Sriram Sankaranarayanan

Sriram Sankaranarayanan is an assistant professor of Computer Science at the University of Colorado, Boulder. His research interests include automatic techniques for reasoning about the behavior of computer and cyber-physical systems. Sriram obtained a PhD in 2005 from Stanford University where he was advised by Zohar Manna and Henny Sipma. Subsequently he worked as a research staff member at NEC research labs in Princeton, NJ. He has been on the faculty at CU Boulder since 2009. Sriram has been the recipient of awards including the President's Gold Medal from IIT Kharagpur (2000), Siebel Scholarship (2005), the CAREER award from NSF (2009) and the Dean's award for outstanding junior faculty for the College of Engineering at CU Boulder (2012).

More info: http://www.cs.colorado.edu/~srirams/

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Pre-MBA Statistics (Coursera)

Welcome to the Pre-MBA Statistics course! By the end of this course, you will be able to describe how statistics can be used to summarize, analyze, and interpret data. This course introduces you to some aspects of descriptive and inferential statistics. You will learn to distinguish between various data [...]

Dynamic Programming, Greedy Algorithms (Coursera)

Apr 1st 2024
Dynamic Programming, Greedy Algorithms (Coursera)
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This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. We will also cover some advanced topics in data [...]

Algorithms for Searching, Sorting, and Indexing (Coursera)

This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters. Algorithms for Searching, Sorting, and Indexing can be taken for academic credit as part of CU Boulder’s Master of [...]

Trees and Graphs: Basics (Coursera)

Apr 1st 2024
Trees and Graphs: Basics (Coursera)
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Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data. Trees and Graphs: Basics can be taken for academic credit as part [...]

Approximation Algorithms and Linear Programming (Coursera)

This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal solutions to problems arising from domains such as resource allocation, scheduling, task assignment, and variants of the traveling salesperson problem. [...]