“Srinivasan is one of the most talented engineers that I have had the pleasure and honour to work with. It's one in a million chance to find such a gem in the industry. He has the ability to quickly grasp any topic and make significant contributions in a very short period of time. In the 2 years that I spent with Srinivasan at Samsung, I have seen him undertake end-to-end research, development and productization of ultrasound imaging algorithms. I had a lot of fun working with Srinivasan. I wish him the very best for his future endeavours!”
About
Machine Learning Scientist building computer vision and representation learning…
Experience
Education
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Department of Computer Science, University of Toronto
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Courses:
Deep Reinforcement Learning
Machine Learning for Health
Computer Graphics
Human-Computer Interaction
Blockchain Technologies -
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Activities and Societies: Opensoft - Software Development Contest, Eastern Vocals, Association of Biotechnologists, Kshitij, Public Relations Cell, Yahoo Hack U, Microsoft Appathon, Inter Hall Ad-design, Inter Hall Data Analytics
Minor in Chemical Engineering
Micro-specialization in Biomedical devices & Instrumentation -
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Activities and Societies: Carnatic Music, Quizzing, Painting, Fine Arts, Tamil and English Dramatics
Licenses & Certifications
Publications
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Automated measurement of fetal right-myocardial performance index from pulsed wave Doppler spectrum
SPIE Medical Imaging - Computer-Aided Diagnosis 2019
Congenital heart disease is the leading cause of birth defect related deaths. The modified myocardial performance index of the right ventricle (R-MPI) is a sensitive and early clinical indicator of fetal cardiac health. Objective repeatable measurement of R-MPI is an important deciding factor for the clinical adaptation of the R-MPI. In this work, we describe a novel method for automatic computation of R-MPI from the Pulsed Wave Doppler (PWD) images. Our method involves a Fourier series based…
Congenital heart disease is the leading cause of birth defect related deaths. The modified myocardial performance index of the right ventricle (R-MPI) is a sensitive and early clinical indicator of fetal cardiac health. Objective repeatable measurement of R-MPI is an important deciding factor for the clinical adaptation of the R-MPI. In this work, we describe a novel method for automatic computation of R-MPI from the Pulsed Wave Doppler (PWD) images. Our method involves a Fourier series based cardiac cycle detection followed by an adaptive windowed energy based valve click localization and weighted gradient based refinement. Using this method, we have been able to measure R-MPI reliably with a mean difference of 0.0075 ± 0.034 from 170 expert annotations on 68 fetal PWD images with an Intra-Class Correlation (ICC) of 0.9380. Furthermore, we have introduced novel methods for normalization and synchronization of PWD images acquired at two different time intervals for the assessment of iso-volume time intervals and an accurate measurement of R-MPI.
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Automated detection and segmentation of follicles in 3D ultrasound for assisted reproduction
SPIE Medical Imaging - Computer-Aided Diagnosis 2018
Follicle quantification refers to the computation of the number and size of follicles in 3D ultrasound volumes of the ovary. This is one of the key factors in determining hormonal dosage during female infertility treatments. In this paper, we propose an automated algorithm to detect and segment follicles in 3D ultrasound volumes of the ovary for quantification. In a first of its kind attempt, we employ noise-robust phase symmetry feature maps as likelihood function to perform mean-shift based…
Follicle quantification refers to the computation of the number and size of follicles in 3D ultrasound volumes of the ovary. This is one of the key factors in determining hormonal dosage during female infertility treatments. In this paper, we propose an automated algorithm to detect and segment follicles in 3D ultrasound volumes of the ovary for quantification. In a first of its kind attempt, we employ noise-robust phase symmetry feature maps as likelihood function to perform mean-shift based follicle center detection. Max-flow algorithm is used for segmentation and gray weighted distance transform is employed for post-processing the results. We have obtained state-of-the-art results with a true positive detection rate of >90% on 26 3D volumes with 323 follicles.
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A Disorder-Induced Domino-Like Destabilization Mechanism Governs the Folding and Functional Dynamics of the Repeat Protein IκBα
PLOS Computational Biology
The stability of the repeat protein IκBα, a transcriptional inhibitor in mammalian cells, is critical in the functioning of the NF-κB signaling module implicated in an array of cellular processes, including cell growth, disease, immunity and apoptosis. Structurally, IκBα is complex, with both ordered and disordered regions, thus posing a challenge to the available computational protocols to model its conformational behavior. Here, we introduce a simple procedure to model disorder in systems…
The stability of the repeat protein IκBα, a transcriptional inhibitor in mammalian cells, is critical in the functioning of the NF-κB signaling module implicated in an array of cellular processes, including cell growth, disease, immunity and apoptosis. Structurally, IκBα is complex, with both ordered and disordered regions, thus posing a challenge to the available computational protocols to model its conformational behavior. Here, we introduce a simple procedure to model disorder in systems that undergo binding-induced folding that involves modulation of the contact map guided by equilibrium experimental observables in combination with an Ising-like Wako-Saitô-Muñoz-Eaton model. This one-step procedure alone is able to reproduce a variety of experimental observables, including ensemble thermodynamics (scanning calorimetry, pre-transitions, m-values) and kinetics (roll-over in chevron plot, intermediates and their identity), and is consistent with hydrogen-deuterium exchange measurements. We further capture the intricate distance-dynamics between the domains as measured by single-molecule FRET by combining the model predictions with simple polymer physics arguments. Our results reveal a unique mechanism at work in IκBα folding, wherein disorder in one domain initiates a domino-like effect partially destabilizing neighboring domains, thus highlighting the effect of symmetry-breaking at the level of primary sequences. The offshoot is a multi-state and a dynamic conformational landscape that is populated by increasingly partially folded ensembles upon destabilization. Our results provide, in a straightforward fashion, a rationale to the promiscuous binding and short intracellular half-life of IκBα evolutionarily engineered into it through repeats with variable stabilities and expand the functional repertoire of disordered regions in proteins.
Projects
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Automated Merging of Torn Paper Fragments
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Designed a software for automated stitching of torn image fragments. It used a contour matching algorithm to detect potential matches. It also resolved disambiguities in the candidate matches during the stitching process.
Other creatorsSee project -
Research Citation Analyser
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Developed a software which would show and analyze citations to papers published by a particular researcher or journal. This system connects to Google Scholar and Microsoft Academic Search as and when needed during its operation. The results are parsed and various metrics pertaining to the author are analysed.
Other creatorsSee project
Honors & Awards
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Samsung Citizen Award
Samsung Research India, Bangalore
For excellence in People and Process category.
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Nipun - Team Level Best Demo
Samsung Research India, Bangalore
Certificate of excellence as one of the contributors towards the "Team Level Best Demo" titled "Follicle Quantification for Assisted Reproduction" during NIPUN held in November 2016
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Spot Award
Samsung Research India, Bangalore
For outstanding contribution towards Achievement of significant milestone (>90% detection rate) towards productization of the next generation 5DFollicle Application
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Best Project Award
Indian Institute of Technology, Kharagpur
Proficiency Award for having done the Best Project Work among graduating students of the Department (2015-2016)
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Institute Silver Medal
Indian Institute of Technology, Kharagpur
Best Student in Order of Merit among the graduating students of the Department (Department Rank 1)
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MITACS Globalink Research Intern
MITACS
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University of Alberta Research Experience Scholarship
Univeristy of Alberta
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Kishore Vaigyanik Protsahan Yojana (KVPY) Scholar 2011
Indian Institute of Science
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Merit Certificate in Science
Central Board of Secondary Education
Awarded for being in top (0.1%) in Class 10 Board examination
Languages
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English
Native or bilingual proficiency
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Tamil
Native or bilingual proficiency
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Hindi
Limited working proficiency
Organizations
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International Society for Computational Biology
Student Member
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Recommendations received
5 people have recommended Srinivasan
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