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SUMMARY:Designing for Collaborative Data Analysis\, a Crime Solving story 
 - Dr Tesh Goyal
DTSTART:20190711T110000Z
DTEND:20190711T120000Z
UID:TALK127198@talks.cam.ac.uk
CONTACT:Melisa B
DESCRIPTION:My research vision is to enable expert and non-experts to succ
 essfully make sense of complex world problems. As a Human-Computer Interac
 tion researcher\, I iteratively focus on studying how sensemaking is perfo
 rmed to identify challenges in collaborative data analytics\, design tools
  using computational techniques that overcome these challenges and evaluat
 e my designs using human participants to inform subsequent designs. Solvin
 g crimes correctly is one such critical and life-altering problem. Nationa
 l Registry at the University of Michigan points out that almost 175 wrongf
 ully incriminated folks were exonerated after having spent a non-trivial a
 mount of their life in prison for crimes they did not commit in 2016 alone
 . This is 4X the number 10 years ago and continues an upward trend. During
  my work\, I have discovered that sharing information socially\, succumbin
 g to cognitive biases\, and lack of support afforded by changing interacti
 on paradigms as key challenges in collaborative data analytics. Subsequent
 ly\, I have iteratively developed multiple tools\, including SAVANT REFLEC
 TIVA\, CROWDS4ANALYTICS\, TEMPORA\, and RAMPARTS to overcome these challen
 ges. My approach establishes a research framework for creating rich collab
 orative data analytic systems by: (1) utilizing human generated analytic a
 rtifacts to inform and design the interactions (2) leveraging "off-the-she
 lf" natural language processing\, sensors and crowds creatively to design 
 intelligent data analytic tools\, and (3) evaluating the effect of these d
 esigns in controlled settings to identify the cost vs. benefit of each des
 ign decision.\n\n_Tesh (Nitesh) Goyal is a researcher at Google\, where hi
 s collaborative sensemaking research has been used in Google Maps and Web 
 experiences. Tesh's research develops design approaches to build novel dat
 a analytics tools that enhance information sharing\, reduce biases using v
 isualizations\, minimize distractions using physiological data\, and suppo
 rt collaborative problem-solving with crowds. His research has also contri
 buted to the theory of Sensemaking by inventing Sensemaking Translucence a
 s a design metaphor for a mirror that enables self-reflection. He received
  his MSc in Computer Science from University of California\, Berkeley and 
 RWTH Aachen under Prof. John Canny's advice\, prior to receiving his PhD f
 rom Cornell University in Information Science where he was advised by Prof
 . Susan R. Fussell. His research has been supported by German Govt. Fellow
 ship\, National Science Foundation\, and MacArthur Genius Grant. Frequentl
 y collaborating with industry (Google Research\, Yahoo Labs\, HP Labs\, Bl
 oomberg Labs)\, he has published 10 first-author papers in top-tier HCI co
 nferences and journals (CHI\, CSCW\, JASIST\, ICTD\, ICIC and Ubicomp/IMWU
 T) and has received two best paper honorable nomination awards._
LOCATION:Nick Mackintosch Room\, Department of Psychology\, Downing Site
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