`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`_________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`_________________
`
`
`APPLE INC.,
`Petitioner
`
`v.
`
`FACETOFACE BIOMETRICS, INC.,
`Patent Owner
`_________________
`
`
`Inter Partes Review Case No. IPR2023-00833
`U.S. Patent No. 11,042,623
`_________________
`
`
`
`DECLARATION OF BENJAMIN B. BEDERSON
`
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`I.
`
`TABLE OF CONTENTS
`
`
`INTRODUCTION ...................................................................................... 10
`A.
`BACKGROUND AND QUALIFICATIONS .................................................. 10
`II. LEGAL FRAMEWORK ........................................................................... 19
`III. OVERVIEW AND LEGAL STANDARDS ............................................. 26
`A.
`LEVEL OF A PERSON OF ORDINARY SKILL IN THE ART ........................ 26
`B.
`CLAIM CONSTRUCTION ....................................................................... 29
`C.
`CLAIMED INVENTION IN THE ’623 PATENT .......................................... 29
`D. OVERVIEW OF THE TECHNOLOGY ............................................ 34
`IV. OVERVIEW OF THE PRIOR ART ........................................................ 39
`A. OVERVIEW OF CORAZZA ..................................................................... 39
`V. GROUND I – CORAZZA DISCLOSES ALL THE
`LIMITATIONS OF CLAIMS 1, 4-6, 8, 11, AND 14-20 .......................... 46
`A.
`CLAIM 1 .............................................................................................. 46
`1(Pre) A computer device comprising at least one processor in
`communication with at least one memory device, wherein the at
`least one processor is programmed ................................................... 46
`1(a) receive a selection of an emoticon .............................................. 47
`1(b) monitor a sensor feed provided by one or more sensors of
`the computer device to detect a plurality of human facial
`expression states; ............................................................................... 48
`1(c) automatically generate a dynamic emoticon that simulates
`the detected plurality of human expression states on the
`selected emoticon based on the sensor feed of the plurality of
`human facial expression states; and .................................................. 49
`1(d) route a message with the dynamic emoticon to a second
`computer device. ................................................................................ 50
`CLAIM 4 .............................................................................................. 51
`4. The computer device of claim 1, wherein the detected
`
`B.
`
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`C.
`
`D.
`
`E.
`
`F.
`
`G.
`
`plurality of human facial expression states includes a smile, a
`laugh, a grimace, a frown, a pout, or any combination thereof. ....... 51
`CLAIM 5 .............................................................................................. 51
`5. The computer device of claim 1, wherein the detected
`plurality of human facial expression states includes an
`expression corresponding to a mood or an emotion, a micro
`expression, a stimulated expression, a neutralized expression, a
`masked expression, or any combination thereof. ............................... 51
`CLAIM 6 .............................................................................................. 52
`6. The computer device of claim 1, where the at least one
`processor is further programmed to analyze a human facial
`expression using an expression recognition process to detect
`the human facial expression state. ..................................................... 52
`CLAIM 8 .............................................................................................. 53
`8. The computer device of claim 1, wherein a human facial
`expression is captured in real-time from the one or more
`sensors. ............................................................................................... 53
`CLAIM 11 ............................................................................................ 53
`11(Pre) A computer-implemented method of operating a
`messaging application, the method comprising: ................................ 53
`11(a) receiving a selection of an emoticon; ....................................... 54
`11(b) monitoring a sensor feed provided by one or more
`sensors of a computer device to detect a plurality of human
`facial expression states; ..................................................................... 54
`11(c) automatically generating a dynamic emoticon that
`simulates the detected plurality of human facial expression
`states on the selected emoticon based on the sensor feed of the
`plurality of human facial expression states; and ............................... 54
`11(d) route a message with the dynamic emoticon to a second
`computer device. ................................................................................ 54
`CLAIM 14 ............................................................................................ 54
`14. The computer-implemented method of claim 11, wherein the
`detected plurality of human facial expression states includes a
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`H.
`
`I.
`
`J.
`
`K.
`
`L.
`
`smile, a laugh, a grimace, a frown, a pout, or any combination
`thereof. ............................................................................................... 54
`CLAIM 15 ............................................................................................ 54
`15. The computer-implemented method of claim 11, wherein the
`detected plurality of human facial expression states includes an
`expression corresponding to a mood or an emotion, a micro
`expression, a stimulated expression, a neutralized expression, a
`masked expression, or any combination thereof. ............................... 54
`CLAIM 16 ............................................................................................ 55
`16. The computer-implemented method of claim 11, further
`comprising analyzing a human facial expression using an
`expression recognition process to detect the human facial
`expression state. ................................................................................. 55
`CLAIM 17 ............................................................................................ 55
`17. The computer-implemented method of claim 11, wherein a
`human facial expression is captured in real-time from the one
`or more sensors. ................................................................................. 55
`CLAIM 18 ............................................................................................ 55
`18. The computer-implemented method of claim 11, further
`comprising continuously detecting human facial expression
`states using one or more sensors of the computer device after
`detecting a first human facial expression state. ................................. 55
`CLAIM 19 ............................................................................................ 56
`19(Pre) At least one non-transitory computer-readable storage
`media having computer-executable instructions embodied
`thereon, wherein when executed by a computer device having at
`least one processor in communication with at least one memory
`device, the computer-executable instructions cause the
`processor to: ....................................................................................... 56
`19(a) receive a selection of an emoticon; .......................................... 57
`19(b) monitor a sensor feed provided by one or more sensors of
`the computer device to detect a plurality of human facial
`expression state; ................................................................................. 57
`
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`19(c) automatically generate a dynamic emoticon that displays
`the selected emoticon changing to the plurality of detected
`human facial expression states based on the sensor feed of the
`plurality of human facial expression states; and ............................... 57
`19(d) route a message with the dynamic emoticon to a second
`computer device, ................................................................................ 57
`19(e) wherein the second computer device displays the selected
`emoticon changing to the detected plurality of human facial
`expression states. ................................................................................ 57
`M. CLAIM 20 ............................................................................................ 57
`20. The at least one non-transitory computer-readable storage
`media of claim 19, wherein the detected plurality of human
`facial expression states includes a smile, a laugh, a grimace, a
`frown, a pout, or any combination thereof. ........................................ 57
`VI. GROUND II – CORAZZA IN VIEW OF BROWN TEACH ALL
`THE LIMITATIONS OF CLAIMS 1-2, 4-8, 11-12, AND 14-20 ............ 58
`A. OVERVIEW OF BROWN ......................................................................... 58
`B.
`CLAIM 1 .............................................................................................. 62
`1(Pre) A computer device comprising at least one processor in
`communication with at least one memory device, wherein the at
`least one processor is programmed to ............................................... 62
`1(a) receive a selection of an emoticon .............................................. 62
`1(b) monitor a sensor feed provided by one or more sensors of
`the computer device to detect a plurality of human facial
`expression states; ............................................................................... 68
`1(c) automatically generating a dynamic emoticon that
`simulates the detected plurality of human facial expression
`states on the selected emoticon based on the sensor feed of the
`plurality of human facial expression states; and ............................... 69
`1(d) route a message with the dynamic emoticon to a second
`computer device. ................................................................................ 69
`CLAIM 2 .............................................................................................. 72
`2. The computer device of claim 1, wherein a messaging
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`D.
`
`E.
`
`F.
`
`G.
`
`H.
`
`I.
`
`interface is used to compose the message, and wherein the
`dynamic emoticon is embedded as part of message. .......................... 72
`CLAIM 4 .............................................................................................. 72
`4. The computer device of claim 1, wherein the detected
`plurality of human facial expression states includes a smile, a
`laugh, a grimace, a frown, a pout, or any combination thereof. ....... 72
`CLAIM 5 .............................................................................................. 72
`5. The computer device of claim 1, wherein the detected
`plurality of human facial expression states includes an
`expression corresponding to a mood or an emotion, a micro
`expression, a stimulated expression, a neutralized expression, a
`masked expression, or any combination thereof. ............................... 72
`CLAIM 6 .............................................................................................. 72
`6. The computer device of claim 1, where the at least one
`processor is further programmed to analyze a human facial
`expression using an expression recognition process to detect
`the human facial expression state. ..................................................... 72
`CLAIM 7 .............................................................................................. 73
`7. The computer device of claim 1, wherein the dynamic
`emoticon is embedded at a displayable portion of the message. ....... 73
`CLAIM 8 .............................................................................................. 73
`8. The computer device of claim 1, wherein a human facial
`expression is captured in real-time from the one or more
`sensors. ............................................................................................... 73
`CLAIM 11 ............................................................................................ 73
`11(Pre) A computer-implemented method of operating a
`messaging application, the method comprising: ................................ 73
`11(a) receiving a selection of an emoticon; ....................................... 73
`11(b) monitoring a sensor feed provided by one or more
`sensors of a computer device to detect a plurality of human
`facial expression states; ..................................................................... 73
`11(c) automatically generating a dynamic emoticon that
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`J.
`
`K.
`
`L.
`
`simulates the detected plurality of human facial expression
`states on the selected emoticon based on the sensor feed of the
`plurality of human facial expression states; and ............................... 74
`11(d) route a message with the dynamic emoticon to a second
`computer device. ................................................................................ 74
`CLAIM 12 ............................................................................................ 74
`12. The computer-implemented method of claim 11, wherein a
`messaging interface is used to compose the message, and
`wherein the dynamic emoticon is embedded as part of the
`message. ............................................................................................. 74
`CLAIM 14 ............................................................................................ 74
`14. The computer-implemented method of claim 11, wherein the
`detected plurality of human facial expression states includes a
`smile, a laugh, a grimace, a frown, a pout, or any combination
`thereof. ............................................................................................... 74
`CLAIM 15 ............................................................................................ 75
`15. The computer-implemented method of claim 11, wherein the
`detected plurality of human facial expression states includes an
`expression corresponding to a mood or an emotion, a micro
`expression, a stimulated expression, a neutralized expression, a
`masked expression, or any combination thereof. ............................... 75
`M. CLAIM 16 ............................................................................................ 75
`16. The computer-implemented method of claim 11, further
`comprising analyzing a human facial expression using an
`expression recognition process to detect the human facial
`expression state. ................................................................................. 75
`CLAIM 17 ............................................................................................ 75
`17. The computer-implemented method of claim 11, wherein a
`human facial expression is captured in real-time from the one
`or more sensors. ................................................................................. 75
`CLAIM 18 ............................................................................................ 75
`18. The computer-implemented method of claim 11, further
`comprising continuously detecting human facial expression
`
`N.
`
`O.
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`P.
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`states using one or more sensors of the computer device after
`detecting a first human facial expression state. ................................. 75
`CLAIM 19 ............................................................................................ 76
`19(Pre) At least one non-transitory computer-readable storage
`media having computer-executable instructions embodied
`thereon, wherein when executed by a computer device having at
`least one processor in communication with at least one memory
`device, the computer-executable instructions cause the
`processor to: ....................................................................................... 76
`19(a) receive a selection of an emoticon; .......................................... 76
`19(b) monitor a sensor feed provided by one or more sensors of
`the computer device to detect a plurality of human facial
`expression state; ................................................................................. 76
`19(c) automatically generate a dynamic emoticon that displays
`the selected emoticon changing to the plurality of detected
`human facial expression states based on the sensor feed of the
`plurality of human facial expression states; and ............................... 76
`19(d) route a message with the dynamic emoticon to a second
`computer device, ................................................................................ 77
`19(e) wherein the second computer device displays the selected
`emoticon changing to the detected plurality of human facial
`expression states. ................................................................................ 77
`CLAIM 20 ............................................................................................ 77
`20. The at least one non-transitory computer-readable storage
`media of claim 19, wherein the detected plurality of human
`facial expression states includes a smile, a laugh, a grimace, a
`frown, a pout, or any combination thereof. ........................................ 77
`VII. GROUND III – CORAZZA IN VIEW OF BROWN AND GATES
`TEACHES ALL THE LIMITATIONS OF CLAIMS 3, 9-10, AND
`13 .................................................................................................................. 77
`A. OVERVIEW OF GATES .......................................................................... 78
`B.
`CLAIM 3 .............................................................................................. 84
`3. The computer device of claim 1, wherein the at least one
`
`Q.
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`C.
`
`D.
`
`processor is further programmed to detect a facial profile and
`to match the facial profile against a known facial profile
`utilizing a facial recognition process to authenticate an
`operating user. ................................................................................... 84
`CLAIM 9 .............................................................................................. 88
`9. The computer device of claim 1, wherein the at least one
`processor is further programmed to detect a plurality of human
`facial expression states on a periodic basis based on a
`predetermined period of time. ............................................................ 88
`CLAIM 10 ............................................................................................ 93
`10. The computer device of claim 1, wherein the sensor feed is
`analyzed for an expression recognition process and a biometric
`recognition process. ........................................................................... 93
`CLAIM 13 ............................................................................................ 95
`13. The computer-implemented method of claim 11, further
`comprising detecting a facial profile and matching the facial
`profile against a known facial profile utilizing a facial
`recognition process to authenticate an operating user. ..................... 95
`VIII. CONCLUSION ........................................................................................... 95
`
`
`E.
`
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`I, Benjamin B. Bederson, hereby declare the following:
`
`I.
`
`INTRODUCTION
`1. My name is Benjamin B. Bederson, and I am over 21 years of age and
`
`otherwise competent to make this Declaration. I make this Declaration based on facts
`
`and matters within my own knowledge and on information provided to me by others,
`
`and, if called as a witness, I would competently testify to the matters set forth herein.
`
`I have been retained by counsel for the Petitioner Apple Inc. (“Apple” or
`
`“Petitioner”) to provide my independent opinions on certain issues requested by
`
`Counsel for Petitioner relating to the accompanying Petition for Inter Partes Review
`
`of U.S. Patent No. 11,042,623 (“the ’623 Patent”). I understand that the Challenged
`
`Claims are claims 1-20. My opinions are limited to those Challenged Claims.
`
`2. My compensation in this matter is not based on the substance of my
`
`opinions or the outcome of this matter. I have no financial interest in Petitioner. I am
`
`being compensated at an hourly rate of $600 for my analysis and testimony in this
`
`case.
`
`A. Background and Qualifications
`3.
`I have summarized in this section my educational background, career
`
`history, and other qualifications relevant to this matter. I have also included a current
`
`version of my curriculum vitae attached herein as Appendix A.
`
`4.
`
`I received a Bachelor of Science degree in Computer Science with a
`
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`minor in Electrical Engineering from Rensselaer Polytechnic Institute (“RPI”) in
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`1986. I received a Master of Science degree and a Ph.D. in Computer Science from
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`New York University (“NYU”) in 1989 and 1992, respectively.
`
`5.
`
`Since 1998, I have been a Professor of Computer Science at the
`
`University of Maryland (“UMD”), where I have joint appointments at the Institute
`
`for Advanced Computer Studies and the College of Information Studies (Maryland’s
`
`“iSchool”) and am currently Professor Emeritus. I was also Associate Provost of
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`Learning Initiatives and Executive Director of the Teaching and Learning
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`Transformation Center from 2014 to 2018. I am a member and previous director of
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`the Human-Computer Interaction Lab (“HCIL”), the oldest and one of the best
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`known Human-Computer Interaction research groups in the country. Last year, I
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`co-founded the J.S. Bryant School, a therapeutic high school to open to students in
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`2025. I was also co-founder and Chief Scientist of Zumobi, Inc. from 2006 to 2014,
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`a Seattle-based startup that is a publisher of content applications and advertising
`
`platforms for smartphones. I am also co-founder and co-director of the International
`
`Children’s Digital Library (“ICDL”), a web site launched in 2002 that provides the
`
`world’s largest collection of freely available online children’s books from around
`
`the world with an interface aimed to make it easy for children and adults to search
`
`and read children’s books online. I was also co-founder and Chief Technology
`
`Officer of Hazel Analytics from 2014-2023, a data analytics company whose
`
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`product sends alerts in warranted circumstances. In addition, I have for more than
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`15 years consulted for numerous companies in the area of user interfaces, including
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`EPAM, Hillcrest Labs, Lockheed Martin, Logitech, Microsoft, NASA Goddard Space
`
`Flight Center, the Palo Alto Research Center, and Sony.
`
`6.
`
`For more than 30 years, I have studied, designed, and worked in the field
`
`of computer science and human-computer interaction. My experience includes 30
`
`years of teaching and research, with research interests in human-computer
`
`interaction and the software and technology underlying today’s interactive
`
`computing systems. This includes the design and implementation of software
`
`applications on mobile devices, including smart phones and PDAs, such as my work
`
`on DateLens, LaunchTile, and StoryKit described below.
`
`7. At UMD, my research is in the area of Human-Computer Interaction
`
`(“HCI”), a field that relates to the development and understanding of computing
`
`systems to serve users’ needs. Researchers in this field are focused on making
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`universally usable, useful, efficient, and appealing systems to support people in
`
`their wide range of activities. My approach is to balance the development of
`
`innovative technology that serves people’s practical needs. Example systems
`
`following this approach that I have built include PhotoMesa (software for end
`
`users to browse personal photos), DateLens (2002 software for end users to use
`
`their mobile devices efficiently access their calendar information), LaunchTile
`
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`(2005 “home screen” software for mobile devices to allow users to navigate apps
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`in a zoomable environment), SpaceTree (2001 software for end users to efficiently
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`browse very large hierarchies), ICDL (International Children’s Digital Library I
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`co-founded in 2001), and StoryKit (a 2009 iPhone app for children to create
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`stories).
`
`8.
`
`LaunchTile led to my creation of Zumobi in 2006, where I was
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`responsible for investigating new software platforms and developing new user
`
`interface designs that provide efficient and engaging interfaces to permit end users
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`to access a wide range of content on mobile platforms (including the iPhone and
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`Android-based devices). For example, I designed and implemented software called
`
`“Ziibii,” a “river” of news for iPhone, software called “ZoomCanvas,” a zoomable
`
`user interface for several iPhone apps, and iPhone apps including “Inside Xbox” for
`
`Microsoft and Snow Report for REI. At the International Children’s Digital Library
`
`(ICDL), I have since 2002 been the technical director responsible for the design and
`
`implementation of
`
`the web site, www.childrenslibrary.org
`
`(originally at
`
`www.icdlbooks.org). In particular, I have been closely involved in designing the
`
`user interfaces as well as the software architecture for the web site since its inception
`
`in 2002. I developed a mobile version of the ICDL for iPhone in 2007 that was
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`publicly available in Apple’s App Store. I then developed a mobile app called
`
`StoryKit that allowed children to create and tell stories using an iPhone and its touch
`
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`screen. It was publicly available in Apple’s App Store starting in 2009.
`
`9. Beginning in the mid-1990s, I have been responsible for the design and
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`implementation of numerous other web sites in addition to the ICDL. For example,
`
`I designed and built my own professional web site when I was an Assistant Professor
`
`of Computer Science at the University of New Mexico in 1995 and have continued
`
`to design, write the code for, and update both that site (which I moved to the
`
`University of Maryland in 1998, currently at http://www.cs.umd.edu/~bederson/) as
`
`well
`
`as
`
`numerous
`
`project
`
`web
`
`sites,
`
`such
`
`as
`
`Pad++,
`
`http://www.cs.umd.edu/hcil/pad++/. I received the Janet Fabri Memorial Award for
`
`Outstanding Doctoral Dissertation for my Ph.D. work in robotics and computer
`
`vision. I have combined my hardware and software skills throughout my career in
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`Human-Computer Interaction research, building various interactive electrical and
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`mechanical systems that couple with software to provide an innovative user
`
`experience.
`
`10. One of my projects involved image processing as it related to personal
`photo management. For example, I wrote a 2003 paper1 describing the use of image
`
`processing to analyze image content and automatically crop away portions of the
`
`
`1 Bongwon Suh, Haibin Ling, Benjamin B. Bederson, and David W. Jacobs. 2003.
`Automatic thumbnail cropping and its effectiveness. In Proceedings of the 16th
`annual ACM symposium on User interface software and technology (UIST ’03).
`Association for Computing Machinery, New York, NY, USA, 95–104.
`https://doi.org/10.1145/964696.964707
`
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`photo leaving the salient parts which would be easier to see in small thumbnails.
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`11.
`
`In 2007, I wrote a paper that continued that line of work, describing
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`further image processing to organize photos based on identifying the clothes that
`
`people were wearing to group them.
`
`
`
`
`
`12. My work has been published extensively in more than 160 technical
`
`publications, and I have given about 100 invited talks, including 9 keynote lectures.
`
`I have won numerous awards including the Brian Shackel Award for “outstanding
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`contribution with international impact in the field of HCI” in 2007, and the Social
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`Impact Award in 2010 from Association for Computing Machinery’s (“ACM”)
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`Special Interest Group on Computer Human Interaction (“SIGCHI”). ACM is the
`
`primary international professional community of computer scientists, and SIGCHI
`
`is the primary international professional HCI community. I have been honored by
`
`both professional organizations. I am an “ACM Distinguished Scientist,” which
`
`“recognizes those ACM members with at least 15 years of professional experience
`
`and 5 years of continuous Professional Membership who have achieved significant
`
`accomplishments or have made a significant impact on the computing field.” I am
`
`a member of the “CHI Academy,” which is described as follows: “The CHI
`
`Academy is an honorary group of individuals who have made substantial
`
`contributions to the field of human-computer interaction. These are the principal
`
`leaders of the field, whose efforts have shaped the disciplines and/or industry and
`
`led the research and/or innovation in human-computer interaction.” The criteria for
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`election to the CHI Academy are: cumulative contributions to the field; impact on
`
`the field through development of new research directions and/or innovations; and
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`(3) influence on the work of others.
`
`13.
`
`I have appeared on radio shows numerous times to discuss issues
`
`relating to user interface design and people’s use and frustration with common
`
`technologies, web sites, and mobile devices. My work has been discussed and I have
`
`been quoted by mainstream media around the world over 120 times, including by
`
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`the New York Times, the Wall Street Journal, the Washington Post, Newsweek, the
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`Seattle Post-Intelligencer, the Independent, Le Monde, NPR’s All Things
`
`Considered, New Scientist Magazine, and MIT’s Technology Review.
`
`14.
`
`I have designed, programmed, and publicly deployed dozens of user-
`
`facing software products that have cumulatively been used by millions of users. My
`
`work is cited in patents by several major companies, including Amazon, Apple,
`
`Facebook, Google, and Microsoft.
`
`15.
`
`I am the co-inventor of 14 U.S. patents and 20 U.S. patent applications
`
`which are generally directed to user interfaces/experience.
`
`16. Based on my experiences described above, and as indicated in my
`
`Curriculum Vitae, I am qualified to provide the following opinions with respect to
`
`the patents in this case. Additionally, I was at least a person having ordinary skill in
`
`the art as of the priority date of the ’623 Patent as described herein.
`
`17.
`
`In writing this declaration, I have considered my own knowledge and
`
`experience, including my work experience in the fields of computer science and
`
`human-computer interaction; my experience in teaching those subjects; my
`
`experience in developing companies and products in those subjects; and my
`
`experience in working with others involved in those fields, my experience in
`
`designing and implementing software systems, and user interfaces. In reaching my
`
`opinions in this matter, I have focused on the following references and materials:
`
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`Description
`Exhibit
`Exhibit 1001 U.S. Patent No. 11,042,623 (“’623 Patent”)
`Exhibit 1002 File History of U.S. Patent No. 11,042,623 (“’623 File History”)
`Exhibit 1004 U.S. Patent Publication No. 2013/0235045 to Corazza et al.
`(“Corazza”)
`Exhibit 1005 U.S. Patent 8,620,850 to Brown et al. (“Brown”)
`Exhibit 1006 U.S. Patent No. 9,256,748 to Gates et al. (“Gates”)
`Exhibit 1007 FaceToFace Complaint
`Exhibit 1008 Carnegie Mellon’s website memorializing Scott Fahlman’s
`original post, http://www.cs.cmu.edu/~sef/Orig-Smiley.htm.
`Exhibit 1009 U.S. Patent Publication No. 2006/0015812 to Cunningham et al.
`(“Cunningham”)
`Exhibit 1010 U.S. Patent Publication 2004/0018858 to Nelson (“Nelson”)
`Exhibit 1011 U.S. Patent Application No. 2010/0177116 to Dahllof et al.
`(“Dahllof”)
`Exhibit 1012 U.S. Patent Application No. 2005/0195927
`(“Solonen”)
`Exhibit 1013 Eudora Email 6.2, pages 47-50
`Exhibit 1016 U.S. Patent No. 9,425,974 to Tucker et al. (“Tucker”)
`Exhibit 1017 Yu Zhong, Pierre J. Garrigues, and Jeffrey P. Bigham. 2013. Real
`Time Object Scanning Using a Mobile Phone and Cloud-based
`Visual Search Engine, Proceedings of the 15th International ACM
`SIGACCESS Conference on Computers and Accessibility
`(AS