BITS Pilani

  • Page last updated on Monday, March 08, 2021


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Research Areas of the Faculty

Distributed Systems and Information Security

This research group addresses issues in supporting emerging network infrastructures, with particular focus on wireless mobile ad-hoc networks, sensor networks, peer-to-peer overlays, grid and cloud computing. Research is centered around the design and analysis of networking protocols and algorithms to support efficient and reliable communication. The groups research focuses on application of graph algorithms to improve the lookup efficiency in P2P overlays, assessing the impact of P2P traffic on IDS/IPS designs, energy-aware routing algorithms for wireless sensor networks, adaptive load distribution algorithms, distributed mutual exclusion over MANETs. The group also works in grid computing security and access control modeling, wherein the focus is about modeling authorization frameworks for single domain and multi-domain grid environments. Ranking based cross domain role mapping algorithms are used in multi-domain grid systems. Cloud computing research of this group proposes solutions for access control, trust based generic security framework, and cloud forensics. In cloud forensics, the researchers have proposed ideas for regenerating events using system snapshots for forensic analysis.

Faculty: Prof. Chittaranjan Hota, Dr. G Geethakumari, Gokul Kannan

Data Management

In a sensor network, sensor nodes monitor and collect physical data without any human intervention for weeks or months. A node should consume less power for the above said operations for keeping the battery life longer. Sensor deployments must be energy efficient, and hence energy efficient data management strategies are necessary. This group is working on issues like efficient data storage, caching, and query techniques for sensory data. This group also works on data dissemination, and management in Information systems.

Faculty: Dr Gururaj R 

Software Engineering


This research group focuses on enhancing software quality and productivity by applying data mining algorithms to various software engineering tasks. As the IT industry is getting matured there is so much of data representing experience and knowledge of systems that is available with the providers and this group addresses several challenges posed during the mining of software engineering data. Secondly, the group also focuses on the implementation challenges of cloud computing in particular SaaS (Software as a Service) model. The main challenges in SaaS are design and development, revenue models, sales and compensation, customer service, support and maintenance and the group is working on generic products that take care of licensing and billing of all services offered by a SaaS provider.


Faculty: Dr. N.L.Bhanu Murthy 


Artificial Intelligence

This research group focuses on three main areas of research: Artificial Intelligence, and data mining. This group uses Data Mining and AI techniques to solve and create innovative and efficient solutions to complex problems like Smart playlist generation, Web Index Advertising Engine and Design and implementation of focused crawler for searching collaborators. In the playlist generation we attempt to suggest similar songs based on the seed songs selected by the user. Hybrid filtering techniques are used for finding similarity between the seed songs and the songs in the training set. In Web Index Advertising research, the group examines behavioural/contextual data of online consumers (who surf web pages) and also works on publishing more relevant advertisements efficiently improving user satisfaction over just in time, place and need parameters.

Faculty: Dr Aruna M, S.S Samant

Computer Graphics

The primary area of research of this group is in computer graphics, computational geometry and its applications in solving different scientific and engineering problems.  One of the focus areas of work is mesh generation which spans variety of problem domains starting from CAD Model meshing to fluid flow simulation. In particular Delaunay based methods for mesh generation are deeply studied, along with their scalability issues and the quality of results obtained in actual simulation process. Problems such as mesh modification and optimization are also researched. Along with mesh generation, geometric reconstruction of boundary representation and their applicability for solving different scientific problem such as 3D surface reconstruction from different kind of volume data is also researched.

Faculty: Dr Tathagata Ray


Sponsored Projects (Ongoing)
. MUT- DROCO: Multipath Networking Test-bed for Drone Communications. Grant Amount: INR 16.6 Lacs. Funding Agency: Start-Up Research Grant by Science and Research Board (SERB), Department of Science and Technology (DST), Govt. of India. Duration: 2020-2022. Type: Research Grant. (Chief Investigator: Dr Paresh Saxena).
. Network Coding for Multipath Transport. Grant Amount: INR 5.5 Lacs. Funding Agency: AnsuR Tech., Oslo, Norway. Duration: 2019-2020. Type: Industrial Consultancy. (Chief Investigator: Dr Paresh Saxena).
. Interpretation of Tuberculin Reaction Using Medical Photography and Computer Aided Diagnosis, Grant Amount: Rs. 9.94 lakhs, DST-SERB; Start up Research Grant, (Formerly known as Early Career Research Award), 2019 – 2021, (Chief Investigator: Dr Jabez Christopher).
Sponsored Projects (Completed)
. "Lightweight Code Self-verification for Internet of Things (IoT) Devices", under Indo-Dutch Joint Research Program for ICT funded by DeitY-NWO-Progress-Irdeto with a project outlay of 380, 000 Euros (INR 2.6 Crores) from July, 2015 to July, 2019. (Investigators: Prof. Chittaranjan Hota and Researchers from Vrije University, Amsterdam).
. "Design and Development of Digital Forensic Tools for Cloud IaaS", Grant amount: Rs 55 lakhs, funded by Ministry of Communication & Information Technology (MeitY), Govt. of India, New Delhi, 2014 - 2017. (Chief Investigator: Prof G Geethakumari, Co-Investigator: Dr. Digambar Povar).
. "Automated Detection of Security and Privacy Threats in Peer-to-Peer Networks", 61.95 Lakhs INR, Funded by Department of Information Technology, Ministry of Communication & Information Technology, Govt. of India, New Delhi in 2012 (PI: C.R. Hota, Co-PI: Abhishek Thakur).
. “Efficient Peer-to-Peer Overlay Infrastructure for Secure Computing over the Internet", Funded by University Grants Commission (UGC), Govt. of India, New Delhi: (2011-2014), 10.38 Lakhs INR (PI: C.R. Hota).
. “Network Coding with Deterministic Coefficients”, Grant Amount: INR 5.6 Lacs. Funding Agency: AnsuR Tech., Oslo, Norway. Duration: 2018-2019. Type: Industrial Consultancy. (Chief Investigator: Dr Paresh Saxena).

Research Scholars

Name: Sai Kiranmai G
Supervisor Name: Dr Aruna M
Co-Supervisor Name: Dr. N.L. Bhanu Murthy
Email ID :,
Research Topic : Named Entity Recognition and Classification for Telugu Language
Research Abstract : Named Entity Recognition (NER) aims to classify each word of a document into predefined target Named Entity (NE) classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as Information Retrieval, Machine Translation, Information Extraction, Question Answering systems and others. For English a lot of work has already done in field of NER, where capitalization is a major clue for rules, whereas Indian Languages do not have such feature. This makes the task difficult for Indian languages especially Telugu Language as it is highly inflectional and agglutinative in nature. The NER system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the different NE's classes, such as Person name, Location name, Organization name, monetary expressions, dates, numerical expressions etc.
Name: Neha Singh
Supervisor Name: Dr. Tathagata Ray
Co Supervisor name : 
Email ID:;  
Research Topic: Mesh Generation
Research Abstract: Mesh Generation is an interesting problem in computational geometry which originates from the field of civil and mechanical engineering. It is the discretization of a given domain into simpler elements such as triangle or quadrilateral in two dimensions and tetrahedron and hexes in three dimensions. In this research, we will generate quality meshes from two-dimensional and three-dimensional point sets. We will use Delaunay Triangulational for generating meshes.
Name: Deevi Radha Rani    
Supervisor Name: Dr G Geethakumari
Co Supervisor name: 
Email ID:
Research Topic: Design of a Cloud Forensic VM Level Framework for Infrastructure-as-a-Service Model
Research Abstract: Cloud computing is radically changing the way information technology services are created, delivered, accessed and managed.The current operational landscape of incident handling and forensic methods have changed with the evolution of cloud computing. To date, there has been very little research done on the current state of the tools, processes, and methodologies to obtain legally defensible digital evidence in the cloud. The main objectives of our research are i) To investigate the forensic challenges in the cloud computing environment ii) To design a forensic framework to facilitate virtual machine level investigation for the cloud Infrastructure-as-a-Service model
Name: Sanket Mishra
Supervisor Name: Prof. Chittaranjan Hota 
Co-Supervisor Name: NA 
Email ID:
Research Topic:  Resilient and Cogniitive IoT Framework for Smart Buildings
Research Abstract: Internet of Things has seen a tremendous uprising in the recent era. This boom engulfs the sectors of home automation,energy,transport,buildings, etc. to name a few. It brings forth the possibility to handle them with intelligence and devise algorithms so as to substantiate their autonomous working. This research deals in devising new algorithms to predict actuations in real world from sensor data and unlocking new horizons in event processing. Also the need arises to secure the IoT scenario by safety mechanisms for which algorithms are created to insulate them from any type of adversities that might hamper their smooth predictions and functionalities. 
Name:   B S A S Rajita
Supervisor Name: Prof. Anand Narasimhamurthy
Co-Supervisor Name: -
Email ID:
Research Topic: Analysis of Temporally Evolving Social Network Patterns
Research Abstract: In this work, we propose to investigate different techniques for identifying temporal patterns and events in social networks that evolve over time. We present a framework for detecting the evolution of dynamic social communities, along with tracking the events and transitions related to communities. These events can be considered as building blocks for pattern detection in networks with evolving communities. These detected events and transitions could then be used for predicting the future patterns of these social networks.

Name: Avinash kumar 
Supervisor Name: Dr. Aruna Malapati 
Co-Supervisor Name: Dr.N.L.Bhanu Murthy
Email ID:  ; 
Research Topic: Opinion Mining Challenges of Social Media Content & Sentiment Polarity Detection.
Research Abstract: Experiences and viewpoint expressed by others have always been important part of decision making process. In current era very large pool of public opinion is available on social media about certain event. These web contents are unstructured data set and a rich source for not only commercial exploitation but also for psychological & sociopolitical research. Our proposed research aims to find an efficient method to extract important features/ aspect about a particular event from social media message and then do the features based sentiment analysis about the same. The proposed method can be adapted to work for text from other online media as well.  
Name:  Rashmi Sahay
Supervisor Name:  Dr. G Geethakumari
Co-Supervisor Name:  Dr. Barsha Mitra
Email ID:
Research Topic:  Securing the Internet of Things Environment against RPL (Routing Protocol for Low power and Lossy Network) Attacks

Research Abstract: Internet of Things (IoT) is network of uniquely identified devices that have the ability to talk to each other without requiring human intervention. IoT devices are constrained which makes it difficult to implement complex security solutions on them. The communication is wireless, which also makes it susceptible to attacks. Also, the devices are mostly placed in locations which cannot be frequently accessed. These characteristics of IoT make it vulnerable to breaches in privacy and security. An effective way to prevent attacks is to have secured bootstrapping. Secure bootstrapping in IoT involves design of light weight cryptographic algorithms. RPL is the Routing protocol used in LLNs in IoT, which is vulnerable to several security attacks. Hence, it is important for an IoT network to have a holistic system to address the RPL attacks. The research topic aims to develop such a system, which can identify the RPL attacks, take action to counter it and also design secure bootstrapping algorithms for authentication of new nodes joining the IoT network.
Supervisor Name:  Dr. Suvadip Batabyal
Co-Supervisor Name: 
Email ID:

Research Topic:   Estimators for Efficient Buffer Management in Mobile Opportunistic Networks.


Abstract of the Research:

Most of the congestion control mechanisms that have been proposed, have a common goal of increasing the message delivery ratio and decreasing the message delivery delay. To achieve this goal, several congestion mechanisms employ dropping the message or try to transfer the message to other nodes. Existing research shows that the several congestion control mechanisms are dependent on the underlying routing protocol. As a result, the congestion control mechanisms are not interoperable with variety of routing protocols. Many existing congestion control mechanisms relies completely on the network information to make the congestion control decisions. Several congestion control algorithms depend on the simulation platforms to evaluate protocols and algorithms, which is a necessary step, but cannot replace the real world experiments. In our work, we aim to use controlled message replication policies to increase the congestion control strategy range to various routing protocols. We also intend to use local information available with the node along with global network information to make a congestion control decision. We will also setup a DTN testbed for our research to verify the results produced by the simulator.


Soumya Prakash Otta

Supervisor: Dr Subhrakanta Panda

Co-Supervisor: Prof Chittaranjan Hota

Email ID:

Research Topic: Security as a Service: Secured Authentication in a Hybrid Cloud Environment.

Abstract of the Research: 

As the first and last line of defence in almost all cases, authentication is a crucial aspect of any cloud. With the desired authentication mechanisms in place, any unauthorised access to the system can be prevented. Through the research the effort would be to design and implement Security as a service by ensuring and maintaining confidentiality, integrity and   availability as well as strict policy based authentication to access control in a hybrid cloud environment.


Anirudh Kasturi

Supervisor Name: Prof Chittaranjan Hota

Co-Supervisor Name: Prof. N.L. Bhanu Murthy

Email ID :

Research Topic:  Distributed and Resilient Cognitive Framework for Edge-centric IOT Applications


Abstract of the Research

Major drawback with the current frameworks revolving around IoT architectures is the increase in actuation time as the analysis of data happens on a central server. So there is a strong need to come up with truly scalable architectures and improved intelligent algorithms that can run on the edge devices. The focus of the research will primarily be on the distributed ML and process discovery resource-aware ML algorithms. 

Tummalapalli Sahithi

Supervisor: Dr Lov Kumar

Co-Supervisor: Prof N L Bhanu Murthy



Research Topic: Detection of web service anti-patterns using machine learning algorithms

Abstract of the Research: The objective of our research is to identify different types of anti-patterns by investigating source code, WSDL file and text based metrics. In particular, our motivation is to investigate the application of machine learning based techniques for building predictive models from source code metrics as features for the task of detecting web-services anti-patterns. 


Name:   Saibharath S

External Supervisor: Dr Sudeepta Mishra

On campus Supervisor: Prof. Chittaranjan Hota

Email ID:

Research Topic: QoS Based Traffic Management through NFV in Next Gen Networks


Research Abstract: 

Design traffic categorization and classification framework to label and segregate LTE and 5G traffic based on QoS attributes; Propose a novel traffic scheduling, resource allocation, load balancing, and offloading mechanism at RAN slices to meet necessary QoS; Joint admission control policies and forecasting through feedback in the Network slices.  

Priyanka Rushikesh Chaudhary

Supervisor: Dr. Rajib Ranjan Maiti

Co-Supervisor : ---

Email ID :

Research Topic: Detection and mitigation of cyber attacks on IoT using machine learning.


Abstract of the Research:

The Internet of Things (IoT) is the next wave of advancement that is revolutionizing our society,

cities and homes. People use these smart devices creating smart environments unaware whether each IoT device is functioning properly safe from cyber-attacks. The communication networks are jeopardized by growing of intrusion attempts, various attacks, worms etc. Appropriate countermeasures initiates an important property for network privacy and security in terms of ongoing attack detection. Machine learning is one of the technique which empowers system with the capability of using data to learn from previous experiences and makes decisions. The research topic aims to identify and reduce security threats over iot devices with the help of machine learning technique to improve the performance of system. 

 Mandan Naresh

Supervisor: Dr. Paresh Saxena

Co-Supervisor: Dr Manik Gupta

Email ID:

Research Topic: NANCY: Neural Adaptive Network Coding methodology for video distribution through wireless networks.



Name:  S.Vishwanath Reddy
Supervisor Name:  Dr. B Manjanna
Co-Supervisor Name: -
Email ID:

Research Topic: Computational Geometry and Approximation Algorithms. 


Name: Abhinandan Banik

Supervisor Name: Dr. Suvadip Batabyal  


Research Domain: Network Security

Pattiwar Shravan Kumar

Supervisor Name: Dr. Paresh Saxena

Co-Supervisor Name:-

Email Id:

Research Topic: Multipath Networking Protocols 

Name: Mithun Kumar S R

Supervisor: Dr Lov Kumar

Co-Supervisor: -

Email ID: 

Research Topic: Perception algorithms in sparsely labelled datasets 

Deepa Kumari

Supervisor Name: Dr. Subhrakanta Panda

Co-Supervisor Name: Dr. Jabez J Christopher

Email id:

Research Topic: A Blockchain- based patient centric MHR system for prediction of future medical complications.

Research Abstract: The project proposal aims to develop a patient-centric blockchain-based framework to store data and keep a trail of the users’ action to avoid any fabrication and/or misuse of sensitive and private medical information, and to predict the onset of any medical complications due to certain treatment. The application of Social Network Analysis methodologies on the relational medical data (relationship between certain diseases and their corresponding drugs) will enable to discover the hidden patterns and will also help to build an individualized patient profile to predict the likelihood of any medical complications in near future. 

Nida Fatima

Supervisor Name: Dr. Paresh Saxena


Research Topic: Efficient routing and resource allocation techniques for future integrated hybrid satellite-terrestrial 5G/B5G networks.


Ramisetty Kavya                                                                                        

Supervisor Name: Dr Jabez Christopher

Co-Supervisor Name: Dr Subhrakanta Panda

Email id:

Research Topic: Decision Support Systems for Health Informatics 

Chillara Anil Kumar

Supervisor Name: Dr.suvadip Btabyal

Co-Supervisor Name:--

Email id:

Research topic : performance enhancements in Multi core architecture .

Research Abstract:

Considering the volume of data and the complexities involved in computations, majority of the bottlenecks in the context of performance/processing in multicore architectures is due to the data movement in the NoC. Research topic aims at considering suitable hardware/software architecture to minimize the data movement in NoC to increase the overall performance of the system.