Three CS&E Professors Named 2017 IEEE Fellows

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December 5, 2017

Professors Maria Gini, Tian He, and George Karypis have all been named IEEE Fellows this year. Their achievements are being recognized as part of the broader mission of the IEEE.  Gini is being recognized for her contributions to multi-agent programming in robotics, He for his development and optimization of networked sensing systems, and Karypis for his contributions to graph partitioning and data mining.

The IEEE Grade of Fellow is conferred by the IEEE Board of Directors upon a person with an outstanding record of accomplishments in any of the IEEE fields of interest. The total number selected in any one year cannot exceed one-tenth of one- percent of the total voting membership. IEEE Fellow is the highest grade of membership and is recognized by the technical community as a prestigious honor and an important career achievement. Becoming an IEEE Fellow is a rare honor among the IEEE community, less than 0.1% of voting members are selected for the elevation.

The IEEE is the world’s leading professional association for advancing technology for humanity. Through its 400,000 plus members in 160 countries, the association is a leading authority on a wide variety of areas ranging from aerospace systems, computers and telecommunications to biomedical engineering, electric power and consumer electronics.

Please join CS&E in extending our congratulations to Professors Gini, He, and Karypis. More details about each individual’s career accomplishments that led to their elevation and the impact of these accomplishments are below.

Maria Gini
Contributions to multi-agent programming in robots

Professor Gini has been a leader in the field of robotics and multi-agent systems for over 30 years, bringing ideas from Artificial Intelligence (AI) into robotics, starting at a time when those two fields were disconnected.  She is a pioneer in the field of robot programming for manipulators, and has made multiple seminal contributions to robot programming and multi-agent systems.  Her early work on the POINTY programming system bridged the gap between high-level languages and programming by guidance. She was also among the first researchers to note the disconnect between the frameworks used in AI and real robots, where uncertainties and errors cannot be ignored and choices are continuous rather than discrete. Her work has spanned both the design of novel algorithms and practical applications, such as navigation, surveillance, exploration, search and rescue.

Gini was one of the first to introduce the notion of a virtual market for agents and demonstrated the power of this design paradigm by implementing a prototype of a virtual market for E-commerce.  This was later extended into MAGNET, a system still unique for its use of auctions for buying and selling tasks that have time and precedence constraints. This makes auctions applicable to a large variety of problems in planning, routing, and robotics, where task duration and travel time must be accounted for.

Tian He
Development and optimization of networked sensing systems

Professor He has made many influential and landmark contributions to the area of wireless sensor networks, the Internet of Things, and cyber-physical systems (over 21,000 citations). He has received many research awards including best papers at MobiCom and SenSys, held many leadership service positions, and graduated 11 Ph.D. students, among which eight have become tenure-track faculty members at reputable universities.

He’s work focuses on expanding the current Internet with billions of tiny computers that can sense, communicate, control the physical world autonomously, effectively and efficiently. The research is the foundation for “smart environments” used across industries, such as transportation, construction, power and energy, agriculture, and manufacturing.

George Karypis
Contributions to graph partitioning and data mining

Professor Karypis is known worldwide for seminal contributions in graph partitioning, data mining, and recommender systems (over 52,000 citations), and also for his software modules that have been incorporated in over 180 commercial packages and several hundred software codes developed at academic institutions, government labs, and industry. Nearly everyone running large-scale simulations on supercomputers uses Karypis’ graph partitioning software to optimize runtime: Cloud-infrastructure companies to intelligently optimize workload; Chip designers to maximize chip-speed, and minimize chip-area and cost; Publishers and content managers to organize/mine information from a vast number of documents; and E-Commerce/media-streaming companies to identify relevant items for their customers.

In a nutshell, the impact of Karypis’ work is extensive both among the research community and in industrial practice. His publications are widely read and cited and 13 of them have received more than 1,000 citations. These papers cover many of the research areas that he has been working on including graph partitioning, graph mining, clustering, recommender systems, parallel computing, bioinformatics, and chemical informatics. Karypis has developed and made publicly available a wide-range of high-quality software packages in the areas of high-performance computing, data mining, circuit design, chemical informatics, bioinformatics, recommender systems, and scientific computing. Unlike most other software developed in academia that have limited user base, his software packages are used extensively worldwide.

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