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Venu Govindaraju, PhD

Vice President for Research and Economic Development, Interim

SUNY Distinguished Professor of Computer Science and Engineering

SUNY Distinguished Professor Venu Govindaraju is the Interim Vice President for Research & Economic Development at the University at Buffalo, the State University of New York (UB). He is responsible for managing UB's research enterprise, university/industry relations and economic development. The university's research contributes to the economic and cultural vitality of New York State and around the world, by discovering knowledge that helps resolve global challenges.

Govindaraju also is the founding director of the Center for Unified Biometrics and Sensors (CUBS). He holds four patents, has received several major professional society awards and co-authored about 400 scientific papers. He serves on the editorial boards of premier journals and belongs to a select group of computer scientists who are fellows of both the Association for Computing Machinery and the Institute of Electrical and Electronic Engineers


PhD, University at Buffalo, State University of New York, 1992

MS, University at Buffalo, State University of New York, 1988

BTech, Indian Institute of Technology (IIT), Kharagpur, 1986

Research Interests

Govindaraju's research focuses on machine learning and pattern recognition and his seminal work in handwriting recognition was at the core of the first handwritten address interpretation system used by the U.S. Postal Service. He has been the principal investigator or co-principal investigator on roughly $65 million in research funding.  


  • US 20060078171: “Biometric Convolution Using Multiple Biometrics”, V. Govindaraju, S. Chikkerur, and S. Chavan. 2010
  • US 7,580,551.  “Method  and  Apparatus  for  Analyzing  And/Or  Comparing  Handwritten  And/Or
  • Biometric Samples”, S. Srihari, V. Govindaraju, et. al. 2009
  • WO/2008/121183. “Method  for  Diagnosis of  Physiological  States  by  Detecting  Patterns  of  Volatile
  • Analytes”,  F. Bright,  A. Cartwright, V. Govindaraju, H. Wesley, and A. Titus. 2008
  • US 5,515,455: “System for Recognizing Handwritten Words of Cursive Script”, V. Govindaraju, D. Wang, and S. Srihari. 1996

Honors and Awards

Major Professional Society Awards

  • IEEE Technical Achievement Award, 2010. “For pioneering contributions to handwriting systems” for sustained achievement over last 10-15 years
  • MIT  Global  Indus  Technovator  Award  2004,  MIT  Indian  Business  Club,  Cambridge,  MA:  “For pioneering endeavors at the frontiers of technological innovation”
  • 40 Under Forty Honoree Business First, Nov. 7, 2002, Buffalo, NY
  • ICDAR Outstanding Young Investigator, 2001 (IAPR) “For visibly demonstrating the utility of pattern recognition algorithms  in  complex  applications  of  postal  document  handling  and  for  outstanding scientific productivity”

Conference Best Paper/Competition Awards

  • ICFHR, ITESOFT Best Paper Award, Kolkata, India, 2010
  • ICPR, IBM Best Student Paper Award, (X. Peng), Istanbul, Turkey, 2010
  • ICDAR Best Paper Award, Barcelona, 2009
  • ICDAR 1st Place in Line segmentation competition, Barcelona, 2009

Industry Faculty Research Awards

  • Qualcom (2014), eBay (2012), Fujitsu (2011, 2013), HP (2008, 2009, 2010), Google (2005, 2011), IBM (2003-04)

University at Buffalo Awards

  • SUNY Distinguished Professor (2010) – Highest rank in SUNY (State University of New York) system.
  • UB Distinguished Professor (2009)
  • Visionary Innovator (2004, ‘08, ‘09), UB STOR
  • 2007 SUNY Chancellor’s Award for Scholarship and Creative Activities
  • 2003 Exceptional Scholar Award, University at Buffalo, NY
  • 2002 SUNY Research Foundation Research and Scholarship Award
  • 1998 Outstanding Research Award (presented by UB President and VP of USPS)


  • Fellow of SPIE – Int. Society for Optics and Photonics, 2013, “For document recognition and retrieval”
  • Fellow  of  AAAS  –  American  Association  for  the  Advancement  of  Science,  2010,  “For  outstanding contributions to the areas of biometrics and document recognition and retrieval”
  • Fellow  of  ACM  –  Association  of  Computing  Machinery,  2009,  “For  contributions  to  handwritten document image analysis, recognition, and retrieval”
  • Fellow  of  IEEE  -  Institute  of  Electrical  and  Electronics  Engineers,  2006,  “For  contributions  to handwriting recognition”
  • Fellow of IAPR – Int. Association of Pattern Recognition, 2004, “For contributions to advances in handwriting recognition”
  • Fellow of IETE – Institute of Electronics and Telecommunication Engineers, 2002

Selected Professional Activities

  • President, IEEE Biometrics Council (2015-)
  • Editor-in-Chief, IEEE Biometrics Council Compendium (2012-)
  • Editorial boards:
    • IEEE Access (2015-)
    • IEEE Transactions on Information Forensics and Security (2015-)
    • IET Biometrics Identification (2012-)
    • International Journal of Document Analysis and Recognition (2003-)
    • IEEE Transactions of Pattern Analysis and Machine Intelligence (2001-2005)
    • IEEE Systems, Man, and Cybernetics (2000-2008)
    • Pattern Analysis and Applications (2004-2008)
    • Pattern Recognition Journal (1997-2005)
  • General Co-Chair of IAPR International Conference on Document Analysis and Recognition (2013), Multilingual OCR Workshop (2009, 2011), International Workshop on Document Analysis Systems (2010), 4th IEEE AutoID (2004).
  • General Program Co-chair of IAPR International Conference on Document Analysis and Recognition (2005), CVPR Biometrics workshop (2006-12)
  • Program Committee member of over 70 conferences and  workshops
  • Given more than 110 invited talks including over 25 keynotes and over 25 colloquium talks

Research Highlights

  • Computing Community Consortium, March 25, 2009 - Computing Research that Changed the World: Reflections and Perspectives, “…Using a learning-based system developed at SUNY Buffalo by Venu Govindaraju and colleagues, 25 billion letters a year are processed automatically by the US postal service - bar-coded for precise deliver - saving hundreds of millions of dollars...”
  • Transferred technology to the Postal Services in US, Australia, and UK which was deployed
  • Principal or Co-Investigator of sponsored projects funded for about 60 million dollars
  • Total scientific publications: 360 (75 journal papers; 25 book chapters); Edited books: 4
  • Total citations is 7000; h-index is 41; DBLP count of 260 (among most prolific authors)
  • Research  reported by  BBC  Radio April 2012; Scientific American, March  2012; ACM TechNews, October 2010, September 2007, January 2005; MIT Tech Review, January 2009, October 2009

Document Recognition and Retrieval

Handwriting Recognition Models: Developed the first handwritten word recognition module suitable for real time applications using an innovative dynamic matching algorithm to assign automatically segmented pieces of words to lexical entities.  

Pattern Recognition Techniques: Developed the first taxonomy of the complexity of classification combination methodologies and a guideline for choosing a particular type of fusion technique.

Document Analysis Systems: His innovative methodology enabled solutions to several practical document processing systems. The postal handwritten address system was deployed in the field with unprecedented success; bank check reading systems could leverage the recognition of the legal amounts written in long hand; and new paradigms for recognition of medical forms became possible by modeling the relationships between handwriting and medical topics.

Innovative Applications: Developed the first simulation of human-like handwriting for designing CAPTCHAs to exploit the differential in handwriting reading proficiency between humans and machines. Innovated methods that stochastically model imperfect word segmentation inherent in handwriting which, along with his highly original work on transcript mapping, is bound to significantly impact the search engines of the future.


Fingerprint Templates and Matching: Explored innovative enhancement and binarization techniques for fingerprint images and was first to formulate the matching algorithm as a minimum cost-flow problem and coupled breadth-first search algorithm. Govindaraju proposed a novel indexing method based on minutia k-plet paths whose search time remains constant even when increasing the number of enrolled persons.

Face and Facial Expression Analysis: Proposed one of the earliest model based face recognition method and developed a face matching system based on semantic descriptors. Verified the individuality of facial expressions and showed that either displacements of facial features or the frequencies of particular expressions could be used as biometric modalities. His innovative methods for automated detection of deceit in facial expressions used changes in facial geometry, texture and changes in the eye movements.

Smart Environments: Formulated a probabilistic framework for person identification and tracking in smart environments and introduced novel methods for confirming the identity of online users. 

Center for Unified Biometrics and Sensors (CUBS)

The Center for Unified Biometrics and Sensors (CUBS) was established in October 2003 with the mission of advancing the science of biometric technologies for both civilian and homeland security applications by integrating pattern recognition and machine learning algorithms with sensors technology. Govindaraju is its founding director.

CUBS research and development activities in machine learning span two strategic application areas, biometrics and language technologies. The activities range from research on Department of Defense projects and developing prototype devices for the industry, to organizing major technical conferences and training graduate students. Federal sponsors include the Army Research Labs, the Central Intelligence Agency, the Defense Intelligence Agency, and the National Science Foundation. Industry sponsors include BBN Raytheon, Google, HP, IBM, and Lockheed Martin.


Govindaraju has contributed significantly to the advancement of his fields by mentoring post-doctoral fellows and supervising dozens of graduate students. Upon graduation, the fellows and students have been employed globally in industry-leading companies and prestigious universities.

Govindaraju has been the primary advisor for 31 doctoral students and 15 masters students. Their research has ranged from handwriting analysis and recognition to cybersecurity to statistical modeling for medical image segmentation. His students have worked on fingerprint detection, transfer learning for probability density estimation and language motivated approaches for human action recognition and spotting. His post-doctoral fellows have focused on Arabic handwriting recognition and fusion of classifiers in biometric systems.