August 3, 2022
We built a tool, EpiPolicy, to help policy-makers better plan interventions to combat epidemics [13]. It was an eye-opening experience, where through collaborations and interviews with teams of epidemiologists, public health officials, and economists, we understood some of the complexities of decision-making on a momentous scale. Decisions and policies made by these teams can seriously […]
Read moreJune 10, 2022
In 2009, we wrote an article highlighting some database challenges in a co-space environment [1]. In such an environment, the physical space and the digital space co-exist in a “universe” and applications can manipulate the data flow within and across the two spaces. 13 years have since passed and progress on co-space research has been […]
Read moreMay 10, 2022
Financially, poor data quality costs organizations some ludicrous amounts of money. Worse, poor data quality is a strong inhibitor to the success of data science: No analytical method can create value from poor quality data. As a consequence, data science projects invest a majority of their resources on cleansing data. However, cleansing resists automation as […]
Read moreApril 17, 2022
Data as a major component of a deep learning solution is often undervalued in the ML projects, which results in a lower-than-expected accuracy, requiring hours and hours of model tuning. According to Andrew Ng, 99% of the recent publications are model-centric with only 1% being data-centric. He argues that there should be a balance between […]
Read moreMarch 24, 2022
INTRODUCTION Over the last half-century, the design and implementation of declarative query processing techniques in relational database systems has been a foundational topic for both the academic and industrial database research communities. Despite this sustained study, the unfortunate reality is that the resulting solutions have largely remained a “black art”. This is due to the […]
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