trained Networks
    • Hierarchical Temporal Memory
    • Oscillating Neural Network
    • Growing Neural Gas
    • Counter Propagation Neural Network
    • Hybridization Neural Network

     

    9. Natural Language Processing, Large Language Models, Generative AI, and Foundation Models

    - Natural Language Processing (NLP)

    • Linguistic Intelligence in AI
    • Computational linguistics and speech processing
    • Speech recognition systems
    • Text-to-speech synthesizers
    • Automated voice response systems
    • Automatic speech recognition
    • Language instruction materials
    • Biomedical natural language processing
    • Machine translation/multilingual processing
    • Information extraction and natural language processing
    • Natural language generation and understanding
    • Automatic text summarization
    • Natural language processing and computational linguistics
    • Natural language processing: algorithms and tools to extract computable information from Electronic Health Records (EHRs) and from the biomedical literature
    • Natural language learning
    • Natural language understanding (NLU) AI models
    • Language generation and conversational AI
    • Sentiment analysis (or opinion mining)
    • Sentiment analysis tools
    • Track brand sentiment
    • Language grounding with vision
    • Statistical relational learning
    • Transfer learning
    • Active learning
    • Auditory, speech and language processing
    • Text analytics and natural language processing (NLP)
    • Natural language processing and its connections with data mining, social science and vision
    • Spoken language understanding
    • Physical commonsense
    • Unsupervised speech processing
    • Automatic text summarization 
    • Speech processing and synthesis
    • Voice synthesis 
    • Text-to-Speech (TTS)
    • Speech recognition
    • Machine learning, natural language processing, and social media
    • Conversational search, recommendation, and QA systems 
    • Online handwriting and gesture recognition technology 
    • The Themes of NLP (Theme extraction, Sentiment analysis, Named entity recognition, Text summarization, Text classification, Topic modeling, Keyword extraction, Information extraction)
    • Prompt and prompt engineering
    • LLM fine-tuning vs prompt engineering

      - Large Language Models (LLMs)

      • LLM training
      • Efficient training
      • Tokenization
      • Human collaboration
      • Chatbots and virtual assistants
      • Healthcare applications
      • Limitations of LLMs, such as computational constraints, hallucinations, and limited knowledge 
      • Reduce and measure hallucinations
      • Optimize context length and context construction
      • Incorporate other data modalities
      • Make LLMs faster and cheaper
      • Design a new model architecture
      • Develop GPU alternatives
      • Make agents usable
      • Improve learning from human preference
      • Improve the efficiency of the chat interface
      • Retrieval-augmented generation (RAG)

      - Generative AI

      • Architecture and Model Design
      • Image generating and Manipulation
      • Natural Language Processing and Text Generation
      • Music and Audio Generation
      • Prediction and Video Generation
      • Unsupervised and Semi-Supervised Learning
      • Understanding and enhancing Latent Representations learnt by Generative Models
      • Multi-Modal and Cross-Modal Generation
      • Robustness and Fairness in Generative AI
      • Transfer Learning and Pre-Training
      • Generative Models That protect Data Privacy
      • Real-World Applications and Deployability
      • Multimodal Creativity and AI Collaboration

      Bergen_Norway_012721A
      [Bergen, Norway - eirikbjo]

      10. Foundation Models 

      • 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐌𝐨𝐝𝐞𝐥𝐬 𝐟𝐨𝐫 𝐓𝐢𝐦𝐞 𝐒𝐞𝐫𝐢𝐞𝐬
       

      11. Computer Vision

      • Optical character recognition (OCR)
      • Computer vision and speech understanding 
      • Vision and Language in Computer Vision
      • Vision sensor technology
      • Computer vision applications (autonomous navigation, visual surveillance, or content-based image and video indexing)
      • Fusing 3D scene reconstruction
      • 3D perception
      • Vision, language, and cognition 
      • Probabilistic graphical models
      • Computational photography
      • Medical vision
      • Computer vision and machine learning
      • Video understanding
      • Visual recognition and visual search
      • Large-scale image/video retrieval
      • Unsupervised visual discovery
      • Image and video segmentation
      • Vision and language
      • Video summarization.
      • Learning-based visual reconstruction 
      • Understanding video contents 
      • Visual sensing for ecology and conservation
      • Smart graphics
      • Graphics, human computer interaction, & user experience 
      • People counting tool
      • Colors detection
      • Object tracking in a video
      • Pedestrian detection
      • Hand gesture recognition
      • Human emotion recognition
      • Road lane detection
      • Business card scanner
      • License plate recognition
      • Handwritten digit recognition
      • Iris Flowers Classification 
      • Family photo face detection
      • LEGO Brick Finder
      • PPE Detection
      • Face mask detection
      • Vision-language models (VLMs)


      12. Machine Vision, Robotics and Robot Learning

      -- Machine Vision 

      •  Human Computer Interaction
      •  Pattern Recognition
      •  Image/Video Processing
      •  Intrusion Detection
      •  Brain-Machine Interface
      •  Geographic Information Systems
      •  Signal Processing
      •  Medical Diagnosis
      •  Segmentation Techniques
      •  Augmented/Virtual Reality
       -- Robotics and Robot Learning
      • Robot learning
      • Robotics and computational perception
      • Mobile robots
      • Robot navigation
      • Distributed robotics  
      • Wearable robotic systems
      • Networked robotic systems
      • Swarm robotics
      • Swarm intelligence
      • Microrobotics 
      • Soft robotics

       

      13. AI-driven Trustworthy, Secure, and Privacy-Preserving Computing (AidTSP)  

      • AI-driven TSP (Traveling Salesman Problem) computing
      • AI-driven TSP computing in IoT/CPS/Edge/Fog/Cloud paradigms
      • AI-driven TSP computing smart data and Big data paradigm
      • AI-driven TSP computing with blockchain
      • AI-driven TSP computing in activity recognition, HCI
      • AI-driven TSP with wearable devices, embedded HW and SW, and applications
      • AI-driven TSP with agent-based computing
      • AI-driven TSP with nature- and brain-inspired computing
      • AI-driven TSP computing against AI-driven malware and fault injections
      • AI-driven TSP computing against AI-driven supply chain & hardware attacks
      • AI-driven TSP computing in big data capture, classification, and analytics
      • AI-driven TSP computing with nano & micro-systems and quantum computing
      • AI-driven TSP computing in OS, virtualization, database, and software systems
      • AI-driven TSP measures, metrics, verification, and validation
      • AI-driven sensing, detection, prevention, and recovery against potential threats
      • AI-driven applied cryptography and security protocols
      • AI-driven defense against AI-driven threats/attacks
      • AI-driven data trust, system trust, service trust, application trust, etc.
      • TSP with learning methods (ML/DL/DRL/FL)
      • TSP, anonymity, and resilience analysis on AI
      • TSP with AI-driven data mining and knowledge discovery
      • TSP concerns with AI-driven technologies, such as GAN
      • TSP with reactive distributed AI, AI tools, and applications
      • Trustworthy ML, DL, DRL, and FL methods and tools
      • Trustworthy AutoML, AutoDL, and automatic control
      • Trustworthiness with AI-driven authentication, access control, & monitoring
      • Theoretical studies on big data system trustworthiness, privacy, and security
      • Fairness, explainability, accountability, reliability, and safety with AI

       

      14. The Popular DL Applications

      • Virtual Assistants 
      • Chatbots 
      • Healthcare 
      • Entertainment 
      • News Aggregation and Fake News Detection 
      • Composing Music 
      • Image Coloring 
      • Robotics 
      • Image Captioning 
      • Advertising 
      • Self Driving Cars 
      • Natural Language Processing 
      • Visual Recognition 
      • Fraud Detection 
      • Personalisations 
      • Detecting Developmental Delay in Children 
      • Colourisation of Black and White images 
      • Adding Sounds to Silent Movies 
      • Automatic Machine Translation 
      • Automatic Handwriting Generation 
      • Automatic Game Playing 
      • Language Translations 
      • Pixel Restoration 
      • Demographic and Election Predictions 
      • Deep Dreaming



       


       

       

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