Meenakshi
Delft
Summary
Computer Vision researcher with expertise in complex data analysis, signal processing, and machine learning. Skilled in developing advanced computational techniques for feature extraction, dimensionality reduction, and data interpretation, particularly in high-dimensional spectral datasets. With a focus on medical imaging, diagnostics, and high-dimensional imaging applications, I have developed innovative solutions to address real-world challenges.
Overview
9
9
years of professional experience
1
1
Certification
Work History
Postdoctoral Researcher
Delft University of Technology
04.2023 - Current
Current Project: Unsupervised Contrastive Learning for Molecular Pattern Recognition in Imaging Mass
Spectrometry Data.
- Developing a deep learning model to improve similarity detection in diverse biological samples, based on
shared biological structures, disease-specific features, and molecular markers while eliminating demographic
biases. This approach has the potential to significantly advance medical diagnostics by enabling more
precise, and reliable disease detection.
Previous Project: Computational Methods for Dimensionality Reduction and Isotope Candidate Detection in Imaging Mass Spectrometry Data.
- Developed computational methods to simplify complex imaging mass spectrometry data and automatically detect isotope candidates in high-dimensional data. These techniques improved understanding of molecular structures in biological tissues and enhanced data analysis accuracy and efficiency, enabling identification of critical molecular markers vital for drug development.
- Collaborated with multidisciplinary team member and drafted manuscript based on this research work that addressed major challenges and advanced the state of the art.
PhD Researcher
Indian Institute of Technology (IIT) Delhi
01.2016 - 10.2022
Sensing matrix optimization and feature extraction for image processing.
- Developed a robust sensing matrix based on an equiangular tight frame, reducing pairwise correlation and ensuring tightness. This advancement enhances compressive sensing in applications like wireless communication, medical imaging, satellite imaging, radar systems, and signal processing.
- Proposed a representation-based feature extraction model to address challenges of insufficient inter-class margin and loss of manifold structure. This approach is particularly effective in classification and recognition tasks with limited training data.
- A regression-based feature extraction model is developed to preserve the underlying structure of the data with sufficient inter-class margins.
Education
Ph.D. - Electrical Engineering
Indian Institute of Technology Delhi
Delhi, India10.2022
M.Tech. - Electronics and Communication Engineering
Panjab University
India01.2015
B.Tech. - Electronics and Communication Engineering
Kurukshetra University
India01.2012
Skills
- Programming: Python, MATLAB
- Deep Learning Frameworks: PyTorch, TensorFlow, Keras, scikit-learn
- Signal Processing Frameworks: scipy, librosa
- Others: Tikz, Latex, Beamer, Dia, LucidChart, Technical writing
Honor, Awards and Fellowships
- Presented a poster titled "IsoSpace: Chemistry-Informed Dimensionality Reduction and Automated Isotope Candidates Detection in Imaging Mass Spectrometry" at the American Society of Mass Spectrometry (ASMS) Annual Conference 2024.
- Ministry of Human Resources and Development (MHRD), Government of India fellowship as a PhD research scholar in Indian Institute of Technology Delhi.
- Recipient of Research Scholar Travel Award, from IIT Delhi to attend a international conference.
- Qualified GATE in Electronics and Communications twice (96.8 and 97.05 percentiles), a key exam for postgraduate admissions and engineering job screening in India.
- UGC NET, Qualified the National Eligibility Test for Lectureship conducted by University Grant Commission of India.
- Ministry of Human Resources and Development (MHRD), Government of India fellowship as a M.Tech. scholar in Panjab University.
- University Gold Medal in B.Tech. (for highest academic standing at the undergraduate level in the Kurukshetra University for 2012 Batch.
- Teaching Assistantship: Assisted in courses on Signal Analysis (TU Delft) and Signals and Systems, Advanced DSP, and Electrical Engineering (IIT Delhi), supporting students through lectures, lab sessions, and coursework, while fostering a strong understanding of complex technical concepts.
- Reviewer: IEEE Access, IEEE Transactions on Circuits and Systems for Video Technology, APSIPA Transactions on Signal and Information Processing.
Languages
English
Proficient
C2
Hindi
Bilingual or Proficient (C2)
Publications
- Twin relaxed least squares regression with classwise mean constraint for image classification, Meenakshi, Seshan Srirangarajan, Image and Vision Computing, 124, 104506, 2022
- Locality-aware discriminative subspace learning for image classification, Meenakshi, Seshan Srirangarajan, IEEE Transactions on Instrumentation and Measurement, 71, 1-14, 2022
- Incoherent and robust projection matrix design based on equiangular tight frame, Meenakshi, Seshan Srirangarajan, IEEE Access, 9, 131462-131475, 2021
- Sparse image reconstruction using improved regularized orthogonal matching pursuit, Meenakshi, Sumit Budhiraja, International Journal of Image, Graphics and Signal Processing, 1-13, 01, 2017
- Compressive sensing based image reconstruction using generalized adaptive omp with forward-backward movement, Meenakshi, Sumit Budhiraja, International Journal of Image, Graphics and Signal Processing, 19-28, 07, 2016
- A survey of compressive sensing based greedy pursuit reconstruction algorithms, Meenakshi, Sumit Budhiraja, International Journal of Image, Graphics and Signal Processing, 7, 1-10, 09, 2015
Certification
- Certification in Convolutional Neural Networks in TensorFlow (Coursera, April 2022).
- Certification in Natural Language Processing in TensorFlow (Coursera, April 2022).
Timeline
Postdoctoral Researcher
Delft University of Technology
04.2023 - Current
PhD Researcher
Indian Institute of Technology (IIT) Delhi
01.2016 - 10.2022
- Certification in Convolutional Neural Networks in TensorFlow (Coursera, April 2022).
- Certification in Natural Language Processing in TensorFlow (Coursera, April 2022).
Ph.D. - Electrical Engineering
Indian Institute of Technology Delhi
M.Tech. - Electronics and Communication Engineering
Panjab University
B.Tech. - Electronics and Communication Engineering
Kurukshetra University
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