VITA

ASHUTOSH GARG

Work Address: ****,

Beckman Institute,

***, *. ******* **.

Urbana,

IL61801

Home Address: **** *. **** **. *** #108

Urbana,

IL61802

Phone No: 217-***-****

Fax No: 217-***-****

Email: abpnn9@r.postjobfree.com

Web Page:

http://www.ifp.uiuc.edu/~ashutosh

RESEARCH INTERESTS

Multimedia and Human Computer InteractionVideo AnalysisAudio-Visual Speech Detection/RecognitionActivity Detection and ModelingEmotion/Expression RecognitionDriver Work Load managementMachine LearningData dependent Generalization BoundsProbabilistic ClassifiersLearning in Cognitive SituationsOnline learning and learning with unlabeled and

noisy dataBioInformaticsGene Annotation

EDUCATION

2000-2002

PhD in Electrical

and Computer Engineering, University of Illinios at Urbana-Champaign, IL

Dissertation

title: Learning in High dimensional spaces: Applications, Theory and

Algorithms.

Advisor:

Thomas S. Huang; Co-Advisor: Dan Roth

1998-2000 M.S. in Electrical and Computer

Engineering, University of Illinios at Urbana-Champaign, IL

Thesis title:

Multimodal Speaker detection using dynamic Bayesian networks.

Advisor:

Thomas S. Huang

1993-1997

B. Tech in

Electrical Engineering, Indian Institute of Technology, New Delhi, India

Thesis title: Gesture Based

Remote Visualization.

Advisors: Santanu Choudhury and

Subhasish Banerjee

PROFESSIONAL EXPERIENCE

Jun 1998 –

present Research Assistant

Beckman

Institute for Advance Science and Technology

Advisors:

Prof. Thomas S. Huang and Prof. Dan Roth

Working

on Probabilistic and statistical Learning techniques including SVMs, Bayesian

Networks, HMM and Daynamic Bayesian networks with applications to video

analysis, activity recognition and speech recognition.

Developed

theoretical understanding of many learning algorithms in a unified framework

(PAC based, VC-dimension based and probabilistic algorithms)

May 2002-Aug 2002 Research Intern

IBM TJ

Watson Research Lab, Yorktown, NY

Advisors:

Dr. Chalapathy Neti and Dr. Gerasimos Potamianos.

Developed

an audio-visual speech recognizer.

Introduced a variation of Factorial HMM for modeling the frame level

reliability indicators in a multistream HMM framework for AVSR. Developed a

theoretical justification of stream weights using mutual information criterion

and showed that improved performance can be obtained for the task of AVSR by

using frame level reliability indicators.

May 2001-Aug 2001 Research Intern

Microsoft

Research Lab, Seattle, WA

Advisors:

Dr. Eric Horvitz and Dr. Nuria Oliver

Developed

a Hierarchical framework for detecting events in an office scenario. Hidden

Markov Models are used in discriminative fashion to model temporal events

(based on multiple modalities – audio, video and pc activity) to detect

events at different levels of temporal abstraction. The system was presented as

part of the Bill Gates keynote address at the International Joint Conference of

Artificial Intelligence (IJCAI’01). Results published at ICMI’02,

CVPR’01

May 2000-Aug 2000 Research Intern

Cambridge Research Lab (HP Computer Corp.), Cambridge, MA

Advisors: Prof. Vladimir Pavlovic and Prof. Simon Kasif

Annotation

of the Human genome (chromosome 22) and Drosophilae (fruit fly) data using mixture

of experts framework and input/output Hidden Markov Model. A novel I/OHMM based

mixture of experts model is developed that can be used to combine the output of

the temporal sequences to improve the classification performance. Presented at

Computational Genomics’00 and Journal of Bio-Informatics.

May 1999-Aug 1999 Research Intern

Cambridge Research Lab (HP Computer Corp.), Cambridge, MA

Advisors: Prof. Vladimir Pavlovic and Prof. Jim Rehg

Developed

a Multimodal Speaker Detection system using Dynamic Bayesian Networks.

Introduced the framework of “Error feedback DBN” for fusing the

information from different modalities. Excellent results for the task of

speaker detection were obtained using this model. Presented at CVPR’00,

ICMI’00, FG’00.

May 1997-May 1998 Research and Development

Engineer

Synopsys

Inc., Bangalore, India

Worked

on HW/SW Co-Verification tool (EAGLEI). Developed processor models for various

processors like Hitachi SH3, OakDSP. Worked on Binary Decision Diagrams for

cycle based Verilog simulator.

TEACHING

EXPERIENCE

Aug 2002-Dec 2002 Teaching Assistant

for Graduate course on Image processing (ECE447), UIUC

Gave

lectures on Fractal Image coding, Designed homeworks and machine problems,

graded them, had regular office hours.

Jan 2002-May 2002

Teaching Assistant for

Graduate/Undergraduate course on Multimedia Signal Processing (ECE371TSH), UIUC

Was

involved in designing the course including the course content, structure,

reference books, problem sets and machine problems. Gave lectures on Bayesian

networks, hidden markov models and had regular office hours.

Aug 2000 – Dec 2000 Teaching Assistant for Graduate course on Image processing

(ECE447), UIUC

Gave

lectures on hidden markov models. Designed homeworks and machine problems,

graded them, had regular office hours.

AWARDS

and HONORS

Robert T. Chien award for excellence in research in Electrical and

Computer Engineering department at UIUC for the year 2003.

Nomination

for the Best paper award in the conference – Algorithmic Learning

Theory’01 (Paper is adjudged as one of the top 3 papers of the conference).

IBM Research Fellowship for the year 2001-2002.

Presented

the system (which was build by me at Microsoft Research) as part of the Key

Note address given by Bill Gates at the International joint conference of

Artificial Intelligence’01.

Best Project of the year (1996-97) Award by IIT Delhi.

ICMI Stay Ahead Award (1996-97) by IIT Delhi for the

best project in Electrical and Computer Science department.

3rd

Rank in Entrance examination for the regional engineering colleges (out

of 200,000 applicants)

Invited

to give lectures at TsinghuaUniversity in Nov’2002.

99.8

percentile in the GATE’97 (Graduate aptitude test in Engineering)

conducted by IITs and IISc, India.

Highest

ranking in exit review while doing summer internship at Microsoft Research.

Highest

ranking in exit review while doing summer internship at Schlumberger Inc (Cairo, Egypt).

PROFESSIONAL

ACTIVITIES

Program Committee member for ICML’2003.

Program Co-chair “Very Low Bitrate Video Coding Workshop” (VLBV’98)

held at Beckman Institute, UIUC.

Student Member IEEE and member Phi Kappa Phi Honor

Society

Reviewer of IEEE Trans. on Pattern Analysis and

Machine Intelligence (PAMI) and many other International Vision conferences

including FG’2000, CVPR’2000, ICPR’2000, ICIP’2000,

ICCV’2001, ICML’2002.

INVITED

LECTURES

A brief introduction to Bayesian Networks,

Mar’2001, IIT Delhi, India.

Event Detection and Conditional Entropic HMM,

Aug’2002, Avaya Research Lab, NJ.

Event Detection and Mutual information HMM,

Aug’2002, Mitsubishi Electric Research Lab, NJ.

Introduction to Support Vector Machines,

Nov’2002, TsinghuaUniversity, Beijing, China

Activity Detection in office Environments,

Nov’2002, Institute of Automation, ChineseAcademy of Sciences, Beijing, China

PATENTS FILED

1. V. Pavlovic, Ashutosh

Garg and S.

Kasif,

“A Bayesian framework for

combining gene predictions” Patent Disclosure filed. (with HP research Lab)

2. Nuria Oliver and Ashutosh Garg,

“Maximizing Mutual Information

between observations and hidden states to minimize classification errors”

Patent Disclosure filed. (With Microsoft Research)

3. Nuria Oliver, Eric Horvitz and Ashutosh Garg,

“Layered models for Context awareness” Patent Disclosure

filed. (With Microsoft Research)

PUBLICATIONS

Journal

Papers (Refreed)

1. Vladimir Pavlovic, Ashutosh Garg and

Simon Kasif, “A Bayesian Framework for combining gene predictions,”

Journal of BioInformatics, Jan’2002

2. Ashutosh Garg, Vladimir Pavlovic, Jim Rehg, and Thomas S. Huang,

“Boosted Dynamic Bayesian Networks for multimodal Speaker Detection”

submitted to Proceedings of IEEE.

3. Gerasimos Potamianos, Chalapathy Neti, Guillaurne Gravier,

Ashutosh Garg, Andrew Senior, “Recent Advances in the Automatic

Recognition of Audio-Visual Speech” submitted to Proceedings of IEEE.

4. Ira Cohen, Nicu Sebe, Larry Chen,

Ashutosh Garg, Thomas S. Huang, “Facial Expression Recognition from

Video Sequences: Temporal and Static Modeling”, submitted to CVIU

special issue on Face recognition (currently being reviewed)

5. Ashutosh Garg, Sariel Har-Peled and Dan Roth, “Generalization

bounds and Margin distribution,” submitted to Machine Learning

Journal.

6. Ashutosh Garg, Dan Roth and Thomas S. Huang,

“Sequential models in Mulitmedia Analysis,” in preparation for

submission to IEEE Trans. on Pattern Analysis and Machine Intelligence.

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