 |
Jennifer G. Dy is a Professor at the Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, where she first joined the faculty in 2002. She received her M.S. and Ph.D. in 1997 and 2001 respectively from the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, and her B.S. degree (Magna Cum Laude) from the Department of Electrical Engineering, University of the Philippines, in 1993. Her research is in machine learning, data mining and their application to biomedical imaging, health, science and engineering, with a particular focus on clustering, multiple clusterings, dimensionality reduction, feature selection and sparse methods, large margin classifiers, learning from the crowds and Bayesian nonparametric models. She received an NSF Career award in 2004. She has served as an associate editor for Machine Learning and Data Mining and Knowledge Discovery, an editorial board member for JMLR, organizing/senior/program committee member for ICML, ACM SIGKDD, AAAI, IJCAI, AISTATS and SIAM SDM, and was program chair for SIAM SDM 2013.
|
 |
|
 |
Vivienne Sze is an Associate Professor at MIT in the Electrical Engineering and Computer Science Department. Her research interests include energy-aware signal processing algorithms, and low-power circuit and system design for portable multimedia applications, including computer vision, deep learning, autonomous navigation, and video process/coding. Prior to joining MIT, she was a Member of Technical Staff in the R&D Center at TI, where she designed low-power algorithms and architectures for video coding. She also represented TI in the JCT-VC committee of ITU-T and ISO/IEC standards body during the development of High Efficiency Video Coding (HEVC), which received a Primetime Emmy Engineering Award. Prof. Sze received the B.A.Sc. degree from the University of Toronto in 2004, and the S.M. and Ph.D. degree from MIT in 2006 and 2010, respectively. In 2011, she received the Jin-Au Kong Outstanding Doctoral Thesis Prize in Electrical Engineering at MIT. She is a recipient of the 2018 Facebook Faculty Award, the 2017 Qualcomm Faculty Award, the 2016 Google Faculty Research Award, the 2016 AFOSR Young Investigator Research Program (YIP) Award, the 2016 3M Non-Tenured Faculty Award, the 2014 DARPA Young Faculty Award, the 2007 DAC/ISSCC Student Design Contest Award, and a co-recipient of the 2017 CICC Outstanding Invited Paper Award, the 2016 IEEE Micro Top Picks Award and the 2008 A-SSCC Outstanding Design Award.
|
 |
Eni Mustafaraj is an Assistant Professor of Computer Science at Wellesley College in Wellesley, MA, USA, who received a M. Eng. in Computer Engineering from the Polytechnic University of Tirana (Albania) and a Ph.D. in Computer Science from the Philipps University of Marburg (Germany). She studies web-based, socio-technical systems, especially platforms such as Google, Twitter, and Wikipedia, and is currently interested in the problem of assessing the credibility of online sources, using human-centered machine learning algorithms. For this research she received an NSF CAREER in 2018. Please visit her research page to learn more. She is also in the editorial board of The Spoke, an Albright Institute faculty initiative, and blogs about her research on Medium.
|
 |
Janet Slifka joined Amazon in 2012 as part of the science team that built and brought Amazon Alexa to market. Janet started out in a scientist role and quickly moved into a manager role -- first building the data collection team and strategies for developing ground truth resources for machine learning, then building the data services team for transcription and annotation, and in 2016 founding the Applied Modeling and Data Science org with Alexa AI. She currently manages globally distributed and cross-functional teams to enable a continually improving experience for Alexa Customers. Janet holds a PhD in Health Sciences and Technology from MIT as part of joint program between Harvard and MIT. She has experience in start-ups, in the health sciences field as a Principal Investigator for NIH and as a scientist for Eliza Corporation, in academia as a Research Scientist as MIT, and in industry as an acoustics engineer at Bose Corporation.
|
 |
|
 |
Tina Eliassi-Rad is an Associate Professor of Computer Science at Northeastern University in Boston, MA. She is also on the faculty of Northeastern's Network Science Institute. Prior to joining Northeastern, Tina was an Associate Professor of Computer Science at Rutgers University; and before that she was a Member of Technical Staff and Principal Investigator at Lawrence Livermore National Laboratory. Tina earned her Ph.D. in Computer Sciences (with a minor in Mathematical Statistics) at the University of Wisconsin-Madison. Her research is rooted in data mining and machine learning; and spans theory, algorithms, and applications of massive data from networked representations of physical and social phenomena. Tina's work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, and cyber situational awareness. Her algorithms have been incorporated into systems used by the government and industry (e.g., IBM System G Graph Analytics) as well as open-source software (e.g., Stanford Network Analysis Project). In 2010, she received an Outstanding Mentor Award from the Office of Science at the US Department of Energy.
|
 |
Sravana Reddy is a researcher at Spotify in Boston, where she works on projects related to natural language processing and machine learning. She also holds a courtesy appointment at Dartmouth College. She got her PhD in Computer Science from the University of Chicago, and has spent time at USC ISI, Dartmouth and Wellesley. Her work spans NLP, speech, machine learning, and linguistics. Most of her academic research centers around language variation: both dealing with it in practical systems, and analyzing it using large corpora. She is also interested in the applications of computation to literature and writing. She has developed and maintains DARLA, a web application for automating sociophonetics.
|
