
Research Interests
HCI, Labor/Work, CSCW, Social Computing
I am a postdoctoral researcher in the Tandon School of Engineering at New York University.
I study how technologies shape workers' identities & practices,
designing ways to improve their work outcomes in the United States and globally. I take a mixed-methods approach. You can read my work in leading conferences, including CHI, CSCW, ICTD, & COMPASS. All of my research has been generously funded by Engaged, Einaudi, and Mozilla grants.
I also actively mentor under-resourced students and provide research assistance for non-profits. Please feel free to send me an email at varanasi[dot]r at nyu [dot] edu.
Hello!
UPDATES
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Mar'25: New paper at CHI'25. Read it here.
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Nov'24: Co-organized an extremely fulfilling workshop at CSCW'24. Read the abstract here.
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Aug'24: Teaching a graduate course on Data visualization for Business Intelligence.
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May'24: Presented the final piece of my dissertation at CHI'24. Read it here.
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Apr'24: Gave a guest lecture around Gig Work in the department of Technology, Culture and Society, NYU.
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Feb'24: Contributed to an NSF planning grant submission. My first.
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Dec'23: Registration chair for ACM GROUP'25.
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Nov'23: Finished my PhD! You can read my dissertation here.
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Jul'23: New paper at COMPASS'23 around post-pandemic teacher support. My first as a mentor!
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Apr'23: New postdoc position at NYU Tandon School from Jan. New chapter!
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Feb'23: Gave invited talk at the department of Informatics, New Jersey Institute of Technology (NJIT)
LATEST WORK
Conference paper (ACM CHI'25)
Generative AI (GAI) technologies are disrupting professional writing, challenging traditional practices. Recent studies explore GAI adoption experiences of creative practitioners, but we know little about how these experiences evolve into established practices and how GAI resistance alters these practices. To address this gap, we conducted 25 semi-structured interviews with writing professionals who adopted and/or resisted GAI. Using the theoretical lens of Job Crafting, we identify four strategies professionals employ to reshape their roles. Writing professionals employed GAI resisting strategies to maximize human potential, reinforce professional identity, carve out a professional niche, and preserve credibility within their networks. In contrast, GAI-enabled strategies allowed writers who embraced GAI to enhance desirable workflows, minimize mundane tasks, and engage in new AI-managerial labor. These strategies amplified their collaborations with GAI while reducing their reliance on other people. We conclude by discussing implications of GAI practices on writers' identity and practices as well as crafting theory.