Gerard Salton Award Provides Opportunity for Zhai to Reflect Before Looking Forward Again

ACM SIGIR presents the Salton Award every three years to an individual who has made significant, sustained and continuing contributions to research in information retrieval.

In July, Illinois CS professor ChengXiang Zhai – typically a researcher with an eye toward the future – couldn’t help but look back upon years of collaborative research efforts. The reason for his shift in mindset came from learning that he had won the Gerard Salton Award from the Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR).

When reflecting on his career to this point, Zhai first recalled the moment he earned his second PhD in 2002. At that point, Zhai knew his future in the computer science field would focus on information retrieval.

In large part, that was due to the rise of Google as a major search engine company around the same time.

“The importance of web search just skyrocketed from that moment, so I realized that web search technologies were going to be in huge demand,” said Zhai, Donald Biggar Willett Professor in Engineering. “It was an important area, and this development presented a lot of new opportunities for research and technology innovation.”

Those new opportunities spoke to the broader theme of Zhai’s research that still inspires him.

Rather than simply developing specific new application tools, he believes his work should focus on developing general theoretical models and algorithms that can be used to power all intelligent software tools for augmenting human capabilities.

To Zhai, humans don’t just happen to invent tools; they do so to somehow better understand our world and even change it to be more effective and efficient.

“The computer is just one of these tools, and I’ve always had a goal to build applications using this tool that can impact many people by bettering their lives,” Zhai said. “Of all the tools that are created, the most interesting to me are ‘intelligent’ tools that are designed to augment our own capabilities to better manage and make use of massive amounts of online information.”

By using this concept as the unifying goal of his research, Zhai built a track record of sustained success in the field of information retrieval, the underlying science of all search engines.

SIGIR described Zhai’s success this way when he won the Gerard Salton Award:

“His work has defined many of the theoretical foundations of the language modeling approach, yielding major insights into areas such as smoothing methods, relevance feedback, topic diversification, and text representations that incorporate positional information. He and his collaborators have also pioneered the axiomatic approach to information retrieval, which continues to provide inspiration for retrieval model and evaluation research.”

One thing Zhai emphasized the most in building a better web search engine is to optimize the collaboration between a search engine and a user to maximize their combined intelligence.

In his keynote address for the Salton Award – titled “Information Retrieval as Augmentation of Human Intelligence” – Zhai outlined his journey of research in pursuing the goal of building an intelligent search engine.

Zhai’s starting point to build better search capabilities began with understanding the content. He then connected that content to the users in an interactive way and developed machine learning algorithms to enable a search engine to learn continuously from its interactions with the users so as to accurately understand their information needs and optimize its service for each individual user in a personalized and adaptive manner.

He sees the future of intelligent search engines as a game between user and technology.

“An intelligent search engine would play a collaborative game with its user in the future,” Zhai said. “You can think about the user’s first search query as the first move – just like in a chess game. In response to every action taken by the user, the search engine would intelligently make its own move by showing an appropriate interface with information to the user. The overarching goal of this game is to get the search engine to deliver all the needed information and knowledge by the user with minimal effort required from the user.”

Zhai credited his success in research to many people, especially his advisors, his students, many collaborators in academia and industry, and the excellent research environment at Illinois CS.

“This is a top computer science department for so many reasons, but one thing that has always amazed me is the breadth of the faculty’s expertise,” Zhai said. “I am grateful to all of the people who have collaborated with me and supported my career development at Illinois, particularly Professor Jiawei Han, who helped me better understand how data mining could enhance information retrieval.”

Zhai also made note of the meaningful nature of the Gerard Salton Award to him.

“I started my career reading two textbooks written by Gerard Salton, so it is a great honor to receive an award named after him. I want to thank SIGIR for recognizing me with this honor,” Zhai said.  “My work recognized by the award reminds me of the many future challenges in this field ahead of us and inspires me to further tackle those challenges. I remain focused on developing next-generation intelligent systems to augment human intelligence, bringing broad benefits to our society in many important domains such as healthcare, education, security, and so forth.”