Sunday, January 22, 2017

Job/Intern Announcements

Following job/intern announcements are of interest to folks.

1. NYT: The Data Science Group at The New York Times is expanding, and we are hiring in data scientist / machine learning roles (http://bit.ly/nyt-datasci). The group focuses on developing and deploying machine learning solutions to meet newsroom and business challenges throughout the company. These challenges include prediction and prescription problems (e.g., supervised learning, targeting), resulting in a variety of internal data products: e.g., webapps, APIs, and slackbots. For examples of public-facing details on machine learning at The New York Times, see the URLs below for an interview [1], talk [2], news [3], or blog [4].

[1] http://www.columbia.edu/itc/applied/wiggins/DSatW-wiggins.pdf
[2] http://www.youtube.com/watch?v=jy_4tljIFqY
[3] http://www.niemanlab.org/2015/08/the-new-york-times-built-a-slack-bot-to-help-decide-which-stories-to-post-to-social-media/
[4] http://bit.ly/AlexCTM

2. Adobe:  Full-Time Positions in Big Data Experience Lab (BEL) at Adobe Research, San Jose, CA

Big Data Experience Lab (BEL) at Adobe Research (https://research.adobe.com/about-the-labs/bigdata-experience-lab/) in San Jose is looking for full-time researchers to define and execute next generation machine learning and AI research for digital marketing applications and services. Adobe Marketing Cloud (http://www.adobe.com/marketing-cloud.html) is one of the largest data collection platforms in the world, managing approximately 35 petabytes of customer data and processing one trillion transactions per quarter. But it's not just the quantity of data - it's the quality of the work that makes this an amazing time to be at Adobe Research. BEL has excellent publication record with dozens of papers at top-tier machine learning and AI conferences and journals in recent years. Join us to turn data into impact as you analyze unique problems, draw inferences, test theories, and see your theories come to life in solutions that help our customers rack up business successes. If you're interested in the problems related to finding information hidden in large data sets, then Adobe Research is your opportunity to make a huge impact on the academic community as well as our customers, who represent the top 10,000 biggest web and mobile businesses.

We accept applications throughout the year. The application should include a brief description of the applicant's research interests and past experience, plus a CV that contains the degrees, GPAs, relevant publications, names and the contact information of references, and other relevant documents. To apply, please send your application to adoberesearchjobs@adobe.com.

3. Adobe: Machine Learning Internship at Adobe Research, San Jose, CA

Machine Learning Group in Big Data Experience Lab (BEL) at Adobe Research (https://research.adobe.com/about-the-labs/bigdata-experience-lab/) in San Jose is looking for interns to work on a range of problems in machine learning, deep learning, digital marketing, and analytics. Our interns will have opportunity to work on real-world terabyte-scale problems in Adobe Marketing Cloud (http://www.adobe.com/marketing-cloud.html). The interns will be supervised by researchers in the group who have excellent publication record with dozens of papers at top-tier machine learning and AI conferences and journals in recent years.  The internship will be in San Jose, California, at the heart of the Silicon Valley. The duration of the internship is 12 weeks and it can start any time from April 1, 2017.

The successful candidate will be mentored and work closely with one or more of the following Adobe researchers:
- Yasin Abbasi Yadkori (http://webdocs.cs.ualberta.ca/~abbasiya)
- Branislav Kveton (http://www.bkveton.com)

The deadline for the application is January 31, 2017.  To apply, please send your application to machine-learning-internships@adobe.com.

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Tuesday, January 17, 2017

Ballet and Gender Roles, A Discussion

Can ballet express modernist view of sexes and gender roles? This is a much needed discussion, and NYT steps up. Good to see friend Amar make cameos in pictures. 

Saturday, January 07, 2017

Lines of NY

Here are the lines of NY in a snowing morning.


Monday, November 28, 2016

Dreading when Data is Unleashed.

For past 2 decades we have believed that web will free information, anyone can report it,  pass it on, take it down, etc. But there was always a nuclear outcome that seemed plausible but the optimists thought humans as a crowd will control its misuse. We are learning it is tricky:

Obama said, “If we are not serious about facts and what’s true and what’s not … if we can’t discriminate between serious arguments and propaganda, then we have problems.”

"If everything seems to be the same and no distinctions are made, then we won’t know what to protect. We won’t know what to fight for. And we can lose so much of what we’ve gained in terms of the kind of democratic freedoms and market-based economies and prosperity that we’ve come to take for granted,” he said. 

Now I have a mental exercise for folks. We are as a society trying to set Data free. Data (say tables, observations, measurements) can be presented, analyzed, depicted, mined in so many ways that there is true and what's not will (need to) be debated in web scale. 

Undergrad vs Graduate Work

What is the difference between undergrad and grad students in professional interaction? I explained it recently to a student as follows:

  •  In undergrad times, the interactions are transactional/negotiation-oriented: professor gives you HWs, you do them, you get points;  professor poses a problem, you answer it, get points, you dont answer it, say the problem was confusing, get partial points; at the end of the course, you get a grade, forget the professor,  approach the professor again when you need a reference letter, professor writes a more or less generic letter saying you were one of the top X students in the class or whatever; your life moves on, the professor stays behind. 
  • In grad times, the interactions are relational: you take a course with a professor and do well or not; you might continue research with the professor or have them on your qualifier exam; you will TA one of their courses later or even be a GA if that professor has funds and your advisor needs some gap funding; that professor might have a contact in a company looking for a research intern for a summer and they might connect you;  they might ask you to referee papers or recommend you for a travel grant; even if your research diverges from that professor, you might remember something about that professor's research which helps you during an interview, just being world-aware; etc. your life moves on, so does the professor's, and two professional research lives, even if parallel, will cross in unexpected ways. 

Saturday, November 26, 2016

Amazon Postdoc at IISc, India

This Amazon postdoc with IISc, Bangalore, India sounds very interesting, focused on data science/machine learning, and theory CS. IISc has very strong theory researchers. Amazon India is an incredible business success story and has terrific data science/Machine learning researchers. Bangalore is a nice place to spend some time in ones life, and explore India.

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Tuesday, November 22, 2016

DIMACS Postdoc Positions

Postdoc positions at DIMACS, announced below. I always thought a postdoc at DIMACS was a great opportunity for emerging theorists out of their Phd to round out their research and set up for something big, with the constellation of researchers and resources in the DIMACS ecosystem.

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DIMACS Center, Postdoctoral Associate

DIMACS, the Center for Discrete Mathematics and Theoretical Computer Science, invites applications for various postdoctoral associate positions for 2017-18. Applicants should be recent Ph.D.'s with interest in DIMACS areas, such as computer science, discrete mathematics, statistics, physics, operations research, and their applications. One of  these positions is a one-year postdoctoral associateship investigating modeling of anomaly detection in multi-layer networks. A second position is a two-year associateship in collaboration with the Institute for Advanced Study (IAS) in Princeton, NJ emphasizing theoretical computer science and discrete mathematics. Another position associated with the Simons Collaboration on Algorithms and Geometry also emphasizes theoretical computer science and discrete mathematics and could be hosted at Rutgers/DIMACS. A fourth position is a two-year associateship in theoretical machine learning in the Department of Computer Science at Rutgers.

See http://dimacs.rutgers.edu/Applications/postdoc.html for application information. Applications have various deadlines, beginning December 1, 2016. 
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Saturday, November 12, 2016

Seeking Research Visitors

I am free much of Jan--Aug next year, and would like to host a couple of researchers at Rutgers/DIMACS/NY/NJ area for collaboration.

I will be mostly doing research in streaming, auction/pricing/mechanism design, or topics of interest in data structures, algorithms, databases, ML/AI.  I am looking for senior graduate students, postdoctoral researchers, faculty members to visit the area, spend a few weeks and get some joint research done. Please contact me if you are interested.

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Views

In the middle below is a monster, and on either side, views of NY.

No Quantum

People used to tell me I was in superposed quantum states. I am much more deterministic now.
  • I live in NY, travel only a little. Kids do that to you. 
  • I teach in Rutgers, undergrads this semester. Have a few PhD students, it is a journey as usual. 
  • I do research in streaming and pricing algorithms. I am excited about some recent theory  (graph matching on streams), new directions (graphical model sketch), some non-theory work on app2vec (see anything2vec), etc. 
  • Like others, between the heartbeats ones life, I manage to consume or create some art.