Currently, I am focusing on theoretical and practical aspects of analog optimization. Analog optimization is a method of solving linear and quadratic optimization problems (LP and QP) using analog circuit.

Despite continued advancement of digital computers, the task of solving optimization problems in very short times (e.g. 1 MHz for MPC based control of fast systems) remains challenging. Using analog technology, solution to real-time optimization problems can be obtained in a few microseconds and ongoing work aims to reduce it to a few nanoseconds, which is lower than any current method known to us.

The proposed method expresses an optimization problem as an equivalent electric circuit whose steady state voltages are solution of the optimization problem.

Possible applications of the new methodology are fast and power-efficient analog signal processing (e.g. Kalman filter), image processing (e.g. optical flow, mathematical morphology) and advanced control (e.g. model predictive control).

See my publications for more details and description of the ongoing projects below.

## Fast and programmable analog controller implemented on printed circuit board.

The goal of this project is to build a functioning fast MPC controller using an analog QP solver. The controller is built using programmable digital potentiometers and switches, which allows reconfiguration to solve a given problem.

## Proof of concept implementation of high speed analog optimization circuit using analog VLSI.

The goal of this project, done in cooperation with prof. Elad Alon and Kristel Deems, is to build a chip that solves a QP problem with speed typical for analog VLSI - hundreds of MHz up to a few GHz.