
Research and
Development
20
Doctoral Students
75+
PATENTS by our faculty
1000+
PUBLICATIONS by our faculty

“INSOFE enters a new era… Our faculty are exploring the foundations
of Artificial Intelligence and developing newer applications in a
variety of fields such as
IoT, Blockchain, Video Analytics, Business Intelligence, and Healthcare.”
Dr. L. Srinivasa Varadharajan
Dean - Research and Development
Research Areas
INSOFE’s 75 faculty members and 20 doctoral students are actively involved in applied research
and product development in the following areas.
Data Science
Horizontals
Verticals
Robotics
Autonomous Systems & Connected Devices
Retail / FMCG
Blockchain
Supply Chain
Quantum Machine Learning
Education
Scaling and Deploying Deep Learning Algorithms
Healthcare
AI Adoption in Business
Distributed Computing and Networking
Robotics, Autonomous Systems & Connected Devices (RASCoD)
Principal Investigators
-
Dr. Anand Narasimhamurthy
-
Prof. Ashwin Ganesan
-
Mahesh Kumar Duvvarapu
-
Nilesh Chopda
Research Objective
- Build product prototypes which help attain safety and efficiency through autonomy and seamless connectivity.
- Grow applied research capabilities through the application of Machine Learning, Deep Learning and Reinforcement Learning in Robotics.
- Deliver best-in-class educational programs that help the industry to adopt and apply robotics for solving real-world problems.
Retail/FMCG
Principal Investigators
-
Prof. Anuradha Sharma
Research Objective
- Our long-term goal is to gain competency in building an AI-driven Retail product for the Indian market. We intend to do that by developing a prototype of a contextual visual recommendation engine layered with user ratings and its aspects for niche areas like Shoes/Bags/Top Food Preferences (Chinese, Italian, Indian) using advanced AI.
- Development of a Retail/FMCG execution playbook for faster, accurate, and scalable delivery in our consulting practice.
Blockchain
Principal Investigators
-
Dr. Praphul Chandra
-
KoineArth Team
Research Objective
- Blockchain based platform for bridging data silos between organizations.
- Build an enterprise grade platform to enable secure, auditable data sharing to improve speed & OTIF performance in Supply Chains.
- Enable organizations to issue publicly verifiable, digitally traceable sustainability, origin & warranty certificates.
- Incentivize secure, consent-based data sharing by enabling data-as-an-asset in B2B & B2C value chains.
Supply Chain
Principal Investigators
-
Dr. Manoj Duse
-
Dr. Anand Narasimhamurthy
-
Prof. Ashwin Ganesan
Research Objective
- Grow applied research capabilities through the application of Machine Learning, Deep learning, Simulation, and Optimization to solve burning problems in industry related to Supply Chain.
- Deliver best-in-class educational programs to help industry ML-driven psychological health profile.
Education
Principal Investigators
-
Dr. Sridhar Pappu
-
Shilpa Kadam
-
Jayant Mulmoodi
Advising Investigators
-
Dr. L. Srinivasa Varadharajan
-
Dr. Suryaprakash Kompalli
Research Objective
- Personalized learning for online and blended learning models.
- Video-based proctoring.
- Mood identification and classification in the classroom.
Healthcare
Principal Investigators
-
Dr. L. Srinivasa Varadharajan
-
Dr. Suryaprakash Kompalli
-
Jagannadha Rao Basa
Research Objective
- Identification of people at risk for various diseases.
- Customized medical support.
- ML-driven psychological health profile.
AI Adoption in Business
Principal Investigators
-
Dr. Dakshinamurthy V Kolluru
-
Dr. Gnana K Bharathy
-
Prof. Anuradha Sharma
-
Tanzeem Ahmed
Research Objective
- Our long-term goal is to make AI adoption systematic and efficient in an enterprise. We will work at 3 layers. CXOs (decision-makers), translators (managers) and engineers. We shall develop frameworks, questionnaires, surveys and tools to make AI adoption easier.
Distributed Computing and Networking
Principal Investigators
-
Prof. Ashwin Ganesan
-
Dr. Anand Narasimhamurthy
Research Objective
- Conduct research in all areas of networking, including wireless networks, sensor networks, interconnection networks, and IoT.
- Investigate the design and performance of distributed algorithms and resource allocation and scheduling algorithms.
- Conduct research in data science, with a focus on graph algorithms in data mining and networked structures in economic and social networks.