ICPC 2024
Sun 14 - Sat 20 April 2024 Lisbon, Portugal
co-located with ICSE 2024
Smita Ghaisas

Registered user since Tue 22 May 2018

Name:Smita Ghaisas
Bio:

Smita Ghaisas is a Chief Scientist and Distunguished Engineer at TCS Research, Tata Consultancy Services Ltd (TCSL). She leads Data Driven Requirements Engineering (RE) Research. She additionally leads the technical task force for an enterprise-wide initiative in AI powered governance of contractual obligations at TCS. For this initiative, she has defined a technical strategic solution and roadmap and deployed it in coordination with the CIO’s office, Delivery Excellence Group, and Corporate Legal at TCS. Their solution for identifying, classifying, and analyzing contractual obligations has recently won the prestigious Blitz award at the TCS Global summit. She is a Senior Member of IEEE

She has published her research in international journals and conferences of high repute and serves on program committees of some of the flagship conferences in Software Engineering. She was a co-chair for the Industry Innovation track of RE 18 Banff, Canada (https://www.re18.org/organization/organizingCommittee.html), keynote speaker for SST@ICSE19 Montreal Canada (https://sst2019.chalmers.se/program/keynote/), and editor for IEEE Software Special Issue on Software Engineering in Society (https://www.computer.org/csdl/magazine/so/2020/03/09068302/1j30YOQomCQ) . She serves on the editorial board for the prestigious IEEE Empirical Software Engineering (EMSE) journal. ( Springer https://lnkd.in/gvfreCr)

Her current interests include creating scalable AI solutions that solve non-trivial practical problems in large enterprises. This involves identifying and addressing multiple interesting Data Science challenges.

Country:India
Affiliation:TCS Research
Research interests:Smita’s current research interests include disambiguation of complex and critical texts such as regulations and contracts by employing deep learning techniques coupled with learning theory-based experiments in crowd sourcing of interpretation tasks.

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