Groups

Computational Biology Group (CBG)

Director(s): Nurit Haspel

The computational biology group focuses on the development of novel algorithms and the application of state-of-the-art existing methodologies to solve various key problems in molecular biology, nanobiology and biochemistry. We combine biophysical and biochemical principles with algorithmic techniques, aiming to better understand protein structure and dynamics. Current research topics include modeling conformational changes in proteins, design of novel nano-structures, modeling protein-protein interactions and understanding protein folding and docking

Computing Hardware & Large-Data Lab (CHiLL)

Director: Tarikul Islam Papon

We design hardware-aware and learned data management solutions for modern data systems. Our work focuses on LSM-based NoSQL key-value stores (memory allocation, workload-aware filters and caching, learned compaction), buffer pool management in relational databases, tiered storage architecture, and data management on modern storage and memory hardware, including SSDs, ZNS SSDs, and CXL-based disaggregated memory.

Distributed Software Systems Group (DSSG)

Director(s): Jun Suzuki

DSSG carries out fundamental and applied research in the area of distributed software systems. Its long-term research goal is to make distributed software systems more autonomous, scalable, adaptive, survivable and easier to develop. DSSG’s research efforts address the research issues that cross the boundaries among distributed computing, software engineering and artificial intelligence.

Knowledge Discovery Laboratory (KDLab)

Director(s): Wei Ding

Knowledge Discovery Laboratory aims at the development of data analysis and data management techniques with applications to challenging problems in geosciences, astronomy, environmental sciences. Areas of research include mining discriminating patterns, discovering interesting regions of arbitrary shape and granularity, designing new classification algorithms, and developing scalable algorithms to cope with large real-world datasets.

Machine Psychology (MPsych)

Director(s): Daniel Haehn

Machine learning methods are inspired by neuroscientific discoveries-but current methods are fragile, do not generalize well, and require massive amounts of data. We use visual computing methods to better understand the similarities and differences between human and machine intelligence.

Mobile Security and Privacy Research Lab (MobSP)

Director(s): Xiaohui Liang

Our research interests include security and privacy for mobile devices, smartphones, and IoT devices. We are currently working on security and privacy issues related to health care, smartphones, and personal voice assistance.

Network Computing Laboratory (NCLab)

Director(s): Duc Tran

NCLab’s primary mission is to perform cutting-edge research in emerging areas of networks and data management, particularly in support of smart social, sensing, storage, and search applications. NCLab also offers research opportunities to students outside the classroom and engages in multidisciplinary R&D collaborations with other academic units at UMass as well as other institutions in and beyond the Boston area.

Services Computing Laboratory (SCLab)

Director(s): Kenneth Fletcher

Services Computing Laboratory (SCLab) focuses on developing methods and algorithms services selection and recommendation. Specifically, SCLab focuses on capturing and including users’ evolving preferences in machine/deep learning algorithms to improve accuracy of services selection and recommendation. Areas of research include exploring user temporal and contextual preferences from sequential actions, detecting fake likers in social media network, and improving recommendation accuracy with Knowledge Graphs.

Software Verification Laboratory (SVL)

Director(s): Tiago Cogumbreiro

The aim of the Software Verification Laboratory is improve the programmer’s productivity, by developing tools and techniques that localize bugs, and enforce the correctness of systems. Our main focus is on verifying scientific codes, in the domain of High Performance Computing. We employ the fields of programming languages, formal methods, concurrency theory, and statistical machine learning to improve the correctness of software.

Virtual Characters Lab (VCLab)

Director(s): Funda Durupinar

Virtual characters have become ubiquitous mainly through movies and games, but also in the assistive domain as virtual tutors, healthcare providers, interviewers and so on. VCLab aims to develop believable, autonomous virtual characters that exhibit a rich repertoire of behaviors driven by external and internal stimuli. We focus on inherently multidisciplinary problems, involving expertise on computer graphics, animation, artificial intelligence, psychology, and movement analysis.