[4eyes] FW: Adobe Research internships available: please pass on to your students

[Matthew Turk]

FYI

-----Original Message-----
From: David Salesin [mailto:salesin at adobe.com] 
Sent: Monday, November 24, 2014 10:44 AM
To: David Salesin
Subject: Adobe Research internships available: please pass on to your
students

Adobe Research is offering internships this spring, summer, and fall in
Cambridge MA, Seattle, San Francisco, and San Jose. We are looking for PhD
students who are excited about pushing the state of the art in audio,
graphics, vision, human-computer interaction, machine learning,
visualization,
analytics, optimization, and more -- in ways that could be of interest to
Adobe 
as well as to the research community at large. We have just started
recruiting,
and we would love to hear from you!

You will collaborate with one or more researchers, with access to
world-class product groups and design teams. We explore opportunities for
technology transfer and regularly publish in leading journals and
conferences.
You would also have an opportunity to partner with our new Disruptive
Innovation Group -- a small team of engineers and entrepreneurs that develop
new products with our research -- making it possible for you to see your
work
in consumers' hands.  We are especially interested in fostering ongoing
collaborations and are open to projects that last beyond the internship and
become part of your PhD thesis. We compensate interns well, and strive to
create an environment that is both productive and fun.

Our Cambridge lab is located in Kendall Square, neighboring the MIT campus
and
steps away from the Red Line "T" with easy access to Boston. The Seattle lab
is located in the hip Fremont area, directly on the water (you can kayak to
work!) and connected by a bike path to UW. The San Francisco lab is located
in
the trendy SOMA area, near the ballpark and a short walk from the Caltrain
station. The San Jose lab is in the heart of Silicon Valley, with a diverse
array of culture and a short walk from the Caltrain station.

Our team currently includes the following researchers (for more information,
visit our web pages at research.adobe.com): 

Cambridge
* Sylvain Paris <sparis>: graphics, vision, photography, video

Seattle
* Aseem Agarwala <asagarwa>: data-driven design, graphics, vision,
photography, video 
* Dan Goldman <dgoldman>: graphics, vision, human-computer interaction 
* Danny Kaufman <kaufman>: graphics, computational design and fabrication,
simulation
* Jovan Popović <jovan>: graphics, games, simulation, control, optimization 
* Eli Shechtman <elishe>: vision, photography, recognition, graphics
* Jue Wang <juewang>: graphics, vision, photography, video 
* Holger Winnemoeller <hwinnemo>: graphics, rendering, human-computer
interaction  

San Francisco
* Joel Brandt <jobrandt>: HCI, software development tools, visual and
interactive design tools
* Floraine Berthouzoz <floraine>: graphics, HCI, data-driven design
* Mira Dontcheva <mirad>: HCI, graphics, visualization 
* Aaron Hertzmann <hertzman>: graphics, vision, machine learning, design
* Matthew Hoffman <mathoffm>: machine learning, audio
* Vladlen Koltun <vladlen>: graphics, vision, machine learning 
* Wilmot Li <wilmotli>: graphics, visualization, HCI
* Leo Zhicheng Liu <leoli>: information visualization, visual analytics, HCI
* Gautham Mysore <gmysore>: audio, machine learning, signal processing
* Bryan Russell <brussell>: vision, recognition, machine learning
* David Salesin <salesin>: graphics, photography, HCI, rendering, color 

San Jose
* Paul Asente <asente>: vector graphics, illustration stylization, HCI 
* Jon Brandt <jbrandt>: visual search, recognition, machine learning,
computer vision
* Hung H. Bui <hubui>: probabilistic graphical model, machine learning,
clustering, activity recognition
* Trung Bui <bui>: reinforcement learning, machine learning, dialog systems 
* Nathan Carr <ncarr>: geometry processing, rendering, high performance
computing
* Duygu Ceylan <ceylan>: geometry processing, 3D fabrication
* Walter Chang <wachang>: content understanding, semantic analysis, and data
analytics 
* Scott Cohen <scohen>: segmentation, matting, stereo, restoration
* Sunil Hadap <hadap>: structured light, photometric stereo, material and
depth acquisition
* Mohammad Ghavamzadeh <ghavamza>: machine learning, reinforcement learning,
online learning, digital marketing
* Daichi Ito <dito>: artistic procedural modeling, designing tools for
artists 
* Tom Jacobs <jacobs>: Internet of Things, Data Science as a Service
* Hailin Jin <hljin>: deep learning, convolutional neural networks, vision,
machine learning
* Jaya Kawale <kawale>: Machine Learning, Data Mining, Econometrics,
Attribution Modeling
* Byungmoon Kim <bmkim>: rendering, simulation,  high performance computing,
geometry
* Eunyee Koh <eunyee>: user segmentation, predictive analytics,
personalization, HCI, data mining 
* Branislav Kveton <kveton>: Online Learning, Machine Learning, Artificial
Intelligence, Reinforcement Learning
* Zhe Lin <zlin>: computer vision, image processing, deep learning, machine
learning
* Nedim Lipka <lipka>: machine learning, data mining, information retrieval,
big data analytics, information visualization
* Jingwan Lu <jlu>: graphics, designing tools for artists, data-driven
design, image stylization, HCI
* Linjie Luo <lluo>: 3D acquisition, data-driven modeling, 3D printing
* Radomir Mech <rmech>: interactive procedural modeling, casual modeling, 3D
printing 
* Gavin Miller <gmiller>: procedural modeling, rendering, simulation,
light-field imaging 
* Saayan Mitra <smitra>: video delivery and monetization, media formats and
standards, digital rights management
* Brian Price <bprice>: semantic segmentation, interactive object selection,
matting 
* Stephen Schiller <schiller>:  image stacks. boundary detection,
segmentation, and simplification in images with texture
* Xiaohui Shen <xshen>: depth estimation, recognition, visual search, scene
understanding
* Kalyan Sunkavalli <sunkaval>:  image, video, physics-based vision
* Vishy Swaminathan <vishy>: video delivery systems, rights management,
network transports
* Georgios Theocharous <theochar>: reinforcement learning, machine learning,
information retrieval
* David Tompkins <tompkins>: cloud computing, distributed systems, data
science as a service
* Nikos Vlassis <vlassis>: machine learning and optimization
* Gregg Wilensky <wilensky>: image correction, matting, creative effects 
* Jianchao Yang <jiayang>: recognition, deep learning, restoration,
recommendation, machine learning, computer vision

To apply, please send an email to research-internships at adobe.com with your
CV,
a list of your research interests, and any specific researchers you would
like
to work with. Also feel free to contact specific researchers at their
<name>@adobe.com address. Internships will be granted on a rolling basis, 
so apply as soon as possible.