I am a Research Assistant and a PhD Candidate with Prof. Wolfgang Maass at the Institute for Theoretical Computer Science at TU Graz. My main research interest is to try to understand how the human brain works. I do this by developing mathematical and computational models for learning and memory with a strong emphasis on biologically plausibility.
I used to be a SDE at Amazon.com in the DynamoDB team for a couple of years before I started my PhD.
Before that, I was a computer science Masters student at UT Austin. I was working with Prof. Risto Miikkulainen on using neuro-evolution and task-decomposition to learn complex tasks. I have also worked with Prof. Peter Stone on agents that learn from human demonstrations and rewards.
Detailed resume available on request.
- Bellec* G, Salaj* D, Subramoney* A, Legenstein RA, Maass W. Long short-term memory and Learning-to-learn in networks of spiking neurons. CoRR [Internet]. 2018;abs/1803.09574. (url) (pdf) (bibtex)
- Kaiser J, Stal R, Subramoney A, Roennau A, Dillmann R. Scaling up liquid state machines to predict over address events from dynamic vision sensors. Bioinspiration & Biomimetics [Internet]. June 2017; (url) (bibtex)
- Petrovici MA, Schmitt S, Klähn J, Stöckel D, Schroeder A, Bellec G, et al. Pattern representation and recognition with accelerated analog neuromorphic systems. In: arXiv:170306043 [cs, q-bio, stat] [Internet]. 2017. (url) (bibtex)
- Subramoney A. Evaluating Modular Neuroevolution in Robotic Keepaway Soccer [Internet] [Master's thesis]. [Austin, TX]: Department of Computer Science, The University of Texas at Austin; 2012. p. 54 pages. (url) (pdf) (bibtex)
- Jain A, Subramoney A, Miikkulainen R. Task decomposition with neuroevolution in extended predator-prey domain. In: Proceedings of Thirteenth International Conference on the Synthesis and Simulation of Living Systems [Internet]. East Lansing, MI, USA; 2012. (url) (pdf) (bibtex)