Natural and engineered systems that consist of populations of isolated or interacting dynamical components exhibit levels of complexity that are beyond human comprehension. These complex systems often require an appropriate excitation, an optimal hierarchical organization, or a periodic dynamical structure, such as synchrony, to function as desired or operate optimally. In many applications, the dynamics of such ensemble systems can … Read More

We describe recent results on foundational aspects of modeling, architecture and performance of networked cyber-physical systems. These include: multi-layer multigraph models, constrained coalitional games, analysis of trust and mistrust in collaboration, dynamics of signed graphs, distributed consensus with adversaries, new concepts of value of information and event-driven inference and decision making, non-commutative probability models. We conclude with directions for future … Read More

Genome sequencing is one of the biggest breakthroughs in science in the past two decades. Modern sequencing methods use linking data at multiple scales to reconstruct pertinent information about the genome. Many such reconstruction problems can be formulated as maximum likelihood sequence decoding from noisy linking data. We discuss two in this talk: haplotype phasing, the problem of sequencing genomic … Read More

Robotics and AI are experiencing radical growth, fueled by innovations in data-driven learning paradigms coupled with novel device design, in applications such as healthcare, manufacturing and service robotics. And in our quest for general purpose autonomy, we need abstractions and algorithms for efficient generalization. Data-driven methods such as reinforcement learning circumvent hand-tuned feature engineering, albeit lack guarantees and often incur a massive computational expense: training these models frequently takes … Read More

Characterizing the rate-distortion region of Gaussian multiterminal source coding is a longstanding open problem in network information theory. In this talk, I will show how to obtain new conclusive results for this problem using nonlinear analysis and convex relaxation techniques. A byproduct of this line of research is an efficient algorithm for determining the optimal distributed Karhunen–Loève transform in the … Read More

In HP’s Emerging Compute Lab, research is being conducted at the intersection of signal processing, auditory perception and machine learning to create fundamentally new experiences for differentiation in HP devices including VR HMD. In this talk we will present various techniques and algorithms, incorporating knowledge of binaural perception, machine learning, and signal processing, to enhance low-frequency perception, spatial rendering, and … Read More

The recent proliferation of acoustic devices, ranging from voice assistants to wearable health monitors, is leading to a sensing ecosystem around us — referred to as the Internet of Acoustic Things or IoAT. My research focuses on developing hardware-software building blocks that enable new capabilities for this emerging future. In this talk, I will sample some of my projects. For … Read More

Today’s cyber-physical systems are the building blocks of smart and citizen-centric applications that will revolutionize the way people interact with the urban environment. Smart systems, cities, and communities will emerge, in which advanced levels of autonomy hold the promise of greater efficiency, reliability and sustainability in areas of national interest and social need, such as health, energy, and transportation. In this new realm of … Read More