Ramya Hebbalaguppe
Senior Scientist @Tata Consultancy Services
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WORK HISTORY
Senior Scientist @Tata Consultancy Services
My interests broadly lie in reliable and compact representational learning. My doctoral study is centered around reliable and trustworthy AI. Currently, I lead efforts in resource constrained machine learning specifically, Neural network compression for resource-constrained environments such as the smartphones and head mounts. Second, I am working on reliable and trustworthy ML systems such as out-of-distribution detection and confidence calibration taming Network agnostophia and overfidence of DNNs. lastly, at the intersection of computer vision and graphics my team works in Augmented Reality where we develop, Next-generation HCI such as Hand Gestural interfaces, Spatial overlays for Augmented Reality - both internal and external overlays and Frugal motion capture systems for animation generation.
EDUCATION
Indian Institute of Science (IISc)
Intern, Broadly in VLSI
Visvesvaraya Technological University
BE, Electonics & Communication from SJCE , Mysore
Dublin City University
Master's Degree, (Research) Computer Vision and Machine learning, INSIGHT: Research Centre for Big Data Analytics
SKILLS
ABOUT RAMYA HEBBALAGUPPE
Ramya Hebbalaguppe is currently a Senior scientist at TCS Research Labs based out of IIT Delhi. Her doctoral studies focussed on reliability of deep neural networks at IIT Delhi. She earned her M. E, in Artificial Intelligence, from INSIGHT: Research Centre for Big Data Analytics, Ireland. She received the B.E. degree from SJCE, Mysore in Electronics Engineering. Prior to her post-graduate studies, she was a researcher at the School of Computer Engineering, Nanyang Technological University, Singapore working in the field of computational photography.Her primary research interests include trustable machine learning, Computer Vision, and Photography. On the ML side, she has been working on problems and resource-constrained machine learning (neural network compression), Deep Neural Network Calibration, Open set recognition and Domain adaptation problems.Awards: She is a recipient of the best research paper award from the Optical Society of America, invent award for commercialization during her academic tenure. She has also received individual excellence and team awards during her work in the industry. She is a senior member of date, she is an author or co-author of over 60 published international conference papers and 2 accepted international journal articles where one article is withheld for reasons of commercial sensitivity. She has served as a reviewer of conferences: CVPR, ICML, ECML, ICCV, WACV, Consumer Electronics, Elsevier Signal Processing, VR, ICGVIPP.S: If you are looking for an internship/pre-doc/full-time position in Deep Learning, Computer Vision, Graphics, and Augmented Reality. Get in touch with me at r••••••••@gmail.com. I prefer a 6-month internship or full time employment as we end up doing papers at reputed venues
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