CS@Mines Research


The Department of Computer Science has a strong emphasis on research, both within the department and collaboratively with other departments, universities, government organizations and industry partners. 

The departmental research areas include the following.

  • Applied Algorithms and Data Structures: An interdisciplinary research area that is applied to areas such as VLSI design automation, cheminformatics, computational materials, and cyber-physical systems.
  • Education: This area encompasses research on STEM recruitment and diversity, K-12 computing education, and computing/engineering education at the university level. Current projects include an on-campus computing outreach program tailored for girls across a broad age range; professional development opportunities for CS high school teachers; design of an intra-disciplinary undergraduate course focused on teamwork and industrial design practices; and the incorporation of social justice into core undergraduate engineering courses with a specific focus on control systems.
  • High Performance Computing: High performance computing in EECS at Mines focus on compiler-based code and data transformation, memory optimization for both multi-core and many-core processors, speculative parallelization, approximate computation, and GPU-based acceleration of Big Data applications (such as graph processing and machine learning algorithms).
  • Algorithmic Robotics: An interdisciplinary research area drawing from traditional computer science, engineering, and cognitive science.  Research themes include artificial intelligence, human-robot interaction, and augmented reality, focusing on integrating computer vision and perception, learning and adaptation, natural language understanding and generation, and decision making into unified robot systems.
  • Augmented Reality: An interdisciplinary research area that encompasses the fields of control systems, signal and image processing, compressive sensing, and optimization. This group undertakes fundamental research into the development, characterization and implementation of algorithms for processing and acting upon data sources, as well as research directed towards applications in energy systems, image analysis, communication systems, and robotics.
  • Machine Learning Includes research in developing mathematical foundations and algorithm design needed for computers to learn. Focus areas include fundamental research in machine learning and numerical methods, as well as developing novel algorithms for bioinformatics, data mining, computer vision, biomedical image analysis, parallel computing, natural language processing, and data privacy.
  • Networking: Research focus areas include credible network simulation, mobile sensing, sensor networks, robotic networks, pervasive computing, wireless networking, and mobile social networks. Interdisciplinary research also exists, mainly in the use of wireless sensor networks for geosystems, environmental monitoring, energy efficient homes, and robotic networks for oil refinery inspection.
  • Security: Research includes usable security and privacy in web/mobile/cloud/cyber-physical systems, vulnerability measurement and analysis, and security & privacy education.

We welcome you to learn more about our faculty members who are engaged in compelling research in the field of computer science:


Tracy Camp

"My students and I apply machine learning techniques to understand real-world systems (e.g., is the earth dam suffering from internal erosion? is the base station rogue?). We are also working to build a wireless sensor system that can collect geophysical data from the subsurface inexpensively. Lastly, I am also interested in developing communication protocols to help a group of unmanned aerial vehicles cooperate on some task."

EDITOR OF SPECIAL ISSUE: E-1. N. Aschenbruck and T. Camp, Guest Editors of Special Issue, “Scenarios for ad hoc Network Evaluation Studies (SCENES)”, Ad Hoc Networks, vol. 12, January 2014. Message from Guest Editor: pp. 1. This special issue intends to disseminate the latest research results in the SCENES research area, by providing an overview of the current state-of-the-art scenario models and methodologies for model validation and credible performance evaluation for ad hoc networks.


Qi Han

"At a high level, my research is within the realm of networking and distributed systems. More specific research areas include cyber physical systems (CPS), Internet of Things (IoT), mobile sensing, and robotic sensor networks. I design algorithms, develop techniques, and build systems to enable pervasive and mobile computing applications,  where mobile robots, stationary sensors and humans interact with each other to accomplish a certain mission.  In addition, I apply my research in interdisciplinary projects such as environmental monitoring,  energy efficient homes, oil refinery inspection, and underground mine safety.  More detailed information about my research can be found at the Pervasive Computing Systems Research Group I direct."

Recent Papers:

Collaborative Recognition of Queuing Behavior on Mobile Phones

Toward Real-time and Cooperative Mobile Visual Sensing and Sharing


William Hoff

"My research interests are computer vision and pattern recognition, including object recognition, activity recognition, human-computer interfaces, 3D reconstruction, and motion estimation.  I focus on applications in augmented reality and robotics.  I am particularly interested in integrated man-machine systems, such as a human assisting or being assisted by computer vision in performing a task."

Recent papers:

Learning Object and State Models for AR Task GuidancePDF versionText only version 

Segmentation and tracking of nonplanar templates to improve VSLAM




Dinesh Mehta

"My core research expertise is in algorithms and data structures which I have applied to interdisciplinary areas such as VLSI design automation, cheminformatics, computational materials and cyber-physical systems. I am focusing my current research to address algorithmic problems arising in big graph analytics."

 Recent papers: 





Hua Wang

"My research interests include machine learning and data mining, as well as their applications in bioinformatics, medical image computing, health informatics, cheminformatics and computer vision. I aim at developing efficient machine learning and data mining algorithms with theoretical guarantees to solve practical problems involving large scale data. I am particularly interested in formalizing and solving new problems driven by the advancements of new technologies.

Recent Papers:

Enforcing Template Representability and Temporal Consistency for Adaptive Sparse Tracking

Drosophila Gene Expression Pattern Annotations via Multi-Instance Biological Relevance Learning


Bo Wu

"My research interest lies in the broad field of compilers and programming systems, with an emphasis on program optimizations for heterogeneous computing and emerging architectures. Most of my research activities have centered around data locality enhancement for heterogeneous computing systems. My choice of this area of focus is driven by the importance of heterogeneous processors (e.g., CPU plus GPU) in meeting the needs of the large variety of modern applications."

Recent Papers: Complexity analysis and algorithm design for reorganizing data to minimize non-coalesced memory accesses on GPU

Enabling and Exploiting Flexible Task Assignment on GPU through SM-Centric Program Transformations



Dejun Yang

"My research interests are in networking, mobile sensing and computing, and Internet of things. Specifically, I apply game theory, optimization, algorithm design, and machine learning to resource allocation, security and privacy problems in these areas." 

Recent Paper: Incentive Mechanisms for Crowdsensing: Crowdsourcing with SmartphonesPDF versionText only version





Chuan Yue

"My research focuses on (1) web, mobile, cloud, and cyber-physical systems security, (2) usable security and privacy, (3) vulnerability measurement and analysis, and (4) cybersecurity education.  I also actively collaborate with researchers in other CS areas and other disciplines, as well as with industry and government partners."

Recent Papers:

Sensor-based Mobile Web Fingerprinting and Cross-site Input Inference AttacksPDF versionText only version (a position paper).

Automatic Detection of Information Leakage Vulnerabilities in Browser Extensions.PDF versionText only version



Hao Zhang

"I am a computer scientist and roboticist working on robot perception, learning and adaptation, and decision making to make robots smarter to work alongside people. Our research interest focuses on integrating the strengths of humans and robots working together in time-critical and safety-critical scenarios. The application domains include search and rescue, assistive robotics, and robot-assisted surveying."

Recent papers:

Robust Multimodal Sequence-Based Loop Closure Detection via Structured SparsityPDF versionText only version

Enforcing Template Representability and Temporal Consistency for Adaptive Sparse TrackingPDF versionText only version



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Last Updated: 10/13/2017 13:59:49