Junghoo "John" Cho
Professor
Computer Science
UCLA
Email: cho@cs.ucla.edu
Phone: (310) 571-8240
Office: Boelter Hall 3531H
Office hour: Tue 2:30-3:30 PM
Biographical Sketch
Junghoo Cho is a professor in the Department of Computer Science at University of California, Los Angeles. He received
a Ph.D. degree in Computer Science from Stanford University and a B.S.
degree in physics from Seoul National University.
His research interest is in the theory and practice of learning, particularly
in the area of language acquisition and understanding.
He is a recipient of the 10-Year Best-Paper Award at VLDB 2010, NSF CAREER Award, IBM Faculty Award, Okawa Research Award, Northrop Grunmann Excellence in Teaching Award and Dr. Stevenson Faculty-in-Residence Award.
Research Interests
My research agenda is understanding and replicating the self-learning ability of humans. I work on this research agenda because I am deeply baffled by the following question: when we are born, how are we able to learn and make sense of the world without any "explicit teaching" by others? This ability looks almost magical to me, but I am also convinced that our brain is nothing more than a computational machine that happens to be implemented using a network of neurons. Given this conviction, I feel that there must be "computational algorithms" that implement the human's learning capabilities. My research goal, therefore, is to discover the mathematical principles and the computational algorithms that lie behind the human's amazing learning capacity.
Any scientific endeavor requires data from which we get inspiration and with which we validate our hypotheses. The particular domain data that I currently work with is human language. Therefore, the current goal of my research may be summarized as "can we develop algorithms that can automatically discover the grammatical structures and the semantic relationship embedded in our language?"
As toolsets to investigate this problem, I use linear algebra, tensor analysis, signal processing, functional analysis, probabilistic and bayesian inference, information theory, and (discrete) differential geometry. As I explore this domain, I learn that topics that I thought were completely unrelated are in fact connected at a deeper layer. For example, until a few years ago, I did not know that the graph partitioning problem is related to identifying the low frequency components of its "Fourier transform", which are obtained as the eigenfunctions of the Laplace operators of the manifold in which the data reside. These are probably the things that the experts in the field already know very well, but how would I have known these when my original background is databases? And whenever I learn these deeper connections, it is so satisfying personally, even if it might be something well known among experts.
In general, I find that, again and again, at the core of everything, our world looks so simple, elegant, and tightly connected. How can this simple structure lead to the amazingly rich world that we experience every day? This is the never-ending source of mystery and wonder that drives me to work on these problems.
Recent Professional Activities
- Program Committee, 26rd International World Wide Web Conference (WWW 2017)
- Program Committee, 2016 ACM International Conference on Management of Data (SIGMOD 2016), Tutorials Track
- Program Committee, Twenty-Second ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2016)
- Program Committee, Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015)
- Program Committee, Twentieth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2014)
- Program Committee, 2013 ACM International Conference on Management of Data (SIGMOD 2013)
- Program Committee, 2012 ACM International Conference on Management of Data (SIGMOD 2012)
- Program Committee, 37th International Conference on Very Large Data Bases (VLDB 2011)
- Program Committee, 4th ACM International Conference on Web Search and Data Mining (WSDM 2011)
- Program Committee, 35th International Conference on Very Large Data Bases (VLDB 2009)
- Program Committee, Second ACM International Conference on Web Search and Data Mining (WSDM 2009)
- Program Committee, Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008)
- Program Committee, 34th International Conference on Very Large Data Bases (VLDB 2008)
- Program Committee, First ACM International Conference on Web Search and Data Mining (WSDM 2008)
- Program Committee, 16th International World Wide Web Conference (WWW 2007)
- Program Committee, 2007 ACM International Conference on Management of Data (SIGMOD 2007)
- Program Committee, Twenty-second National Conference on Artificial Intelligence (AAAI-07), Special track on AI and the Web
- Program Committee, 15th Conference on Information and Knowledge Management (CIKM 2006)
- Program Committee, Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2006)
- Program Committee, Twenty-first National Conference on Artificial Intelligence (AAAI-06), Special track on AI and the Web
- Program Committee, 32nd International Conference on Very Large Data Bases (VLDB 2006)
- Program Committee, 2006 ACM International Conference on Management of Data (SIGMOD 2006)
- Program Committee, 31st International Conference on Very Large Data Bases (VLDB 2005)
- Program Committee, Eighth International Workshop on the Web and Databases (WebDB 2005)
- Program Committee, First International Workshop on Challenges in Web Information Retrieval and Integration (WIRI 2005)
- Program Committee, 13th International World Wide Web Conference (WWW 2004)
- Program Committee, 13th Conference on Information and Knowledge Management (CIKM 2004)
- Program Committee, Seventh International Workshop on the Web and Databases (WebDB 2004)
- Program Committee, 19th ACM Symposium on Applied Computing (SAC 2004)
- Program Committee, 2003 ACM International Conference on Management of Data (SIGMOD 2003)
Awards
- Best Paper Runner Up, SIGIR 2013
- 10-Year Best Paper Award, VLDB 2010
- Dr. Stevenson Award for the Best Faculty-In-Residence, 2010
- Northrop Grumman Excellence in Teaching Award, 2006
- Okawa Foundation Research Award, 2006
- IBM Faculty Award, 2005
- Best Paper Award, ICDE 2005
- National Science Foundation CAREER Award, 2004
- Best Paper Runner Up, WWW 2004
- KFAS (Korea Foundation for Advanced Study) Fellowship, 1998-2001
- Stanford Engineering School Fellowship, 1996
- GE (General Electric) Fellowship, 1994
Students
Current Ph.D. students
Past PhD Students
Teaching
I teach the following classes regularly at UCLA.
© Junghoo "John" Cho
