The rise of cloud computing has paved the way for the emergence of big data. Together the two concepts are helping businesses and governments to focus their resources on the core functions. Cloud computing brings big data within the reach of enterprises, big and small. They can now work with unstructured data at a huge scale. The competitive edge of the future will lie in extracting the business value from a sea of data made possible by the cloud. As the cloud and the data it holds turn critical with multiple ramifications, it requires a cautious approach to handling the cloud computing and big data.
- To provide common infrastructure, research environment and technical guidance for students and academicians.
- To work with the Industry in terms of current technological problems and challenges and come up with solutions which can make an impact quickly in the technological directions.
- To be a major catalyst for the building of Open Source communities in the country.
PES University ensures the best in faculty work in well equipped laboratories. Each domain is guided by a domain head with sterling academic credentials and a passion for research and development activities. The domain head leads a research team comprising of members drawn from the faculty who work closely with the students. The key technologies are selected taking into account availability of expertise and potential industry support. The students get a chance to try their hands on the latest software tools.
Research enriches all aspects of teaching and learning in the curriculum. The list of current projects demonstrates the deep domain knowledge of the faculty and competence of the students. Premier organizations have relied on PES University’s talent for active assistance. The guidance provided by the experienced faculty and the well equipped laboratories have ensured successful completion of projects that meet the expectations of the funding organization.
The CCBD at PES University has successfully initiated projects independently and in collaboration with other research institutes. At present the funding organizations for this domain are government organizations and industry. The vibrant academic environment and a tradition of active participation in technical events have resulted in publications in premier conference proceedings and leading journals.
- Filariasis treatment analysis- Institute of Applied Dermatology –
- Project: ELogic – optimization of BlastX
- Janagraaha – Analytics of citizenship participation in smart cities
- IBM – Cloud Security
- DataXu – Software Troubleshooting Using Machine Learning
- AMD – Big Data Workloads
- Hewlett Packard – Early identification of escalations
- Hewlett Packard – Log consolidation and cloud install of MongoDB/MariaDB
- 6 undergraduate students worked with Prof Ramesh Jain in UCI during summer of 2016 on a collaborative project and spent the summer in UCI
- 6 undergraduate students worked on collaborative projects with SUNY Binghamton on collaborative projects and spent the summer there. (Photos attached)
- Please see attached document for more details on invited talks
- of students working on various projects presently (Undergrads: 75, Post grads: 12, Research Associates: 2)
- Papers and Publications:
- Sitaram, Dinkar, H. L. Phalachandra, Anush Vishwanath, Pramod Ramesh, Meghana Prashanth, Akshay G. Joshi, Anoop R. Desai, R. Shwetha, and A. Yashaswini. “Security Infrastructure for Hybrid Clouds and Cloud Federation.” To be published in International Journal of Internet Technology and Secured Transactions.
- Sitaram, Dinkar and K. V. Subramaniam, “Complex Event Processing in Big Data Systems”, invited book chapter.
- Dhar, Shivam, Pooja U. Tata, Sachit M. Nayak, Subramaniam Kalambur, Dinkar Sitaram, and Atanu Dasgupta. “Identification of escalations during product maintenance.” In Advances in Computing, Communications and Informatics (ICACCI), 2016 International Conference on, pp. 2329-2334. IEEE, 2016.
- Agarwal, Aditya, Syed Munawwar Quadri, Savitha Murthy, and Dinkar Sitaram. “Minimally supervised sound event detection using a neural network.” In Advances in Computing, Communications and Informatics (ICACCI), 2016 International Conference on, pp. 2495-2500. IEEE, 2016
- Suresh, Susheel, Tarun Sharma, and Dinkar Sitaram. “Towards quantifying the amount of uncollected garbage through image analysis.” In Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing, p. 73. ACM, 2016.
- Aarti Jivarajani, Apoorva, Dhanya Raghu, HL Phalachandra and Dinkar Sitaram, “Workload Characterization and Green Scheduling on Heterogeneous Clusters”, 22nd Annual International Conference on Advanced Computing and Communications, ADCOM-2016, Bangalore
- Yasaswi Kishore, Venkat Datta NH, K V Subramaniam and Dinkar Sitaram, “QoS aware Resource Management for Apache Cassandra”, 2nd annual IEEE International Workshop on Foundations in Big Data Computing (HiPC BigDF’16) in conjunction with 23rd IEEE International Conference on High Performance Computing (HiPC 2016), December 2016, Hyderabad