Research

Research interests

My research interests evolve over time. Some of the current core themes are:

  • Emergence - phase changes in computational complexity, gravity from quantum entanglement
  • Algorithmic Complexity - universality, expressibility, fractals, tensor networks
  • Artificial General Intelligence - recursive self-improvement, artificial life, explainable neural networks
  • Quantum Computation - quantum Hamiltonian complexity, quantum optimization, quantum learning theory
  • Soft-computing - hardness of approximate, neuro-evolution

Current Projects

  • Near-term quantum optimization and learning algorithms for genomics (Ph.D. dissertation)
  • Evolutionary quines on gene expressions for recursive self-improvement systems
  • Spiking neural network based associative memory neuro-evolution

… Interested in a research collaboration (or master’s thesis) within QCA lab on related topics? Contact me over LinkedIn or email.

Past Projects

  • Quantum algorithms for pattern-matching in genomic sequences (M.Sc. thesis)
  • Quantum Innovation Environment (QuInE), a PyQT based IDE for quantum programming
  • Brain-inspired robotic mapping and navigation using time-series of hexagonal grid and place cells
  • System design of warehouse automation using multi-agent collaborative box-pushing strategies
  • Human brain simulation in GPU with Inferior Olive model in OpenCL and CUDA
  • GATK based human genome sequencing for distributed Spark platform in Scala
  • Fuzzing and concolic execution on RERS-2016 problems using AFL and KLEE
  • Optimizing a SoC using ρ-VEX VLIW processors
  • Enhancing the Plasma processor IP core
  • Accelerating object tracking in OMAP3530 application processor
  • Solar energy forecasting using ORCA system
  • Earthquake occurrence analysis and aftershock prediction using MATLAB and Tableau
  • Elevation mapping using stereo vision enabled heterogeneous multi-agent network (B.Tech. thesis)
  • Computer vision based centralized multi-agent system on MATLAB and Arduino
  • Self-configuring classical logic gate circuits using genetic programming in Java
  • Multi-vehicle path planning in dynamically changing environments using genetic optimised TSP

Curriculum vitae

Associations