Hey there PCHU A few thoughts: 1 - Small business doesn't hire...

Hey there PCHU

A few thoughts:

1 - Small business doesn't hire the same way large corporate businesses do. The typical US small business listed above has 2 to 20 employees (the vast, vast majority of small businesses have ZERO employees and are one man businesses based at home). So the idea that they are going to sign up and pay thousands to hire people for jobs they don't have is interesting but unlikely.

2 - Dr. Smola is a very clever man. He has spent much time in academia. Do see his many accomplishments below. However being unhelpful to recruiters is unhelpful if the plan is to sell to recruiters. Few enjoy this level of facetiousness and few forget. And as for the commercial experience at Yahoo the less said the better. And if 1PG plans to invest in blue sky ML then it no longer is competing with Linkedin (which many on these boards think is simple) but now also with Facebook, Google, Snapchat, Apple, Twitter, News, IBM etc etc etc. How this is a plus for 1PG is deeply unclear.

3 - Carnegie Mellon is not in Silicon Valley. Neither is the Australian University mentioned above.

Finally - today's fall at this level of volume shows significant change in the register. Close to $1.51 at some points.

Laters!

Dr. Alexander Johannes Smola
Professor, Australian National University
Senior Principal Researcher, NICTA
Track record

Academic
My research on Support Vector Machines and kernel methods has shaped the progress in this area. Consequently it found its way into textbooks. One of my own books has become standard course material for kernel methods. There is hardly an aspect of kernel methods which I have not contributed to, be it optimization, statistical properties, theory, applications, teaching, or organization of events. Kernels allow one to design a large number of estimators which show superior flexibility and ease of use.
Community
I have served (repeatedly) on several senior program committees in NIPS, COLT, ICML, KDD, SDM. In addition to that, I am member of the editorial boards of the Journal of Machine Learning Research, Statistics and Computing, and the IEEE Transactions on Pattern Recognition and Machine Intelligence. I have reviewed for every major conference and journal in the area of machine learning.
Teaching and Supervision
Over the past decade I have (co)supervised and am supervising several PhD students, among those Ying Guo, Cheng Soon Ong, Omri Guttman, Justin Bedo, Karsten Borgwardt (de facto), Le Song (de facto), Markus Weimer (de facto), Matthew Robard, Quoc Le, Choon Hui Teo, Owen Thomas, Tim Sears, Novi Quadrianto and Javen Qinfeng Shi.
Grants
In the past I have held 7 grants of the Australian Research Council, with a total of approximately 1.5 Million AU$. In addition to that, I held a postdoctoral grant of the German Research Foundation, and grants by the German National Scholarship Foundation. Finally, the Statistical Machine Learning Program holds a European Union collaborative grant as part of a European network of excellence in machine learning.
In my role as a Program Leader in NICTA I am responsible for an annual budget of 1.5 to 2 Million AU$.
Leadership
My recent position as program leader of the Statistical Machine Learning Program at NICTA involved leading a team of up to 35 researchers, programmers, PhD students, visitors, and interns (the numbers fluctuate widely, since SML had a large number of visitors and its team members are internationally well connected). During my leadership the size of the program has trebled.
Career

• since 2008 Yahoo, Santa Clara, USA
  Principal Research Scientist (Machine Learning Program)
• 2004-08 NICTA, Canberra Research Laboratory, Australia
  Statistical Machine Learning Program leader, (11 academics, 3 programmers, 10 PhD students, 1 sabbatical visitor)
• 2001-04 Australian National University, Canberra, Research School for Information Sciences and Engineering
  Machine Learning Group, Leader, (3 academics, 1 PhD student)
• 1999-01 Australian National University, Canberra, Deptartment of Engineering, Visiting Researcher (DFG Grant)
• 1998-99 GMD FIRST, Berlin, Department of Software Engineering
  Postdoctoral Researcher
• 1996-98 GMD FIRST, Berlin, Department of Software Engineering
  PhD Student
• 1995-96 AT&T Research, Holmdel
  Intern (final year's project)
• 1991 Siemens AG, Research and Development, Munich, Germany
  Intern

Grants

• 2009-11 Australian Research Council, Partner Investigator
  Machine Learning in the Multicore Area with Prof. Alistair Rendell ($250k total)
• 2004-08 Pascal European Union network of excellence in machine learning ($30k per annum)
• 2007-09 Australian Research Council, Chief Investigator
  Unifying Machine Learning with Prof. Bob Williamson ($250k total)
• 2003-05 Australian Research Council, Chief Investigator
  Computer Vision and Machine Learning with Prof. Richard Hartley ($250k total)
• 2003-05 Australian Research Council, Chief Investigator
  Network Intrusion Detection via Machine Learning ($165k total)
• 2002-04 Australian Research Council, Chief Investigator
  Machine Learning with Prof. Bob Williamson and Dr. Shahar Mendelson ($220k total)
• 2001 Australian Research Council, Faculty Research Granst Scheme, Principal Investigator
  Finding Genes with Kernel Methods ($25k total)
• 2000 Australian Research Council, Faculty Research Granst Scheme, Principal Investigator
  Unsupervised Learning with Kernels ($20k total)
• 1999-2001 Australian Research Council, Associate Investigator
  Large Margin Classifiers ($240k total) with Prof. Bob Williamson and Prof. Peter Bartlett
• 1999-2001 Telstra Research Grant
  Machine Learning and Data Mining with Prof. Bob Williamson, Prof. Peter Bartlett and Dr. Jon Baxter ($60k total)
• 1999-2001 German Research Council (DFG), Postdoctoral Fellowship
  Applicable Learning Theory ($100k total)

Books

• mce-anchorG. Bakir, T. Hofmann, B. Schölkopf, A.J. Smola, B. Taskar, and S.V.N. Vishwanathan, editors. Predicting Structured Data. MIT Press, Cambridge, MA, 2006.
• mce-anchorS. Mendelson and A. J. Smola, editors. Machine Learning, Proceedings of the Summer School 2002, Australian National University, volume 2600 ofLecture Notes in Computer Science. Springer, 2003.
• mce-anchorB. Schölkopf and A. J. Smola. Learning with Kernels. MIT Press, 2002.
• mce-anchorB. Schölkopf, C. J. C. Burges, and A. J. Smola, editors. Advances in Kernel Methods--Support Vector Learning. MIT Press, Cambridge, MA, 1999.
• mce-anchorA. J. Smola, P. L. Bartlett, B. Schölkopf, and D. Schuurmans, editors. Advances in Large Margin Classifiers. MIT Press, Cambridge, MA, 2000.

Education

• 1997-98 Technische Universität Berlin, PhD Thesis in Computer Science (summa cum laude) on Learning with Kernels, Supervisor Prof. Klaus-Robert Müller
• 1995-96 AT&T Bell Laboratories, Holmdel, Thesis on Regression with SV Machines, Supervisor Prof. Vladimir Vapnik
• 1994-95 Technische Universität München, best Physics MA, score 1.0 in range [1.0-5.0]
• 1993-94 Universita degli Studi di Pavia
• 1991-93 Technische Universität München, best Physics BA, score 1.0 in range [1.0-5.0]

Workshops and Summer Schools

• 2002, 2003, 2005, 2006, 2008 Machine Learning Summer School Canberra
• 2004 Machine Learning Summer School Berder
• 2006 Machine Learning Summer School Taipeh
• 2010 SIGIR Workshop on Feature Generation and Selection
• 2009 NIPS Workshop on Large-Scale Machine Learning
• 2007 NIPS Workshop on Representations of Distributions
• 2004 NIPS Workshop on Kernels and Graphical Models
• 2002 NIPS Workshop on Unreal Data
• 1999 ICANN Workshop on Gaussian Processes and Support Vectors
• 1998 NIPS Workshop on Large Margin Classifiers
• 1998 EUROCOLT Workshop on Kernel Methods
• 1997 NIPS Workshop on Support Vectors

Refereeing

I am a member of the editorial board of

• the Journal of Machine Learning Research
• Statistics and Computing
• IEEE Transactions on Pattern Analysis and Machine Intelligence

In addition to that I have served as a member of the program committees of

• the conference on Computational Learning Theory (COLT) 2002, 2006, 2008
• the conference on Neural Information Processing Systems (NIPS) 2003, 2008 (workshop chair)
• the International Conference on Machine Learning (ICML) 2002, 2004, 2005, and 2006.

In addition to that I am a member of the advisory board (and co-founder) of Kernel-Machines.org. Finally, I am a referee for grants of the Australian Research Council.
Academic Collaboration

I have collaborated with a large number of colleagues worldwide, such as Thomas Hofmann (Fraunhofer, Dortmund), Tony Jebara and Risi Kondor (Columbia University), Chris Burges (Microsoft, Redmond), Ralf Herbrich (Microsoft, Cambridge), Karsten Borgwardt (Cambridge University), Carlos Guestrin (CMU), Eleazar Eskin (UC San Diego), John Shawe-Taylor (University College London), John Langford (Yahoo Research), Sam Roweis (University of Toronto), Amir Globerson (MIT), Gideon Dror (U Haifa), Bernhard Schölkopf and Gunnar Rätsch (MPI for Biological Cybernetics, Tübingen), Klaus-Robert Müller (Fraunhofer, Berlin), Yasemin Altun (Toyota Technological Institute, Chicago), Thomas Gaertner (Fraunhofer, Bonn), and Stephane Canu (INSA, Rouen).