Super Computing


The diseases most common today are often the most complex. It is unlikely that a simple solution will be easily found. Instead, it will be necessary to collect, analyze and integrate large amounts of data in order to find cures. It is not simply a matter of throwing resources at a problem, however. Computing power alone is not enough. New computational techniques must be developed to carry out large-scale computing as efficiently as possible.
Alexander D. Wissner-Gross conducts research in artificial intelligence on a massive scale. His recent research project includes a planetary scale computing model for electronic trading. 


Many large computing resources do not consist of one large computer; instead, they are composed of many small computers linked together. Although this approach allows for the construction of an easily-upgradable computing center using publicly available parts, it has some disadvantages. The connections between the computers make management more complex and potentially introduce a new bottleneck that could slow down the entire system. New networking techniques could help avoid those potential problems.

Quantum ComputingQuantum computing

Today’s computers are based on silicon transistors. Making the transistors progressively smaller has allowed more and more powerful computers to be developed. Experts anticipate that within the next 10 years we will reach the physical limits of how small transistors can be made. To continue making faster computers, a new approach will be necessary. Scientists are now exploring ways of using the quantum properties of particles to do computation. If such a computer were developed, even a small one, it could rapidly do computations that would take an ordinary computer centuries to complete.

Neuro ComputingNeuro-computing

The human brain contains billions of cells, with trillions of connections. Due to its complex nature, it is capable of extraordinary computational power. It is more powerful than the world’s fastest supercomputer- even though the latter takes up an entire building. Clearly, we have a lot to learn from the human brain. Shaped by billions of years of evolution, it is more powerful and efficient than the computers we have spent mere decades developing. The field of neuro-computing applies lessons from neuroscience to help improve computers.

David Eagleman conducts research in neurology and envisions a future where novel sensory inputs can be connected to the brain. Click here to lean more about Dr. David Eagleman’s research projects.

Ben Goertzel conducts research in artificial intelligence and uses patterns and models of how humans think and applies them to computer learning programs. Click here to lean more about Ben Goertzel’s research projects.

Ed Rosenfield has written multiple books on neurocomputing.

Bio ComputingBiocomputing

Smartphones are always getting smaller and more powerful. But is it possible that there is an even more powerful computer that is so small you need a microscope to see it? Indeed, it is, as a cell is really a computer. Although seemingly simple on the surface, every cell must constantly monitor its environment, taking in thousands of inputs, from hormonal signals, to nutrition status, to signs of infection, and integrate all that data to decide how to act. The field of biocomputing seeks to harness the naturally-ocurring data processing and computational abilities of biological organisms.

Systems ModellingSystems modeling

The human body is composed of many intricate systems, such as the nervous system, the cardiovascular system and the respiratory system. The complexity of these systems makes it difficult to determine the cause when they malfunction. Systems modeling uses mathematical and computational techniques to simulate biological systems, enabling scientists to better understand pathologies and develop treatments.

Alexander D. Wissner-Gross conducts research in artificial intelligence on a massive scale. His recent research project includes a planetary scale computing model for electronic trading. 

Tanya Petrossian does research in bioinformatics and systems biology. 

Bio InformaticsBioinformatics

The analysis of biological information is undergoing a revolution. It took decades to sequence the first human genome; now, it is possible for a single lab to produce more sequence data in a single day than was produced by every lab in the world during the first 30 years of sequencing. Despite the deluge of data, we have still not witnessed the revolutions in medicine expected from the availability of massive amounts of sequencing. This is because data is not enough: we must also analyze the data to find out its meaning. The new field of bioinformatics is focused on developing new techniques of data analysis in order to gain a better understanding of biological systems and diseases.

Tanya Petrossian does research in bioinformatics and systems biology.

Russell Hanson is currently involved with bioinformatics research. Click here to lean more about Russell Hanson’s research projects.