Ravi Ramachandran

View Scopus Profile

Research activity per year

If you made any changes in Pure these will be visible here soon.

Education/Academic qualification

Bachelor of Science, Bachelor, Concordia University

Master of Science, Master, McGill University

Doctor of Philosophy, doctorate, McGill University

Fingerprint

Dive into the research topics where Ravi Ramachandran is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

1 Finished

Collaborative Research: TUES: Vertical Integration of Concepts and Laboratory Experiences in Biometrics across the Four Year Electrical and Computer Engineering Curriculum
Ramachandran, R.
National Science Foundation
10/1/11 → 9/30/15
Rowan University
Project: Other project

52 Conference article
46 Article
43 Conference contribution
9 Paper
More

Robust Explainability: A tutorial on gradient-based attribution methods for deep neural networks
Nielsen, I. E., Dera, D., Rasool, G., Ramachandran, R. P. & Bouaynaya, N. C., Jul 1 2022, In: IEEE Signal Processing Magazine. 39, 4, p. 73-84 12 p.
Rowan University
Research output: Contribution to journal › Article › peer-review
The Case against Sentiment Analysis for Natural Text
Siddiqui, S., Rasool, G. & Ramachandran, R. P., Jul 18 2021, IJCNN 2021 - International Joint Conference on Neural Networks, Proceedings. Institute of Electrical and Electronics Engineers Inc., (Proceedings of the International Joint Conference on Neural Networks; vol. 2021-July).
Rowan University
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Artificial intelligence for helicopter safety: Head-pose estimation in the cockpit
Feuerstein, E., Rasool, G., Bouaynaya, N., Ramachandran, R. & Johnson, C., 2020.
Rowan University
Research output: Contribution to conference › Paper › peer-review
Towards an explainable mortality prediction model
Epifano, J. R., Ramachandran, R. P., Patel, S. & Rasool, G., Sep 2020, Proceedings of the 2020 IEEE 30th International Workshop on Machine Learning for Signal Processing, MLSP 2020. IEEE Computer Society, 9231833. (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; vol. 2020-September).
Rowan University
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Using Deep Speech Recognition to Evaluate Speech Enhancement Methods
Siddiqui, S., Rasool, G., Ramachandran, R. P. & Bouaynaya, N. C., Jul 2020, 2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 9206817. (Proceedings of the International Joint Conference on Neural Networks).
Rowan University
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Ravi Ramachandran

Personal profile

Education/Academic qualification

Fingerprint

Network

Dive into details

Collaborative Research: TUES: Vertical Integration of Concepts and Laboratory Experiences in Biometrics across the Four Year Electrical and Computer Engineering Curriculum

Robust Explainability: A tutorial on gradient-based attribution methods for deep neural networks

The Case against Sentiment Analysis for Natural Text

Artificial intelligence for helicopter safety: Head-pose estimation in the cockpit

Towards an explainable mortality prediction model

Using Deep Speech Recognition to Evaluate Speech Enhancement Methods

Ravi Ramachandran

Personal profile

Education/Academic qualification

Fingerprint

Network

Projects

Collaborative Research: TUES: Vertical Integration of Concepts and Laboratory Experiences in Biometrics across the Four Year Electrical and Computer Engineering Curriculum

Research output

Robust Explainability: A tutorial on gradient-based attribution methods for deep neural networks

The Case against Sentiment Analysis for Natural Text

Artificial intelligence for helicopter safety: Head-pose estimation in the cockpit

Towards an explainable mortality prediction model

Using Deep Speech Recognition to Evaluate Speech Enhancement Methods