Building 32 from MIT CSAIL Alliances

MIT CSAIL Professor Manolis Kellis discusses how the symbiotic relationship between computer science and biology helps us to better understand the complex programming language that is our DNA. Through DNA, we can find the molecular basis of the pathophysiology of a disease and take a more holistic approach to disease treatment, and one day may even predict disease. He explains the impact of human genome and epigenome research on the pharmaceutical industry in developing medicine that is both precise and personalized, dramatically transforming the therapeutic landscape.

Manolis Kellis

Principal Investigator, MIT CSAIL, Professor of Computer Science, Computational Biology Group leader

https://cap.csail.mit.edu/podcasts/understanding-science-disease-through-human-genome-research

Download the podcast transcript:

https://cap.csail.mit.edu/sites/default/files/research-pdfs/Podcast_ManolisKellis_04_29_2020.mp3_.pdf

Aleksander Madry, Associate Professor at CSAIL, tackles key algorithmic challenges in today’s computing as part of his work in the Theory of Computation Group at CSAIL. His work is described as re-thinking machine learning from the perspective of security and robustness. Madry discusses the evolution of the human and machine interaction and provides insight on adoption of M/L systems over the next few years.

Are we even sure what the internet is today? One of the original architects of the internet, David Clark, Senior Research Scientist at CSAIL, talks about shaping the future of the internet, the potential challenges and what it could become.

Julie Shah discusses the challenges and successes of designing and employing intelligent design teammates that aim to enhance human productivity in descion-making and physical tasks through using reverse engineering methods and computational models. She shares how research is exposing robots to building skills that allow them to infer and anticipate their human counterpart's next move and motives within a given situation and the flexibility to adapt and adjust outside of predetermined plans.

Andrew Lo, Charles E. and Susan T. Harris Professor at MIT Sloan School of Management, and Director of MIT Laboratory for Financial Engineering, shares insight into the collaborative research efforts of MIT CSAIL and MIT Sloan School of Management within the three distinct areas of crytopgraphy, machine learning and AI, as well as discusses the progress of blockchain technology and cryptocurrency. He also offers a glimpse into the future of banking and finance and reveals the emerging technology of secured multi-party computation.

MIT CSAIL's Howard Shrobe, Director of the Cybersecurity@CSAIL initiative, discusses what led him to become involved in the industry of Cybersecurity, his experience with DARPA, and creating the cybersecurity programs of CRASH and MRC. Additionally, he shares insights as to the biggest challenges in cybersecurity today and how these challenges effect the development of the Internet of Things.

MIT CSAIL professor Srini Devadas describes computer architecture, computer security and their intersection. He gives further insight into the conflict between ease of programming and performance and the communication between these threads through parallel software, such as message passing or shared memory abstraction (e.g. Google Docs).

While the promise of the Internet of Things (IoT) brings many new business prospects, it also presents significant challenges ranging from technology architectural choices to security concerns. The concept of Internet of Things (IoT), which has roots at MIT, has begun to make an impact in industries ranging from industrial systems to healthcare. MIT researchers continue to conduct ground-breaking research on topics ranging from RFID to cloud technologies, from sensors to the World Wide Web. Learn cutting-edge tools and applications for this new evolution in hardware, software, and data from MIT's Computer Science and Artificial Intelligence Laboratory's IoT experts: http://bit.ly/1S4sIdp

A researcher at MIT’s Computer Science and Artificial Intelligence Lab, Michael Stonebraker has founded and led nine different big-data spin-offs, including VoltDB, Tamr and Vertica - the latter of which was bought by Hewlett Packard for $340 million.

Now he’s bringing his insights to a new online course being offered this month through edX and MIT Professional Education. Co-taught by long-time business partner Andy Palmer, “Startup Success: How to Launch a Technology Company in 6 Steps” covers topics ranging from generating ideas and recruiting top talent to pitching VCs and negotiating deals - all in the span of three weeks.

The Data Science Machine is an end-to-end software system that is able to automatically develop predictive models from relational data. The Machine was created by Max Kanter and Kalyan Verramachaneni at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT.