Shripad Thite's Email Addresses & Phone Numbers

Intern @ Centre for Development of Advanced Computing (C-DAC) Simulated asynchronous communication integrated circuit in VHDL to validate invariants. From 1996 to 1996 (less than a year) Pune, IndiaSoftware Engineer @ YouTube Growth through better performance: Reimplemented the YouTube experience on Android for buttery-smooth performance on resource-constrained mobile phones on 2G networks. Key contributor to Google’s growth...

Intern @ Centre for Development of Advanced Computing (C-DAC) Simulated asynchronous communication integrated circuit in VHDL to validate invariants. From 1996 to 1996 (less than a year) Pune, IndiaSoftware Engineer @ YouTube Growth through better performance: Reimplemented the YouTube experience on Android for buttery-smooth performance on resource-constrained mobile phones on 2G networks. Key contributor to Google’s growth efforts in Emerging Markets. Rewrote the key home page content discovery (browse) experience from scratch, influencing product decisions as well as making technical choices on infrastructure and libraries.https://youtube.googleblog.com/2016/09/youtube-go-youtube-reimagined-for-next.htmlhttps://www.wired.com/2016/09/youtube-reinvented-next-billion-users/ From 2015 to 2017 (2 years) San Bruno, CASoftware Engineer @ YouTube Personalized discovery and ranking of engaging videos using machine learning.Personalize the YouTube.com home page/screen to your interests by surfacing relevant content. Machine learning to facilitate serendipitous discovery of engaging content. Improved user engagement and retention on YouTube through better personalized video recommendations. Helped make YouTube a destination site by tailoring the home page content and ranking to the individual user by engineering infrastructure for large-scale machine learning recommendation systems.Member of Emmy award-winning team! Acknowledged in RecSys 2016 paper by research team: https://ai.google/research/pubs/pub45530 From April 2013 to 2017 (4 years) San Bruno, CASoftware Engineer @ Google Achievements in improving AdWords ads quality:http://adwords.google.com/support/aw/bin/answer.py?hl=en&answer=6136* OC award (formerly, EMG award) for Ads Quality improvements, specifically through better ads coverage and quality.* 3-5 patent applicationsWork:* Improve user happiness and advertiser return-on-investment and reach by increasing the coverage and relevance of ads on search queries on Google.com and partner web properties.* Design and implement algorithms to improve the targeting of ads, by using semantic knowledge, quality signals, and historical data. Implement algorithms in worldwide live servers with strict latency, CPU, and memory constraints.* Design, run, and analyze experiments affecting billions of search queries per day and billions of dollars of revenue per year.* Analyze performance of ads targeting by implementing statistical algorithms such as hypothesis testing, Bayesian inference, linear and logistic regression.* Monitor and help maintain production servers worldwide.* Mentor junior engineers and interns.* Collaborate with fantastic engineers, research scientists, and product managers in four time zones and three countries and multiple product areas. From October 2009 to October 2012 (3 years 1 month) San Francisco Bay AreaPostdoctoral Fellow @ California Institute of Technology * Research in algorithms for combinatorial problems in computational geometry and topology as a scholar in the Center for the Mathematics of Information, Information Science & Technology- Collaborated with Caltech researchers in Computer Science on problems in computational geometry and topology, such as those motivated by graphics applications.- Investigated algorithms for robust clustering and regression of interval data, with Caltech colleagues.- Researched algorithmic problems in topology such as computing optimum homotopy between curves on surfaces and homeomorphism between surfaces, and curve and surface approximation.- Researched algorithms for design and implementation of a real-time spot auction market for online display advertising, including algorithms for price support in multiple online Vickrey auctions and for inventory matching to maximize return-on-investment.* Instructor for special topics course in Computer Science: Algorithms in Geometry and Topology.* Advised OpenX Inc. on algorithms for design and implementation of a real-time spot auction market for online display advertising. Researched algorithms for price support in multiple online Vickrey auctions and for inventory matching to maximize return-on-investment. * Researched and implemented software for fast, real-time surface reconstruction from point clouds for dentistry application for Caltech researchers and Arges Imaging:https://www.caltech.edu/about/news/3-d-dentistry-37606 From September 2007 to August 2009 (2 years) Research Assistant @ University of Illinois at Urbana-Champaign • Developed algorithms for spacetime meshing to support novel spacetime-discontinuous Galerkin finite element methods. Our algorithms were the first adaptive geometric algorithms to construct efficiently solvable spacetime meshes. The meshes we construct are suitable for efficient simulation of time-dependent wave-like physical phenomena using spacetime discontinuous Galerkin finite element methods.• Designed algorithms for problems in computational topology, such as the homotopic Fréchet distance between curves and shortest pants decompositions of surfaces.• Studied motion planning and grasping problems in robotics and designed an algorithm for capturing an object in the plane with three robots.• Developed algorithms for computing a minimum-cost binary search tree or BST on a hierarchical memory model of computation, suitable for constructing such a data structure for massive data that is stored across multiple levels of memory devices with vastly different access times. From August 1999 to September 2005 (6 years 2 months) Graduate Research Assistant @ Los Alamos National Laboratory • Intern in the Basic & Applied Simulation Science (D-2) group at LANL.• Developed software tools for simulating the economics of large-scale auction-based deregulated markets for electrical power.• Designed and implemented an agent-based, microeconomic, scalable model for the simulation of a deregulated electrical power market. The project included writing computer software to simulate power demand and consumption, market forces such as monopolistic and oligopolistic behavior, external regulatory policies, and physical constraints of the power grid.• Unique features of our simulator are individual, demographics-based elastic demand profiles; configurable matching between buyers and sellers; and flexible market clearing mechanisms.• Evaluated the performance and efficiency of the market under different market clearing algorithms and sellers’ strategies. From May 2002 to August 2002 (4 months) Graduate Research Assistant @ Los Alamos National Laboratory • Intern in the Basic & Applied Simulation Science (D-2) group at LANL.• Designed algorithms for conflict-free communication in ad-hoc wireless networks and proved bounds on the maximum throughput of such networks. Conducted research on theoretical and practical problems associated with wireless radio networks. This work intersects the areas of graph theory, computational geometry, and networking. Algorithms for distance-2 edge coloring and matching in graphs modeling ad-hoc wireless networks can be applied to designing routing protocols for such networks and for predicting the network throughput. From May 2001 to August 2001 (4 months) Teaching Assistant @ University of Illinois at Urbana-Champaign Instructor: C and C++ Programming Laboratories (2 semesters)Teaching Assistant: Introduction to the Theory of Computation; Combinatorial Algorithms; Automata, Formal Languages, and Computational Complexity (3 semesters) From August 1997 to May 1999 (1 year 10 months) Graduate Research Assistant @ Los Alamos National Laboratory • Optimized numerical software libraries for external-memory computation to improve cache performance: extended blocking algorithms for matrices to improve memory-efficiency of matrix operations. Implemented and simulated the same on an SGI Origin multiprocessor system, and empirically demonstrated a significant improvement in performance.• Implemented a blocking algorithm for graphs, as proposed by Awerbuch et al., and investigated its performance. From May 1998 to August 1998 (4 months) Software Engineer @ The Climate Corporation Designed and implemented a reliable, latency-critical, RESTful web service running on Amazon Web Services (EC2 and S3) for large-scale analysis of historical weather data and weather forecasting on demand. Use Java, Clojure, and Python to create RESTful back-end web service supporting weather and agriculture tools on the front end. From October 2012 to March 2013 (6 months) San Francisco Bay AreaPostdoctoral Researcher @ Eindhoven University of Technology * Devised external-memory cache-efficient and cache-oblivious algorithms for fundamental problems in computational geometry and in optimization. Results are applicable in Geographic Information Systems, where map data is too massive to fit entirely in main memory; Algorithms are practical and implementable as well as theoretically efficient.* Designed a cache-oblivious IO-efficient version of the algorithm of Frederickson and Johnson for selecting in sorted X+Y matrices. The matrix selection algorithm is a key building block of many other optimization algorithms, sometimes serving as an alternative to expensive parametric search.* Proved bounds on the combinatorial complexity of Voronoi diagrams on realistic terrains—studied problems in combinatorial geometry. From September 2005 to August 2007 (2 years) Software Engineer @ Facebook San Francisco Bay AreaSoftware Engineer @ Uber Help rideshare and other products at Uber run more optimally by predicting the future. Inform short- and medium-term marketplace decisions. Build end-to-end Machine Learning pipelines in service of this goal. Enable "production-first" rapid iteration of ML models, features, and algorithms through a scalable framework leveraging SparkML and best software engineering practices.Worked on improving driver safety in emerging markets through reliable rider background checks. From 2017 to July 2020 (3 years) San Francisco Bay Area