I am a Masters student in the department of Computer Science at BITS, Pilani, India.
My recent research interests have revolved around networking and machine learning. Recent works include incremental deployment of class based hybridization models for campus networks and real time monitoring of QoS metrics in Software Defined Networks (SDN). I am also working on lung cancer detection and ear biometrics leveraging CNNs and ResNets.
My work on leveraging WebRTC for P2P content distribution in web browsers and character recognition in natural scene images have been accepted at international conferences. I have been among top 25% at various data science challenges (Kaggle.com) and completed 12 MOOCs on data science and related.
I have played Tabla, drums and octopad and national level competitions.
Jun 28, 2017: Presenting SDN routing in MPI at HPDC'17, Washington DC, USA
May 22, 2017: Presenting on intelligence trade-off in control-data plane in SDN at SP'17, San Jose, CA, USA
Apr 03, 2017: Presenting an algorithm on measuring control packets in SDN at SOSR'17, Santa Clara, CA, USA
Sep 22, 2016: Presenting a WebRTC + Chord Framework at ICACNI'16, NIT, Rourkela, IN.
Mar 23, 2016: Presenting a new P2P Framework using WebRTC at AINA'16, Switzerland.
Dec 23, 2014: Presenting at Winter School on Character Recognition at IIITD, N.Delhi.
Aug 01, 2012: KVPY Fellowship awarded by DST, Govt. of India.
Oct 21, 2011: Presenting on Carbon Sequestration at CBSE National Level Science Exhibition.
Birla Institute of Technology and Science, Pilani
M.E in Computer Science 2016-18 (expected)
Department of Computer Science and Information Systems
Birla Institute of Technology and Science, Pilani
M.Sc.(Tech.) in Information Systems 2012-16
Department of Computer Science and Information Systems
Centre for excellence in SDN, BITS Pilani
WebRTC + Chord for a P2P network usinf Web Browsers
Hybrid SDN: Model design and performance evaluation
Real-time monitoring framework for Hybrid-SDN
Swathanthra Malayalam Computing, NLP on Indic Languages
Transliteration module for Indic languages for GNU/Linux
Sterlite Tech. Elitecore, Ahmedabad
Hydra, a sequence database engine for Hadoop search in shotgun mass spectrometry
Dept. of Biological Sciences, BITS Pilani
Protein sequence analysis for homology detection and structure prediction
Among the factors that determine the performance of a computationally intensive application running on a highperformance computing (HPC) system, communication between processes is vital. Our fundamental idea behind optimizing Message Passing Interface (MPI) communications is to maximize the utilization of the network of the cluster system, by deploying the Software Defined Networking (SDN) paradigm. We identify two primary issues: overuse of shortest paths leaving them choked and dynamically unoptimized path selection. SDN will be used to leverage dynamic routing to avoid these two issues. In this paper, we present an application-aware network routing mechanism specifically for enhancing MPI applications with the help of an adaptive routing algorithm.
Abstract: Control-data plane intelligence trade-off in SDN
With the decoupling of network control and data planes, the upcoming Software Defined Networking (SDN) paradigm advocates better network control and manageability. It introduces logical centralized control, network programmability and abstraction of underlying infrastructure from network services and applications. With global visibility of network state and central control that eases real time monitoring, policy alterations etc., it certainly enhances network security inherently. However, the separation of planes opens up new challenges like denial of service (DoS) attack, saturation attack, man-in-the middle attack and so on. Many of the issues of controller availability, controller-switch communication delay and scalability can be solved separately by distributed controllers, out-of-band communication links and parallelization respectively. Control-data plane intelligence trade-off has the potential to solve all of these. It increases controller availability, reduces latency for traffic engineering & decision making, and improves controller scalability. Moreover, control-data plane intelligence trade-off enables the control-data plane communication to be more secure. This will tremendously offload the processing load on the controller. We present how to realize control-data plane intelligence tradeoff extending OpenFlow.
The new paradigm of Software Defined Networking (SDN) although has great potential to address the complex problems presented by enterprise networks, it has its own deployment and scalability issues. Further, a full SDN deployment has its own business and economic challenges. A smooth transition from legacy networks to SDN (disruption free, accommodating budget constraints, with progressive improvement in network management) requires a hybrid networking model as an inevitable intermediate step; that allows heterogeneous paradigms to function together while the full transition is realized in phases. Therefore, the need of the hour is to develop an incremental deployment strategy that caters to the needs of the organization. We present here a classbased hybrid SDN model for Multi Protocol Label Switching (MPLS) networks. We discuss the model, design, components, their interactions, advantages and drawbacks. We also present an implementation and evaluation of a prototype. In legacy networks, MPLS architecture closely resembles SDN paradigm in terms of separation of control and data planes, flow-abstraction etc. Moreover, ISPs have preferred MPLS over the years due to benefits of virtual private networks and traffic engineering. The central idea is to partition traffic using forwarding equivalence classes at the ingress router, the rules of which can be updated via a centralized controller using OpenFlow. Therefore, we aim to use the standard MPLS data-plane together with a controlplane based on OpenFlow to come up with a systematic incremental deployment methodology as well as a hybrid operation model
Abstract: Meticulous Measurement of Control Packets in SDN
The data packet statistics sent by OpenFlow compliant switches cumulatively includes statistics about control traffic which is used for network control and management. This reduces the accuracy of calculation of QoS metrics and thus hampers network monitoring. We present here a novel algorithm to accurately measure the fraction of control packets in SDN within 3% error rate.
Abstract: A Browser-based Distributed Framework for Content Sharing and Student Collaboration
The utilization of the networks in education system has become increasingly widespread in recent years. WebRTC has been one of the hottest topics recently when it comes to Web technologies for distributed systems as it enables peer-to-peer (P2P) connectivity between machines with higher reliability and better scalability without the overhead of resource management.
In this paper, we propose a browser based, asynchronous framework of a P2P network using distributed, lookup protocol (Chord), NodeJS and RTCDataChannel; which is scalable and lightweight. The design combines the advantages of P2P networks for better and sophisticated education delivery. The framework will facilitate students to share course content and discuss with fellow students without requiring any centralized infrastructure support.
Abstract: Addressing Challenges in Browser Based P2P Content Sharing Framework Using WebRTC
Abstract: Comparative Study of Preprocessing and Classification Methods in Character Recognition of Natural Scene Images
This paper presents an approach to character recognition in natural scene images. Recognizing such text is a challenging problem in the field of Computer Vision, more than the recognition of scanned documents due to several reasons. We propose a classification technique for classifying characters based on a pipeline of image processing operations and ensemble machine learning techniques. This pipeline tackles problems where Optical Character Recognition (OCR) fails. We present a framework that comprises a sequence of operations such as resizing, grey scaling, thresholding, morphological opening and median filtering on the images to handle background clutter, noise, multi-sized and multi-oriented characters and variance in illumination. We used image pixels and HOG (Histogram of Oriented Gradients) as features to train three different models based on Nearest-Neighbour, Random Forest and Extra Tree classifiers. When the input images were pre-processed, HOG features were extracted and fed into extra tree classifier, and the model classified the characters with maximum accuracy, among the other models that we tested. The proposed steps have been experimentally proven to yield better accuracy than the present state-of-the-art classification techniques on the Chars74k dataset. In addition, the paper includes a comparative study elaborating on various image processing operations, feature extraction methods and classification techniques.
Honors and Awards
Merit Scholarship cum. 40% Fee Wavier, BITS Pilani
Offered only to 5% of the higher degree students
KVPY Scholarship, DST, Govt. of India
Awarded to top 125 students from the country for research excellence
National Award for Science Exhibit, CBSE
CBSE National Level Science Exhibition
Ear Biometrics, A Convolutional Neural Network Approach
Ear localization with a HOG+SVM framework and ear recognition using a CNN approach with Adagrad Optimization, 92.3% in USTB III dataset
Springleaf Marketing Response, Kaggle.com
Deployed XGBoost to predict which customers will respond to a direct mail, placed in top 16% at Kaggle.com among 2500 international participants
LLVM IR Superoptimizer using GreenThumb Advanced Compilation Techniques
Lung Cancer Detection, Deep Learning
Used ResNets for feature extraction from CT scans
Prayag Sangeet Samiti, Allahabad
Sangeet Prabhakar (BA) in Tabla percussion
Featured on TV Show: Jharkhand Ke Sitare as National Level Percussionist at Naxatra News, popular Hindi news channel in the Jharkhand state
National Level Championship in All India Youth Festival
Awarded by D. A. V. College Management Committee, represented 100 schools
Best Letter, in Jharkhand state, in 35th UPU Letter Writing Competition
organized by Universal Postal Union, the United Nations