Ranjit Padmanabhan

Ranjit Padmanabhan

Director of Engineering at Comcast Silicon Valley Innovation Center

San Francisco Bay Area
Computer Software

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Ranjit Padmanabhan's Overview

  • Co-Founder & Director of Engineering at TheFind
  • Senior Technical Product Manager at Neoteris (acquired by NetScreen (acquired by Juniper Networks))
  • Chief Technology Officer at Euphorion
  • Director of Engineering at IntelliMatch (reborn as Euphorion)
  • Section Manager at Synopsys
  • Technical Lead at Zycad (acquired by Synopsys)
  • Member of Technical Staff at Hewlett-Packard
  • Applications Engineer at Monolithic Memories

264 connections

Ranjit Padmanabhan's Summary

My career spans all aspects of software delivery, ranging from development, through architecture, to leadership.

Specialties: Technical depth, Building engineering organizations, Executive leadership (global teams), Product Management, Development (I still write code), Patents, Entrepreneurship & Venture Capital

Domains: Home Automation, Mobile Applications, Vertical Search, Online Advertising, Cloud Computing, Data Science, Machine Learning, Web Services

Ranjit Padmanabhan's Experience

Public Company; 51-200 employees; Computer Software industry

April 2013Present (1 year 6 months) San Francisco Bay Area

As Comcast spreads its technology wings, the Innovation Center in Sunnyvale (aka Comcast Labs) is leading the charge.

I am managing engineering teams that build products for Xfinity Home, the X1 set-top box, and Xfinity Connect, used by millions of users, including:
-- innovative solutions around Home Automation (aka “Smart Home” aka “Internet of Things”) to integrate home devices, cloud services, and mobile apps into a unified and seamless experience.
-- mobile apps that combine messaging, voice, phone, and TV to enable families to stay connected (Family Point).
-- address book, voice mail & text messaging tools for Xfinity customers
-- infrastructure for calendar, voice, notifications, reminders, TV, and other services
-- developer platform for the X1 STB with a diverse set of interactive & content-aware Smart TV apps

Cloud services, big data analytics & data science, SQS/SNS, rules engines, Python, Cassandra, Redis, HTML5, devices, hubs, and mesh networks.

Founder & Matchematician


January 2011Present (3 years 9 months) San Francisco Bay Area

IntelliMatch is developing technology for "smart" matching jobs to candidates along with an end-to-end Talent Acquisition platform.

We build tools for Job Seekers to evaluate their fit for any job, find jobs that match their qualifications, explore resources for acquiring new skills, and apply to jobs with a single click.

Our platform enables Recruiters to make their job listings interactive, attract qualified candidates, and rank & manage applicants.

Key Technologies: Java, Ruby on Rails, JavaScript/CSS, GitHub, Heroku, AWS (EC2, S3)

VP of Engineering


Privately Held; 51-200 employees; Internet industry

January 2012January 2013 (1 year 1 month) San Francisco Bay Area

Quixey is pioneering new frontiers in App Search based on the concept of a Functional Web. The technology stack includes a rich schema, intelligent algorithms, and a comprehensive database of Apps. The Quixey API powers app search for device manufacturers, carriers, and websites.

I transformed a small & talented team of programmers into an Engineering powerhouse 8-). I hired about a dozen engineers & managers and helped transition our product line from a collection of impressive demos to a reliable & enterprise-grade product. We launched half-dozen partners in multiple countries and built a strong infrastructure for future growth.

For a few months, I also provided Product Management for our Ad Platform.

Concepts: Multi-language search, Search Advertising, Machine Learning, Cloud Computing, Big Data, Mobile applications

Key technologies: Java, AWS, Lucene, Python, MongoDB, Hadoop, JIRA, Jenkins

Consultant (Behavioral Advertising Platform)

Compass Labs

Privately Held; 11-50 employees; Internet industry

May 2010December 2011 (1 year 8 months) San Francisco Bay Area

Compass Labs targets ad campaigns into social networks based on consumer behavior and interests.

My responsibilities were cross-functional, spanning Product Management, Engineering, and Business. I was Product Manager for the current advertising applications and Technical Architect for the next-gen platform. My duties ranged from specification through project management to deployment.

Specific activities include system architecture, product specs, integration proposals for partners, UI design & development, web services, and application modules (Java).

Key Technologies: Facebook Ads API, Java, JQuery, AJAX, PHP, MySQL, AWS (EC2, EMR, Turk)

Co-Founder & VP of Products and Strategy

MashLogic (acquired by Groupon)

Privately Held; 1-10 employees; Internet industry

June 2007May 2010 (3 years)

I built a demo platform for contextual search and advertising. I was brought in as a Founder/EiR at Bessemer Venture Partners to build & lead MashLogic.

MashLogic builds products that analyze page content and dynamically add "smart links" to web pages. These links reflect user preferences (when used as a browser extension) or publisher preferences (when embedded into websites). The functionality is based on an innovative blend of rich & responsive UI, semantic intelligence on our server, web services, and high-performance architecture.

I ran the company for 2+ years, building a powerful technology platform, developing our distribution & revenue strategy and raising two rounds of funding - an angel round, and a Series A led by NEA. My responsibilities centered around Engineering and Product Management, along with the day-to-day company operations.

Key Technologies: LAMP, JavaScript, Perl, C++

Co-Founder & Director of Engineering


Privately Held; 51-200 employees; Internet industry

July 2004May 2007 (2 years 11 months) San Francisco Bay Area

I co-founded TheFind in 2004 and managed the teams responsible for UI & Online Widgets, Merchant Services, QA (offshore), and Analytics.

Key Technologies: Java, JavaScript, LAMP, Perl, C++

In 2011, I returned as a Consultant for a few months (Jan-Jul).

My primary responsibility during that time was Product Management for TheFind's Mobile applications on iPhone, Android, and iPad. This includes product definition and project management across the engineering (USA & Russia), QA (India), and design teams.

Key Technologies: Android, iOS, mobile-friendly CSS/JavaScript (smart phones & tablets), Google Analytics, Flurry

Senior Technical Product Manager

Neoteris (acquired by NetScreen (acquired by Juniper Networks))

March 2003June 2004 (1 year 4 months) San Francisco Bay Area

Product responsibility for all Neoteris' Win32 secure proxy clients.

Rolled out the SSL-VPN industry’s first Endpoint Security application in 2004.

Chief Technology Officer


October 1997March 2003 (5 years 6 months)

Architect & technical lead for numerous client engagements, focused largely on sophisticated Information Retrieval and E-Commerce projects.

Provided technology leadership for 50+ engineers across USA, Europe, and Asia.

Key Technologies: Java, Oracle, WebSphere, WebLogic

Director of Engineering

IntelliMatch (reborn as Euphorion)

May 1996October 1997 (1 year 6 months) San Francisco Bay Area

Managed an engineering team with about 20 members.

IntelliMatch built web applications to enable on-line matching between jobseekers and employers. This was done by intelligent (algorithmic/heuristic) parsing of free-text job and resume listings into structured form, driven from an underlying ontology.

Section Manager


Public Company; 5001-10,000 employees; SNPS; Computer Software industry

October 1990May 1996 (5 years 8 months)

Managed four product groups of 3-6 software engineers apiece. The primary charter was integration of Synopsys’ products with 3rd-party applications.

Public Company; 5001-10,000 employees; SNPS; Computer Software industry

July 1989October 1990 (1 year 4 months) San Francisco Bay Area

Managed an engineering group to build the front-end software pipeline for Zycad's Logic Simulation engines.

Our group was acquired by Synopsys.

Member of Technical Staff


Public Company; 10,001+ employees; HPQ; Information Technology and Services industry

December 1986July 1989 (2 years 8 months)

Developed ASIC Design Tools (schematic design, verification, layout) at the Santa Clara Design Technology Center.

Applications Engineer

Monolithic Memories

January 1984December 1986 (3 years)

Wrote PALASM and PLEASM compilers to program MMI Programmable Array Logic devices (PALs). The highlight of my work was a JEDEC decompiler that would reverse engineer chips from competitors into MMI PALs. This was very beneficial to our Sales Team.

Ranjit Padmanabhan's Certifications

  • Introduction to Programming for Musicians and Digital Artists

    • Coursera
    • December 2013
  • Songwriting

    • Coursera
    • March 2014
  • Developing Your Musicianship

    • Coursera
    • May 2014

Ranjit Padmanabhan's Skills & Expertise

  1. Engineering Management
  2. Technical Leadership
  3. Product Management
  4. Entrepreneurial Experience
  5. Raising Venture Capital
  6. Start-ups
  7. Semantic Technologies
  8. Mashups
  9. Information Retrieval
  10. Machine Learning
  11. Search
  12. Ruby on Rails
  13. JavaScript
  14. jQuery
  15. Amazon Web Services
  16. EC2
  17. MySQL
  18. Mobile Commerce
  19. Git
  20. Cloud Computing
  21. Facebook API
  22. Behavioral Targeting
  23. PHP
  24. LAMP
  25. Java
  26. Google Analytics
  27. Google API
  28. Subversion
  29. Endpoint Security
  30. Entrepreneur
  31. Entrepreneurship
  32. Amazon EC2
  33. Venture Capital
  34. Databases
  35. Architecture
  36. Analytics
  37. Web Applications
  38. Perl
  39. Big Data
  40. Scalability
  41. Distributed Systems
  42. Amazon Web Services (AWS)
  43. System Architecture
  44. Android
  45. Python

View All (45) Skills View Fewer Skills

Ranjit Padmanabhan's Patents

  • Method and system to identify records that relate to a pre-defined context in a data set

    • United States Patent 7,672,958
    • Issued March 2, 2010
    Inventors: Ranjit Padmanabhan

    The present invention provides a method and a system for identifying relevant information in a data set. The method involves the identification of nodes of interest in a tree structure. A node of interest is a node that contains information, which is relevant to a pre-defined context. The method further involves the step of iteratively extracting sub-trees from the tree structure and identifying records in the extracted sub-trees. The sub-tree is a hierarchical structure that shows the relationship of each node of interest with its ancestor nodes in the tree structure. Each record is a group of sub-tree nodes and contains at least one node of interest.

  • Method and system for information extraction

    • United States Patent 7,444,325
    • Issued October 28, 2008
    Inventors: Ranjit Padmanabhan

    A present invention provides a method and a system for extracting information related to a pre-defined context from data sets written in semi-structured or unstructured form, such as a natural language text. The information related to the pre-defined context is stored in an information store in accordance with a pre-defined structural arrangement. Further, the individual data values in the extracted information are assigned weights depending on their relevance to attributes of the predefined context. The operation of assigning weights to the structured information provides a measure for comparing the relevance of a plurality of structurally arranged information to the attributes of the pre-defined context.

  • Method and system to compare data objects

    • United States Patent 7,440,955
    • Issued October 21, 2008
    Inventors: Ranjit Padmanabhan

    The invention provides a method and system to compare data objects. Each data object is converted into a directed acyclic graph forest, which comprises one or more directed acyclic graphs. The directed acyclic graph forests corresponding to data objects are then compared to calculate a similarity score between the data objects. The similarity score is then used as a measure to determine the extent of similarity between the data objects.

Ranjit Padmanabhan's Education

University of California, San Diego

MS, Computer Science


Indian Institute of Technology, Madras

BS, Electronics Engineering


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