Sanjukta Bhanja of College of Engineering, University of South Florida

Quadratic Unconstrained Binary Optimizing (QUBO) is a combinatorial optimization problem that has become essential to machine learning, economics, and healthcare applications. Therefore, QUBO solvers have seen a significant boost in their demand. These problems are computationally expensive, complex to parallelize, and require MIMD approaches.  Ising machines such as D-wave have proposed a quantum solution for solving these NP-hard optimization problems. Several data-dominant application spaces, namely protein folding problems in Computational Biology, genome sequencing for COVID-19 and other pandemic diseases, and traffic patterns in social media, have benefitted from this problem mapping and one-shot solution. Although they can solve QUBO problems, the exceptionally high operating cost due to the cryo-cooling for quantum Ising machines might not justify the accuracy they achieve. In this talk, we will explore a magnetic QUBO-solver, which could solve the problems more quickly and cost-effectively at room temperature.  Because the Hamiltonian of a system of coupled nanomagnets is quadratic, a wide class of quadratic energy minimization can be solved much more quickly by the relaxation of a grid of nanomagnets than by a conventional Boolean processor. Our research shows that magnet-based solutions are independent of problem size as the ground state of the magnets yield the optimization solution in parallel. This co-processor consists of a programmable grid of magnetic cells that can generate any magnetic layout in a 2D plane and will be integrated with peripheral control similar to STT-MRAM memory. This talk will focus on state-variable design, problem mapping and reconfigurability.

Biography:

Sanjukta Bhanja received a bachelor’s degree in Electrical Engineering from Jadavpur University, Calcutta, and a Master’s degree from the Indian Institute of Science, Bangalore. She earned her Ph.D. in Computer Science and Engineering from the University of South Florida, Tampa. She is currently a professor at the Department of Electrical Engineering at the University of South Florida. Currently, Bhanja serves as Executive Associate Dean for the College of Engineering since FY’2021.

Sanjukta Bhanja’s research spans VLSI, nano-electronics, and applied physics, with external sponsorship from the National Science Foundation and NASA. She has graduated 12 Ph.D. graduates who’ve excelled in high-tech industries and advises four doctoral students. Her creative works are published in top-tier peer-reviewed journals and conferences, including high-impact journals such as Nature Nanotechnology. She has been an Associate Editor of the IEEE Transactions on VLSI Systems and ACM Journal on Emerging Technologies in Computing Systems. Besides serving on various IEEE and ACM conferences’ Technical Program Committees (TPC), she has assumed leadership roles in Conference organization and steering committees. She organized a National Science Foundation-sponsored conference on ”Field-coupled Nano-computing” that created a roadmap and evaluated research progress in Field-coupled computing. Her accolades include the NSF CAREER Award, “Outstanding Faculty Research Achievement Award” from USF, Outstanding Undergraduate Teaching recognition, the F.E.F William Jones Outstanding Mentor Award, and certification as an Executive Leadership Fellow in the ELATES at Drexel® program for 2020-2021

Email:

Address:Tampa, Florida, United States, 33620