Insoon Yang

The simultaneous reduction of power supply and threshold voltages for low-power design without suffering performance losses will eventually reach the limit of diminishing returns as static leakage power dissipation becomes a significant portion of the total power consumption. This is especially acute in systems that are idling most of the time. In order to meet the opposing requirements of high performance at reduced power supply voltage and low-static leakage power during idle periods, a dynami

Standard stochastic control methods assume that the probability distribution of uncertain variables is available. Unfortunately, in practice, obtaining accurate distribution information is a challenging task. To resolve this issue, in this article we investigate the problem of designing a control policy that is robust against errors in the empirical distribution obtained from data. This problem can be formulated as a two-player zero-sum dynamic game problem, where the action space of the adversa

We consider the problem of constructing control policies that are robust against distribution errors in the model parameters of Markov decision processes. The Wasserstein metric is used to model the ambiguity set of admissible distributions. We prove the existence and optimality of Markov policies and develop convex optimization-based tools to compute and analyze the policies. Our methods, which are based on the Kantorovich convex relaxation and duality principle, have the following advantages.

Simultaneous reduction of supply and threshold voltages for low power design without suffering performance losses will eventually reach the limit of diminishing returns as static power dissipation becomes a significant portion of the total power equation. In order to meet the opposing requirements of high performance and low power, a dynamic threshold voltage control scheme is needed. A novel SOI technology was developed whereby a back-gate was used to control the threshold voltage of the front-

We characterize the statistical properties of a large number of agents on two major online auction sites. The measurements indicate that the total number of bids placed in a single category and the number of distinct auctions frequented by a given agent follow power-law distributions, implying that a few agents are responsible for a significant fraction of the total bidding activity on the online market. We find that these agents exert an unproportional influence on the final price of the auctio

Online auctions have expanded rapidly over the last decade and have become a fascinating new type of business or commercial transaction in this digital era. Here we introduce a master equation for the bidding process that takes place in online auctions. We find that the number of distinct bidders who bid k times up to the tth bidding progresses, called the k-frequent bidder, seems to scale as n(k)(t) approximately tk(-2.4). The successfully transmitted bidding rate by the k-frequent bidder is li

A new indirect load control approach is developed for managing financial risks in electricity markets. These risks are generated by price volatility and demand uncertainty regarding distributed renewable generation as negative load. The proposed method is based on risk-limiting dynamic contracts between a load-serving entity and its customers. The contract framework allows the load-serving entity to incentivize the customers to control their loads in a way that is beneficial to itself, while ens

This paper proposes a method to design an optimal dynamic contract between a principal and an agent, who has the authority to control both the principal's revenue and an engineered system. The key characteristic of our problem setting is that the principal has very limited information: the principal has no capability to monitor the agent's control or the state of the engineered system. The agent has perfect observations. With this asymmetry of information, we show that the principal can induce t

SOIAS (SOI with Active Substrate) is a novel, SOI-based technology which enables the integration in the third dimension of gates and interconnects by utilizing buried under-layers. The fabrication of SOIAS substrates takes full advantage of the existing technologies of Chemical Mechanical Polishing (CMP) and wafer bonding. The active buried under-layers can be pre-patterned isolated gates or interconnects using high temperature refractory metals such as tungsten, or blanket insulating or semi-in

This paper considers an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable suboptimality bounds to provide computationally tractable solution methods even when the dimension of the system and the number of the binary variables are large. The proposed method employs a linear approximation of the objective function such that the approximate problem is defined over the feasible

We present a numerical method for computing backward reachable sets in differential games. A backward reachable set for time t is captured by the t sublevel set of the lower value function of the game, which coincides with the viscosity solution of a stationary Hamilton-Jacobi-Isaacs (HJI) equation. We solve the stationary HJI equation in a computationally efficient way that does not involve any numerical integration over time, which would otherwise be required for time-dependent HJI equations.

The integration of wind energy into the power grid is challenging because of its variability, which causes high ramp events that may threaten the reliability and efficiency of power systems. In this paper, we propose a novel distributionally robust solution to wind power ramp management using energy storage. The proposed storage operation strategy minimizes the expected ramp penalty under the worst-case wind power ramp distribution in the Wasserstein ambiguity set, a statistical ball centered at