She has consistently pursued research and teaching in artificial intelligence, robotics and machine learning, and has advised 45 CMU Ph.D.

That navigation system, called SemExp, last month won the Habitat ObjectNav Challenge during the virtual Computer Vision and Pattern Recognition conference, edging a team from Samsung Research China. It was the second consecutive first-place finish for the CMU team in the annual challenge. SemExp, or Goal-Oriented Semantic Exploration, uses machine learning to train a robot to recognize objects -- knowing the difference between a kitchen table and an end table, for instance -- and to understand where in a home such objects are likely to be found. This enables the system to think strategically about how to search for something, said Devendra S. Chaplot, a Ph.D. student in CMU's Machine Learning Department. "Common sense says that if you're looking for a refrigerator, you'd better go to the kitchen," Chaplot said.

PITTSBURGH--A robot travelling from point A to point B is more efficient if it understands that point A is the living room couch and point B is a refrigerator, even if it's in an unfamiliar place. That's the common sense idea behind a "semantic" navigation system developed by Carnegie Mellon University and Facebook AI Research (FAIR). That navigation system, called SemExp, last month won the Habitat ObjectNav Challenge during the virtual Computer Vision and Pattern Recognition conference, edging a team from Samsung Research China. It was the second consecutive first-place finish for the CMU team in the annual challenge. SemExp, or Goal-Oriented Semantic Exploration, uses machine learning to train a robot to recognize objects -- knowing the difference between a kitchen table and an end table, for instance -- and to understand where in a home such objects are likely to be found.

The Machine Learning Department is made up of a multi-disciplinary team of faculty and students across several academic departments. Machine learning is dedicated to furthering the scientific understanding of automated learning and to producing the next generation of tools for data analysis and decision making based on that understanding. Today's demand for expertise in machine learning far exceeds the supply, and this imbalance will become more severe over the coming decade. Students can pursue one of four Ph.D. programs, a Master's program, and an undergraduate Minor, Concentration, or Major. Students can also take classes in the Machine Learning Department without being part of one of its academic programs.

The Machine Learning Department of the School of Computer Science at Carnegie Mellon University occupies a privileged position in the world of machine learning, in part as the world's only academic Machine Learning Department. The Department has close relationships through shared faculty and active collaboration across the university, especially the Statistics Department and other academic units in the School of Computer Science (Computer Science Department, Language Technologies Institute, Computational Biology Department, and the Robotics Institute). We seek applicants who will thrive in this interdisciplinary setting.

Ranked as the #1 educational research institution in the for #AI and #machinelearning Research projects https://blog.ml.cmu.edu

Machine learning is an incredibly broad and diverse field, with a non-stop increase on research, along a multitude of applications. Thus writing a list enlisting the best machine learning researchers on the field proves challenging for a number of reasons. Please mind that this list encompasses researchers who are currently working on the field. Also, please mind that this list is by no means ranked. Everyone listed below has done extraordinary work to advance humanity's state of AI further.

Machine learning is an incredibly broad and diverse field, with a non-stop increase on research, along a multitude of applications. Thus writing a list enlisting the best machine learning researchers on the field proves challenging for a number of reasons. Please mind that this list encompasses researchers who are currently working on the field. Also, please mind that this list is by no means ranked. Everyone listed below has done extraordinary work to advance humanity's state of AI further.

Carnegie Mellon University's School of Computer Science will offer a new undergraduate degree in artificial intelligence beginning this fall, providing students with in-depth knowledge of how to transform large amounts of data into actionable decisions. SCS has created the new AI degree, the first offered by a U.S. university, in response to extraordinary technical breakthroughs in AI and the growing demand by students and employers for training that prepares people for careers in AI. "Specialists in artificial intelligence have never been more important, in shorter supply or in greater demand by employers," said Andrew Moore, dean of the School of Computer Science. "Carnegie Mellon has an unmatched depth of expertise in AI, making us uniquely qualified to address this need for graduates who understand how the power of AI can be leveraged to help people." This spring, U.S. News and World Report ranked SCS as the No. 1 graduate school for artificial intelligence. The bachelor's degree program in computer science teaches students to think broadly about methods that can accomplish a wide variety of tasks across many disciplines, said Reid Simmons, research professor of robotics and computer science and director of the new AI degree program.

Machine Learning (ML) is a fascinating field of Artificial Intelligence (AI) research and practice where we investigate how computer agents can improve their perception, cognition, and action with experience. Machine Learning is about machines improving from data, knowledge, experience, and interaction. Machine Learning utilizes a variety of techniques to intelligently handle large and complex amounts of information build upon foundations in many disciplines, including statistics, knowledge representation, planning and control, databases, causal inference, computer systems, machine vision, and natural language processing. AI agents with their core at Machine Learning aim at interacting with humans in a variety of ways, including providing estimates on phenomena, making recommendations for decisions, and being instructed and corrected. In our Machine Learning Department, we study and research the theoretical foundations of the field of Machine Learning, as well as on the contributions to the general intelligence of the field of Artificial Intelligence.