Akanksha Ganesh

• Automated review moderation, reducing manual effort by 99% across 30M+ submissions. • Built LLM-powered sentiment summaries for Reliance Retail product pages. • Launched Review, Rating, and Q&A platforms serving 396M+ users across five e-commerce brands. • Developed a centralized portal managing reviews, ratings, and Q&A across Reliance business verticals. • Built configurable administration tools for pricing rules and operational policies. • Led Reward System UI architecture from design through productio

• Served as Scrum Master and Agile Lead, increasing delivery velocity by 80%. • Core feature developer of Labview, working with Austin teams. • Automated FPGA IP licensing workflows, doubling the customer base. • Replaced manual licensing processes with scalable Azure and AWS automation.

• Developed CLI functionality for the NI Licensing Tool using C#. • Automated daily Linux builds, reducing manual build steps by 95%. • Collaborated with build engineering to improve build reliability and consistency.

• Built a Python framework automating installer execution and test-suite verification. • Reduced installer testing time by 90% through automated validation. • Developed an XML generator, reducing TestStand development time by 80%. • Generated driver-compliant TestStand files directly from technical specifications.

• Collaborated with PhD researchers to evaluate machine learning methods for viewport prediction in 360° VR video streaming. • Analysed user head-movement patterns and sequential viewing behaviour to enhance adaptive streaming strategies, reducing bandwidth usage and latency. • Designed, trained, and evaluated predictive models using deep-learning techniques for time-series and sequential-data analysis. • Contributed to research, presented experimental findings and compared model performance across diff

• Developed a transcription model for Kannada, a low-resource language, using deep-learning and parameter-efficient fine-tuning techniques. • Collected and normalized audio-transcript pairs to improve dataset quality and support reliable model training and evaluation. • Built a pronunciation lexicon to evaluate performance using Word Error Rate and Character Error Rate. • Applied CTC loss, LoRA fine-tuning, and data-augmentation techniques to improve recognition performance with limited labeled data. • Achi

Bachelor of Technology in Computer Science and Engineering with a specialisation in Data Science.