Research Insights

While we are a commercial organization focused on delivering impactful Applied AI solutions for our clients, we are equally invested in research with several paper publications ranging from Record Linkage Algorithms to Geospatial Events in UFO database.

Our team has published scientific and research papers on several contemporary topics in the field of Advanced Analytics, Artificial Intelligence and Machine Learning. Our team of Scientific Advisers include:

  • Harish Krishnamurthy Kashyap, MS, Electrical Engineering, Northeastern University, Boston, MA

  • Srikanth Ramaswamy, PhD, Silico Neurosciences, EPFL, Lausanne, Vaud

  • Kiran V Byadarhaly, PhD, University of Cincinnati, Ohio

  • Abhinandan S Prasad, PhD, Computer Science, The University of Gottingen

Scientific Papers

1. ”Negative Binomial Classifier for Record Linkage”, In progress of submission to ICML 2021

2. ”Bayesian Networks using Python”, Book to be published by Apress in 2021 - In Progress

3. Harish Krishnamurthy, Anna Lafontant, Ren Yi, A Time-Series Cluster Space Search Scheme for Localization of Geospatial Events in the UFO database., Best Presentation Award, International Conference on Machine Learning Applications (ICMLA), Copenhagen, June 2017. ICMLA , Copenhagen, 2017.

4. “From ProtoTyping to Production, Building an Efficient Pipeline“, Artificial Intelligence Summit, StampedeCon, St. Louis, MO, USA, 2017.

5. Probabilistic Graphical Models (PGMs) for Fraud Detection and Risk Analysis, Open Data Science Conference 2017, Bengaluru, India

6. Probabilistic Graphical Models, HMMs using PGMPY, ODSC 2017, Bengaluru, India

7. Graduate Course in Machine Learning, State University of New York (SUNY), Buffalo,

8. Classification of Power System Faults using Probabilistic Neural Networks and Wavelet Transforms, IEEE circuits & systems, ISCAS 2003,

9. Hybrid Neural Networks for Age Identification of Ancient Kannada Scripts, IEEE Circuits & Systems, ISCAS 2003,

10. Least Square Variational Bayesian Autoencoder with Regularization (In review- Journal of Machine Learning Research) 

11. “Probabilistic Machine Learning”, Book to be Published by Packt in 2021 - In Progress.

12. RAERA: A Robust Auctioning Approach for Edge Resource Allocation, IEEE

13. Reconstruction and Simulation of Neocortical Micro-circuitry

14. Rich cell-type-specific network topology in neocortical micro-circuitry

15. Data‐driven integration of hippocampal CA1 synaptic physiology in silico

16. Regularized covariance matrix estimation with high dimensional data for supervised anomaly detection problems

17. A spiking neural model for the spatial coding of cognitive response sequences

18. A hierarchical model of synergistic motor control

19. Learning Complex Population-Coded Sequences

20. Effect of second trimester and third trimester weight gain on immediate outcomes in neonates born to mothers with gestational diabetes: a retrospective observational study from India

21. Methods, systems, and computer readable media for supporting multi-homed connections

22. Supervised Negative Binomial Classifier for Probabilistic Record Linkage

23. A Mechanism Design Approach to Resource Procurement in Cloud Computing

24. RAERA: A Robust Auctioning Approach for Edge Resource Allocation

25. On the Security of Software-Defined Networks