Computer Science

Master’s Research Project Topics

The following research project topics are available to Master’s students. If you are interested in any of these projects, please contact the professors listed below.


Data-driven approaches in networking

Faculty Member

Xin Liu

Description

We use machine learning and control/optimization techniques, based on network measurement and user behavior data, to address network resource allocation and management challenges. One project is on prediction-assisted dynamic bandwidth allocation mechanisms in wireline networks. Another project is on analyzing real network performance data for better cellular network configurations. The third project is to conduct experiments on a remote wireless testbed, Orbit.

Requirements

  • Basic understanding of networks, machine learning, and optimization techniques
  • Strong programming skills

Deep learning techniques for populating databases

Faculty Member

Bahram Ravani

Description

A GSR position is available in Professor Ravani’s group for MS or PhD students in Computer Science for the above titled research project.

Requirements

  • Continuing or admitted student in the graduate program in Computer Science
  • Working knowledge of Python, Javascript, and Django

Development of computational methods for discovery of conserved regions in known neurodevelopmental disorder genes

Faculty Member

Fereydoun Hormozdiari

Description

We have made significant discoveries in finding genes contributing to neurodevelopmental disorders. However, each gene can be considered as several domains with various intolerance levels for mutations. We want to develop a novel computational method to discover domains that are intolerant to missense mutations, utilizing the available large-scale sequencing projects. Furthermore, we will try to study these domains in the context genetic networks to find potential domain-domain interactions that are crucial for neurodevelopment.

Requirements

  • Knowledge of statistics and probability
  • Strong programming skills (C/C++, Java, or Python)
  • Understanding of combinatorial algorithms

Experiment with anonymization and the Bro intrusion detection system

Faculty Member

Matt Bishop

Description

We have access to 2 data sets:

  1. UC Davis data; this is a set of full packet captures.
  2. LBNL data; this is pre-anonymized (using prefix-preserving anonymization) and packet bodies are stripped.

The goal of this project is to determine the effect of anonymization on signature-based intrusion detection analysis. First, run Bro on both sets of data to establish a baseline of alerts from the data. Then, anonymize the packets in each data set using black marker anonymization, and rerun the analyses. Record the differences between the results and the baseline (false positives and false negatives). Repeat this with prefix-preserving anonymization. Then, explain any differences between the analyses of the anonymized data and the raw data sets.

Requirements

  • Continuing or admitted student in the graduate program in Computer Science

In situ simulation infrastructure

Faculty Member

Jason Lowe-Power

Description

Not only is hardware technology changing rapidly, but the workloads that execute on this hardware are also evolving. This set of projects will extend the open-source architecture simulator gem5 to simulate systems in their native environment with close to zero overhead so computer system designers in industry and academia can evaluate new hardware on real applications. gem5 is used by many different universities and in industry including at ARM, Google, and AMD. If you want to work on a vibrant open-source project with real impact on research and industry, I’d be happy to work with you! These projects will give you experience working on a large distributed-development C++ open-source application.

See my research page for more information.

Requirements

  • Experience with C++ and Python
  • Architecture knowledge will be helpful, but not required

Simplified geometric models of subcellular components of a cell

Faculty Member

Nelson Max

Description

We hope to construct simplified geometric models of subcellular components of a cell, like the nucleus or mitochondria. The input will be high resolution Focused Ion Beam Scanning Electron Microscope (FIB-SEM) images of plane sections through the cell, which are assembled into a 3D voxelized volume. These voxel volumes have already been segmented to identify the voxels belonging to the subcellular objects of interest. The output will be a simplified geometric approximation to the voxel volumes in these objects, bounded by pieces of planar, spherical, or conical surfaces. Such a simplified description can serve as a compressed summary of the volume, taking much less data to specify, and can also be used to compute things like the surface area of the object.

Initially, the project will involve applying existing published algorithms to this data to compute the approximations, which will be used to create images for grant proposals, since I have no funding to support a research student on this project. If we get a grant, there may be money to support a student to carry the research further.

Requirements

  • Continuing or admitted student in the graduate program in Computer Science
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