Shivani Rao Email & Phone Number

Mountain View, Ca, Us

Wilmington, Delaware, Us

All topics in AI/ML ranging from the very basics like Supervised/ Unsupervised ML to more advance topics like Modern ML frameworks, GenAI, LLMs etc.

Sunnyvale, Ca, Us

Leading two teams with a total 11 AI/ML engineers and researchers on understanding our members and their relationship to entities in the LinkedIn ecosystem. Utilizing a variety of techniques including but not limited to Entity Resolution, Relationship extraction, Member activity understanding, Prompt engineering to aid in labeled data collection and identifying gaps in taxonomy, GNN + LLM based approaches for edge linking, LLM scaling for Training and Inference

Sunnyvale, Ca, Us

Led a team of 5 AI/ML engineers in fighting Jobs Abuse on LinkedIn Platform. Utilizing both behavioral and content based signals to build online and offline AI models to prevent and mitigate Jobs Fraud on LinkedIn platform.

Sunnyvale, Ca, Us

Redesigned the calibration pipeline for Ads PipelinesRedesigned and revamped the Response prediction models to improve modeling velocity and efficiency, led the effort across the entire org of 30 peopleStrong record of Mentoring and onboarding new engineers

Sunnyvale, Ca, Us

Built several key components of the course-recommendation pipeline: cold-start recommendations, supervised models using gradient boosted treesBuilt course to skill and video to skill taggers using semi-supervised modeling approaches.

Redwood City, Ca, Us

At Box, I was involved in building the Machine Learning platform for improving user experience through data intelligence. We analyze usage data and content to come up with suitable ML algorithms for various product use cases. I was also involved in developing scalable and reliable software for these ML algorithms in Apache Spark. Prior to my current project, I was involved in supporting and building the data- analytics Infrastructure at Box, and thus, have accrued basic experience in technologies like Kafka, RedShift, Storm, Hive, Hadoop and ETL.

Mountain View, Ca, Us

Streetview panaromic views are heavily dependent on the pose of the vehicle as captured by the GPS. In big cities, the GPS data is grossly erroneous. In such situations, images can be used to correct the pose of the vehicle offline. The pose can be corrected by using a computer vision algorithm called loopclosing. The candidate intersections are pre-computed using GPS information and transform compute to align the vehicle pose at these intersections. The alignment is used to perform optimization in order to estimate the true location of the vehicle. My internship at Google was to develop and test appearance-based loop-closing algorithms on street view data, and suggest evaluation measures of performance of the algorithms.

Santa Clara, Ca, Us

After the successful completion of MS in IIT Madras, I joined the video decode display team at Nvidia Graphics India. The work involved writing and modifying driver code at the kernel level in order to implement functionalities like post processing, image scaling, in-loop de-blocking using the GPU (Graphics processor unit). The job required one to learn or be aware of the various video-coding standards like MPEG-2, MPEG-4, WMV, H.264 and VC, knowledge of Windows OS like Windows XP, Windows Vista, co-processor architecture, low-level C programming

Phd, Electrical And Computer Engineering

Master’S Degree, Computer Science

Be, Information Technology