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Research Area

Artificial Intelligence

Artificial intelligence research is the quest to build machines that can reason, learn, and act intelligently – to understand and reproduce human cognition. With increasingly complex algorithms, growing computing power, and the collection of greater amounts of data, society is on the verge of a fundamental transformation.

AI is already ubiquitous. It is used to recommend what you should buy online, to understand what you say to virtual assistants, to recognize who is standing next to you in a snapshot, to warn you when you are the target of phishing, and to detect when you are the victim of credit card fraud. The application of AI is spreading to more aspects of our everyday lives. AI will drive economic growth, boost innovation and tackle issues of global significance from healthcare delivery to food security to public safety.

Research Topics

  • Machine learning and deep learning: The most significant AI research breakthroughs in recent years have been in the related areas of machine learning and deep learning. Using machine learning, an algorithm can modify itself without human intervention to produce a desired result. It ‘feeds’ itself data and analyzes that data using deep learning, which is a system or network of algorithms, also known as an artificial neural network (ANN). The ANN mimics the operation of the human brain in analyzing unstructured data. These approaches have a wide spectrum of current and potential applications, from enabling self-driving cars to creating robotic assistants and companions to helping healthcare professionals diagnose patients faster and more accurately.
  • Robotics: AI and robotics have a symbiotic relationship – AI involves automated decision-making while robotics involves manipulating objects. Combining the two creates the ability to take effective or desired action in the real world and to acquire real-world data to adjust or improve performance. Visions of the future include robots and drones transporting goods to market, helping with routine surgical procedures, and providing personalized assistance to people with physical limitations.
  • Cognitive computing: Closely related to AI, cognitive computing involves the simulation of human thought processes in computerized models. It features self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the operation of the human brain. Cognitive computing enables computers to address complex situations characterized by uncertainty and ambiguity. The main aim of cognitive computing is to help humans with decision-making, for example, to enable accurate data analysis, create more efficient business processes, or improve customer experience.

Faculty


  • Dorothea Blostein
    Research Interests:
    • Biomechanics
    • adaptive tensegrity
  • Yuanzhu Chen
    Research Interests:
    • Computer networking
    • Mobile computing
    • Complex networks
    • Applied machine learning
  • Salimur Choudhury
    Research Interests:
    • Algorithms
    • Network Management and Optimization
    • Healthcare Resource Management
  • Steven Ding
    Research Interests:
    • Data Mining
    • Machine Learning
    • Security
  • Qingling Duan
    Research Interests:
    • machine learning
    • biomedical computing
    • bioinformatics
  • Gabor Fichtinger
    Research Interests:
    • computer assisted surgery, interventions
  • Sidney Givigi
    Research Interests:
    • Artificial intelligence
    • Machine Learning (reinforcement learning and deep learning)
    • Autonomous Vehicles
    • Robotics
  • Ting Hu
    Research Interests:
    • evolutionary computing
    • machine learning
    • artificial intelligence
    • complex networks
    • bioinformatics
  • Parvin Mousavi
    Research Interests:
    • Machine Learning in Computer Assisted Diagnosis and Interventions
    • Image-Guided Interventions
    • Ultrasound Imaging
    • Medical Image Computing
    • Computational Biology
    • Bioinformatics
    • Systems Biology
  • Christian Muise
    Research Interests:
    • Artificial Intelligence
    • Automated Planning
    • Model Understanding, Learning, and Acquisition
    • Goal-Oriented Dialogue Systems
  • Amber Simpson
    Research Interests:
    • Machine learning
    • Medical image analysis
    • Computer aided surgery
  • Catherine Stinson
    Research Interests:
    • bias and explanation in machine learning
    • computational psychiatry
    • embodied intelligence
    • community-led design
  • Yuan Tian
    Research Interests:
    • Software engineering
    • Applied machine learning
    • Recommender systems
    • Deep learning
    • Mining software repositories
  • Farhana Zulkernine
    Research Interests:
    • Big and Streaming Data Management and Analytics
    • Artificial Intelligence
    • Deep Learning and Decision Support Systems (DSS)
    • Cognitive Computing
    • Knowledge Management Systems
    • Cloud and Services Computing
All Research Faculty
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