(B. Tech., Electrical Engineering, IIT Kanpur (India); MS, Electrical Engineering, Stanford University)
PhD candidate, Stanford AI Lab
Computer Science,
Stanford University
Room 112, Gates Building 1A
Phone: (650)723-4310 (office), areacode-ELE-1-LAB
(cell)
asaxena at cs.stanford.edu
PhD advisor: Prof. Andrew Y. Ng
Merit Scholarship, IIT Kanpur, India (2000-2004)
IEEE India Best Student Paper Award, 2002. (Best paper among all papers in 2002, whose first author is a student in India.)
National Talent Scholar, India (1998-2004). Awarded to top 500 students selected from all students in India.
- UAI, 2008.
- AAAI, PGAI track, 2008.
- International Conference on Machine Learning (ICML), 2007.
- Robotics: Science and Systems (RSS) - Robot Manipulation: Intelligence in Human Environments, 2008.
- Robotics: Science and Systems (RSS) - Workshop on Robot Manipulation, 2007.
- International Journal of Computer Vision (IJCV), 2007-till date. (IJCV had highest impact factor of 6.085 in all computer sciene, as well as all artificial intelligence journals in 2006.)
- International Journal of Robotics Research (IJRR), 2006-till date.
- Reviewer/PC-member: European Conference on Computer Vision (ECCV) 2008.
- Machine Learning, Springer, 2007-till date.
- IEEE RAS Magazine, 2008.
- IEEE Int'l Conf on Multimedia and Expo (ICME), 2008.
- IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2007.
- Co-Reviewer, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.
- IEEE International Conference on Robotics and Automation (ICRA), 2007.
- IEEE Systems, Man and Cybernetics - Part B, 2005-till date.
- Journal of Computational and Graphical Statistics, 2005-2006
- 11th International Conference on Neural Information Processing, 2004
IEEE Student Branch Mentor (India Section) 2003-2004
Coordinator, IIT Kanpur Electronics Club, 2002-2003
STAIR: Research Project in Artificial Intelligence (CS294a) in 2007.
Machine Learning (CS 229) in 2005
I have co-supervised/worked with the following students:
- Lawson Wong (Jan 07 - till date). Won Wegbreit Prize for best Honors Thesis on his contribution to Robotic Grasping.
- Ellen Klingbeil (Oct 07 - till date), Hee-Tae Jung (Oct 07 - till date), Lawrence McAfee (Jan 08 - till date)
- Brad Gulko (Apr 07 - till date)
- Nuwan Senaratna (current), Savil Srivastava (current), Kiyoshi Shikuma (current)
- Justin Pearson (Oct 07 - Dec 07), now at AeroVironment, Inc.
- Justin Driemeyer (Oct 05 - Jun 07), now at startup ****
- Min Sun (Jun 06 - Sep 07), now PhD student at Princeton University
- Justin Kearns (Oct 05 - Aug 06), now research programmer at iRobots.
- For 3 month STAIR/CS229 projects: Tim Lipus, Nikolai Lakovlev (2007); David Ho, Seokchang Ryu (2006); Chioma Osondu (Oct 05 - Mar 06); Steve Chuang, Eric Shan (2005).
- Anthony Xiao (Jun 04 - Sep 04, at CSIRO, Australia) for Honors thesis.
Jun-Sep 2005: Microsoft Intern
Redmond, WA, USA
Invented a markov random field based learning model for an undisclosed purpose related to free-form text documents.
Jun-Sep 2004: Researcher (Industrial Trainee)
BioMedia Lab, CSIRO ICT Center, Commonwealth Sci. & Ind. Research Org. (CSIRO), Sydney, Australia
Invented a novel miniature 6-DOF wireless sourceless input device using inertial sensors.
May-Jul 2003: Analytical Research Summer Intern
Bose Corporation, Boston, USA
Developed models to predict speaker behavior.
May-Jul 2001: Research Summer Intern
Supervisor: Prof. Rajiv K. Varma, IIT Kanpur, India
Invented a wrist-worn wireless gadget that observes currents on human skin to prevent electrical shock.
2002-2004: Savior Electronics (founder)
Started a company called Savior Electronics for making wrist-worn electronic device to prevent electric shock. Won first prize in Megabucks, and seed money from SIDBI, IIT Kanpur, India.
1996-1999: Terraductus Software, one person company
In the days when pocket money was a luxury, selling dos based cheap software solutions to retail shops, used to get me some cash.
Win 08: Elements of Statistical Learning II.
Fall 07: Elements of Statistical Learning I.
Spr 07: Experimental Robotics.
Win 07: Convex Optimization II.
Fall 06: Algorithms in Biology, Computational Models of Neocortex
Spring 06: Mathematical Programming and Combinatorial Optimization
Winter 06: Probabilistic Models in AI, Linear Dynamical Systems, Stanford AI Robot
Fall 05: Text Retrieval and Web Search
Spring 05: Convex Optimization; Cognitive Neuroscience; Colloqium on AI, Geometry, Graphics, Robotics and Computer Vision
Winter 05: Intro. to Computer Vision; Applied Vision and Imaging Systems; Independent Study: Learning Depth from Single Images
Fall 04: Intro. to Linear Dynamical Systems; Statistical Signal Processing; Machine Learning
Relevant courses at IIT Kanpur (India):
Artificial Intelligence, Detection and Estimation Theory, Neural Networks, Computational Brain, Image Processing, Digital Signal processing, Information and Coding Theory.