Rahul Simha
Professor of Computer Science



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I have just one research interest: ideas.

Especially, ideas that help solve problems and help understand the world around us. But also ideas that are fun, inspiring, foster collaboration, and lead to looking at things in a new way.

Because interesting ideas are everywhere, I tend to work in a number of different "areas" or "problems". These are some current areas of focus:

  • Educational technology. As part of the Learning Technologies Research group, my students and I are interested in effective ways to enable learning through smartphones. Currently, we are working on apps that enhance literacy instruction and math education for adult learners.

  • Robotics: human-in-the-loop. Many problems that formerly bedeviled robots are now "almost solved", including motion, using location awareness, and machine vision. But many basic problems remain, such as reliably recognizing everyday objects and how to use them. So, for the near future, it appears that humans need to teach robots how to work with everyday objects. The goal of this project is to use a simple interface for humans to show robots how to work with objects: how to grasp them, manipulate them, operate them.

  • Thermal sensing. Current energy consumption that goes into heating and cooling (HVAC) buildings represents 30-50% of the energy usage in residential and commercial buildings, which itself is about 40% of total energy consumption. At the same time, surveys of indoor quality show that people are often dissatisfied with indoor temperature regulation. The goal of this project is to use combination sensors (visual and thermal) to accurately detect when an individual is feeling discomfort (too cold, too hot) based on the thermal signature of various parts of the skin and clothing.

  • Complex systems: Biocomplexity. Consider the complex network of interactions in the average living cell. What is known today is that some biomolecular ``circuits'' -- such as sensors for particular external signals -- are relatively simple, whereas others show astonishing complexity -- such as the collection of molecules that govern the sequence of events in the birth-to-death cycle of a cell. A central goal in biology today is to understand such circuits or networks. A Boolean network is a popular model for such circuits and has resulted in a significant literature. Our work focuses on questions that go to the heart of why biological systems are complex. We focus on the space of networks that result in a given behavior (the biological phenomenon of interest), and ask: what kinds of networks produce the behavior? what is the minimal network needed? what components are involved and why?

  • Systems security. The broad area of systems security tries to address the question: how do we build computing infrastructure that is less vulnerable to attacks from viruses, hackers and the like? Because a basic computer is complex, the design of computing systems involves a number of sub-specialties from software engineering at one end, to detailed hardware design at the other. Within this span, I have focused on languages, compilers, and architecture by asking: what can do with languages, compilers and hardware to make a system more secure? In recent work, we have developed ideas for how architecture can support software security (through hardware monitoring), encrypted execution (in which programs run fully encrypted but can nonetheless be attacked), and Trojan circuits (in which an untrusted manufacturer can insert circuits into a chip). I am also working with students on related problems in language design, runtime systems, and taming software complexity.

  • Autonomous and cyberphysical systems. These two big words are intended to reflect how once-specialized areas such as robotics and vision are now broadly influencing the design of languages and systems. I am interested in new language and systems primitives, especially with humans-in-the-loop, for autonomous and cyberphysical systems.

  • STEM education. In a general sense, I am interested in "better ways to teach", especially in Science, Technology, Engineering and Math (STEM) disciplines. Not just my own teaching, but also curricula and new programs and interdisciplinary curricula that can help train the next generation of scientists and engineers. In recent projects, I have worked with physicists and biologists in integrating computational approaches into science education.

Besides the above, I am continually adding new areas or problems-to-solve, often based on student interests. For you, the student, I have one message: stop by and we'll find something interesting and valuable that you can work on.

In an earlier life, I worked on problems in networks (starting with my PhD), stochastic modeling and parallel computing. I might come back to these some day, who knows. It all depends on where the interesting ideas are.