5 citations · 5 across the 6 of their papers we have counts for
7 papers
Upstream flow geometries can be uniquely learnt from single-point turbulence signatures
Mukesh Karunanethy, Raghunathan Rengaswamy, Mahesh V Panchagnula
We test the hypothesis that the microscopic temporal structure of near-field turbulence downstream of a sudden contraction contains geometry-identifiable information pertaining to…
User authentication system based on human exhaled breath physics
Mukesh Karunanethy, Rahul Tripathi, Mahesh V Panchagnula +1
This work, in a pioneering approach, attempts to build a biometric system that works purely based on the fluid mechanics governing exhaled breath. We test the hypothesis that the s…
Designing biological circuits: from principles to applications
Debomita Chakraborty, Raghunathan Rengaswamy, Karthik Raman
Genetic circuit design is a well-studied problem in synthetic biology. Ever since the first genetic circuits -- the repressilator and the toggle switch -- were designed and impleme…
CDiNN -Convex Difference Neural Networks
Parameswaran Sankaranarayanan, Raghunathan Rengaswamy
Neural networks with ReLU activation function have been shown to be universal function approximators and learn function mapping as non-smooth functions. Recently, there is consider…
Proof for frequency response analysis using chirp signals
Resmi Suresh, Raghunathan Rengaswamy
Hundreds of applications utilize frequency response characterization of a system. Identification of frequency response requires long experimentation time, use of transformation tec…
Incorporating prior knowledge about structural constraints in model identification
Deepak Maurya, Sivadurgaprasad Chinta, Abhishek Sivaram +1
Model identification is a crucial problem in chemical industries. In recent years, there has been increasing interest in learning data-driven models utilizing partial knowledge abo…