About the Authors
Dana Dachman-Soled
Dana Dachman-Soled
Department of Computer Science
Columbia University
New York, NY
dglasner[ta]cs[td]columbia[td]edu
Dana Dachman-Soled (a.k.a. Dana Glasner) is a Ph.D. candidate in the Department of Computer Science at Columbia University, supervised by Tal Malkin and Rocco Servedio. She received her undergraduate degree in Computer Science from Yeshiva University. Her research interests include property testing and cryptography. She enjoys life in New York City with her husband and their 17-month-old (at the time of submission) son.
Homin K. Lee
Homin K. Lee
Department of Computer Science
University of Texas at Austin
homin[ta]cs[td]utexas[td]edu
http://www.cs.utexas.edu/~homin
Homin K. Lee is a postdoctoral researcher under the direction of Adam Klivans at the University of Texas at Austin. He received his Ph.D. from the Department of Computer Science at Columbia University where he was advised by Tal Malkin and Rocco A. Servedio. His thesis was titled On the Learnability of Monotone Functions, and his research interests include computational learning theory and the analysis of Boolean functions. He is often hungry.
Tal Malkin
Tal Malkin
Assistant Professor
Department of Computer Science
Columbia University
New York, NY
tal[ta]cs[td]columbia[td]edu
http://www.cs.columbia.edu/~tal
Tal Malkin received her Ph.D. in Computer Science from MIT in 2000, under the supervision of Shafi Goldwasser. After spending three years at AT&T Labs Research, she joined the Department of Computer Science at Columbia University, where she heads the Cryptography Lab. Her research interests are in cryptography, security, complexity theory, and related areas, with foundations of cryptography being closest to her heart. She enjoys living in New York City and spending time with (and without) her husband, two sons, and cat. In theory she loves theater, ice hockey, editing the journal "Theory of Computing," and sleep, but in practice she doesn't get to enjoy these activities too often.
Rocco A. Servedio
Rocco A. Servedio
Associate Professor
Columbia University
New York, NY
rocco[ta]cs[td]columbia[td]edu
http://www.cs.columbia.edu/~rocco
Rocco A. Servedio is an associate professor in the Department of Computer Science at Columbia University. He graduated from Harvard University in 2001 where his Ph.D. was supervised by Leslie Valiant. He is interested in computational learning theory, computational complexity, and other topics. He enjoys spending time with his family and hopes to drink a quart of stout with Herman Melville in the afterlife.
Andrew Wan
Andrew Wan
Department of Computer Science
Columbia University
New York, NY
atw12[ta]columbia[td]edu
http://www.cs.columbia.edu/~atw12
Andrew Wan is a Ph.D. candidate at Columbia University, advised by Tal Malkin and Rocco Servedio. His interests include complexity theory, cryptography, and computational learning theory. Before graduate school, he was a student of philosophy at Columbia University and enjoyed playing the piano, the trumpet, and the accordion. Although he still enjoys playing music, the PAC model rarely affords him the time.
Hoeteck Wee
Assistant Professor
Department of Computer Science
Queens College, City University of New York
hoeteck[ta]cs[td]qc[td]cuny[td]edu
http://www.cs.qc.edu/~hoeteck
Hoeteck Wee is an assistant professor at Queens College, CUNY. He received his Ph.D. from UC Berkeley under the supervision of Luca Trevisan and his B.Sc. from MIT. He was previously a postdoc at Columbia University and a visiting student at Tsinghua University and IPAM. Hoeteck currently lives in Manhattan close to the cafés in order to cut down on his commute. He's working to convince more people that “black box is the new black.”