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
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