Sushma Gundra

Sushma Gundra

Seattle, Washington, United States
1K followers 500+ connections

About

Software Engineer with ardent interests in Operating systems , Networking, Cloud…

Experience

  • Stripe Graphic

    Stripe

    Seattle, Washington, United States

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    Seattle, Washington, United States

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    Greater Seattle Area

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    Greater Seattle Area

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    San Francisco Bay Area

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    San Francisco Bay Area

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    Bengaluru Area, India

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    Bengaluru Area, India

Education

  • Cornell University Graphic
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    Activities and Societies: ACE(Association of Computer Engineers), Udhbav, IEEE MSRIT

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    Activities and Societies: Event Management,Organized the cultural and sports fests.

Publications

  • Optimal Feature Selection of Speech using Particle Swarm Optimization Integrated with mRMR for Determining Human Emotion State

    IJCA

    Speech is one of the most promising model through which various human emotions such as happiness, anger, sadness, normal state can be determined, apart from facial expressions. Researchers have proved that acoustic parameters of a speech signal such as energy, pitch, Mel frequency Cepstral Coefficient (MFCC) are vital in determining the emotion state of a person. There is an increasing need for a new Feature selection method, to increase the processing rate and recognition accuracy of the…

    Speech is one of the most promising model through which various human emotions such as happiness, anger, sadness, normal state can be determined, apart from facial expressions. Researchers have proved that acoustic parameters of a speech signal such as energy, pitch, Mel frequency Cepstral Coefficient (MFCC) are vital in determining the emotion state of a person. There is an increasing need for a new Feature selection method, to increase the processing rate and recognition accuracy of the classifier, by selecting the discriminative features. This study investigates the use of PSO integrated with mRMR (Particle Swarm Optimization integrated with Minimal-Redundancy and Maximal-Relevance) technique to extract the optimal feature set of the speech vector, thus making the whole process efficient for the GMM.

    See publication

Courses

  • ABAP beginner Training

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  • J2ME

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  • Microsoft SIlverLight beginner training

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  • SAP UI5 training

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Projects

  • Port Scan Detector


    Built a network port scan detector in C, to identify var- ious TCP port scan attacks. Implemented the libpcap interface to parse packets from an input pcap file.

  • Implementation of Hierarchical Unix-like File System

    Developed code to implement a file system in line with the Unix file system having multiple levels of inodes.
    Languages used: C

  • Multithreaded SMTP server

    Built a multithreaded SMTP server to spawn 32 threads and handle multiple clients in parallel.The client grabs a socket and starts communicating with server by conforming to a pre-defined protocol. Also, implemented mailbox and backup threads to record the mails being sent from the client from time to time.

  • Decision Tree Learning using AdaBoost and Random Forests

    Enhanced performance of ID3 decision trees using Bagging and Boosting algorithms on the Iris Flower and Heart disease datasets respectively.
    Programming Language: Octave

    Other creators
  • HTTP proxy-based malware detector

    Implemented a HTTP proxy which can interact with
    a virtual machine and replay contents from a server(web page) and detect if it is malicious or not. This web exploit scanner can detect malicious websites/domains and report it back to the client browser.

  • Map Reduce - K means Clustering

    Implemented a K means clustering algorithm to implement Map reduce in Hadoop. Ran the map and reduce jobs for a fixed number of iterations or until the centroids stopped changing.

    Other creators
  • Spiral Dataset Classification using Kernelized Support Vector Machines

    Performed classification experiments using radial basis functions and polynomial kernels of varying degrees.
    Programming Language: Octave

    Other creators

Honors & Awards

  • Best in Academics

    Department of Computer Science

  • Cultural Secretary

    Venkat International Public School

Languages

  • English

    Full professional proficiency

  • Hindi

    Full professional proficiency

  • Kannada

    Native or bilingual proficiency

  • Telugu

    Native or bilingual proficiency

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