I'm a Ph.D. student working with Polina Golland in the Medical Vision Group in CSAIL. My research interests are in machine learning and artificial intelligence; in particular I'm working on applications of these to problems in medical imaging. I'm currently funded by the NSF Graduate Research Fellowship.
I was an undergraduate in EECS at UC Berkeley. While I was there I worked with Stan Klein's Visual Processing Lab on signal processing in vision science, and with Dan Garcia and Brian Harvey on a curriculum development project involving parallelism in introductory computer science courses.
- Ramesh Sridharan*, Adrian Dalca*, Kaitlin Fitzpatrick, Lisa Cloonan, Allison Kanakis, Ona Wu, Karen Furie, Jonathan Rosand, Natalia Rost, and Polina Golland. "Quantification and Analysis of Large Multimodal Clinical Image Studies: Application to Stroke." In Proceedings MICCAI International Workshop on Multimodal Brain Image Analaysis (MBIA), 2013.
- Danial Lashkari, Ramesh Sridharan, Ed Vul, Po-Jang Hsieh, Nancy Kanwisher, and Polina Golland. "Search for Patterns of Functional Specificity in the Brain: A Nonparametric Hierarchical Bayesian Model for Group fMRI Data." NeuroImage, 59(2):1348-1368, 2012.
- Ramesh Sridharan. "A Generative Model for Activations in Functional MRI." Master's Thesis, MIT, 2011.
- Danial Lashkari, Ramesh Sridharan, and Polina Golland. "Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations." Accepted in Advances in Neural Information Processing Systems (NIPS), 2010.
- Danial Lashkari, Ramesh Sridharan, Ed Vul, Po-Jang Hsieh, Nancy G. Kanwisher, and Polina Golland. "Nonparametric Hierarchical Bayesian Model for Functional Brain Parcellation." In Proceedings of MMBIA: IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis, 2010.
- Matthew Johnson*, Ramesh Sridharan*, Robert H. Liao, Alexander Rasmussen, Dan Garcia and Brian K. Harvey. "Infusing Parallelism into Introductory Computer Science Curriculum using MapReduce." UC Berkeley Technical Report No. UCB/EECS-2008-34, 2008.
* Equal contribution
- I taught a short course titled 6.S085, Statistics for Research Projects in January 2012 (with my colleague Finale Doshi-Velez), January 2013, and January 2014 (with my colleague George Chen).
- In 2013, I received the Frederick C. Hennie III Teaching Award, awarded to a few graduate students in the department each year for teaching excellence.
- I was a TA for 6.s080: Introduction to Inference in Fall 2012. This was a brand-new undergraduate course on inference! Along with my fellow TAs, George Chen and Gauri Joshi, we made Khan Academy-inspired videos summarizing recitation topics. If you're at MIT, you can view my teaching ratings. I also wrote up some notes on course topics:
- I was a TA for 6.438: Algorithms for Inference in Fall 2010. If you're at MIT, you can view my teaching ratings.
- I was a TA for 6.041: Probabilistic Systems Analysis and Applied Probability in Fall 2008. If you're at MIT, you can view my teaching ratings.
- In 2008, I received the Outstanding Graduate Student Instructor Award, granted to several TAs within each department across UC Berkeley each year. The same year, I received the EECS Outstanding Graduate Student Instructor Award, granted to one or two outstanding TAs within the department each year.
- I was a TA for CS61A: Structure and Interpretation of Computer Programs, an introductory computer science class, from Summer 2006 to Spring 2008. You can see my teaching ratings.