October 26, 2022
Given a large number of users’ preferences (numerical or ordinal scores, ranked order) over a large number of objects, returning top-k results entails selecting a small list/set containing exactly k objects that are most “appropriate “. In this article, I will investigate two alternatives for selecting a top-k list/set that consumes such preference based inputs. […]
Read moreSeptember 17, 2022
The sheer volume, variety, and velocity of data in this modern era have enabled significant advancements in many research areas. However, the advancements in the research community thanks to Big Data do not necessarily translate to the benefit of society; of ordinary people living ordinary lives. There is indeed a gap between breakthroughs in the […]
Read moreAugust 25, 2022
In this post, we motivate the need for efficient and effective solutions for data series similarity search, and we briefly present the work that has been done in this direction by the data series community. We also discuss the relationship to high-dimensional (high-d) vectors and deep neural network embeddings, point to the relevant efforts in […]
Read moreAugust 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 […]
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