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[GIRE] RA Internship with a professor at UIUC, Computer Science Department
Hi, this is GIRE! Artificial intelligence in its broad and powerful forms is transforming every industry. Machine learning is becoming incredibly useful and pervasive in our society, from chatbots and predictive text, language translation apps, Netflix recommendations, social media feeds, self-driving cars, and even disease diagnosis. [What is machine learning?] Machine learning (ML) is an artificial intelligence (AI) that allows software applications to more accurately predict outcomes without being explicitly programmed. Machine learning algorithms use historical data to predict new output values. [Use of machine learning in the enterprise] Many of today's leading companies, such as Facebook, Google, and Uber, have made machine learning a central part of their operations. Machine learning can help companies identify trends in customer behavior and business operations patterns and support new product development. Other popular uses are fraud detection, spam filtering, malware threat detection, business process automation (BPA), and predictive maintenance. According to a 2020 Deloitte survey, 67% of organizations are using machine learning, and 97% plan to use it in the next year. Therefore, for many companies, machine learning has become an important competitive differentiator. [The Importance of Using Machine Learning] “In just the last five or 10 years, machine learning has become a critical way, arguably the most important way, most parts of AI are done,” said MIT Sloan professor Thomas W. Malone, the founding director of the MIT Center for Collective Intelligence. “Machine learning is changing, or will change, every industry, and leaders need to understand the basic principles, the potential, and the limitations,” said MIT computer science professor Aleksander Madry, director of the MIT Center for Deployable Machine. (source: mitslogan.mit.edu) [Machine Learning Research: Professor Harrison Zhao] Professor Harrison Zhao, a computer science professor at the University of Illinois Urbana-Champaign in the United States, uses these machine learning technologies to develop transfer learning (domain adaptation/generalization, multi-task/meta-learning), algorithm fairness, stochastic circuits and applications in natural language, and signal processing.  In particular, He stated that his long-term goal is to build trustworthy ML systems that are efficient, robust, fair, and interpretable to enhance the use of machine learning. Currently, Professor Harrison Zhao is teaching a class called 'Trustworthy Machine Learning' at the university to develop methods for machine learning to operate with reliability and responsibility.