To know more about the research, click on EEE Research.

Prof. BVVSN Prabhakar Rao

I am interested in the design and analysis of biomarkers for (i) brain tumor detection and (ii) breast cancer detection. and (iii) ECG signal detection and processing methods.

PhD Thesis Adjudication :  External PhD thesis adjudication is in progress (complete details will be furnished after report submitted)

Doctoral Thesis 

1. Paramkusham Spandana, “A Novel Approach for Classification and Early Detection of Breast Cancer using Image Enhancement, Image Segmentation and Feature Extraction on Mammograms” (Ph.D. awarded during Convocation, 2019). 

Supervisor : BVVSN Prabhakar Rao , Co-supervisor : KMM Rao 

2. Manu Gupta “Non-invasive methods for Glioma grade classification using MR images”  (Ph.D. awarded during Convocation, 2019)

Supervisor : BVVSN Prabhakar Rao , Co-supervisor : Venkateswaran R

3. Madhuri Bayya “Battery Monitoring source side excitation with voltage pulse sequence” (Ph.D. awarded during Convocation, 2018)

Supervisor : BVVSN Prabhakar Rao , Co-supervisor : Moorthy Muthukrishnan

4. Priyanka BG “Memristor Based Neural Networks for Signal Processing Applications” (on going) 

Supervisor : BVVSN Prabhakar Rao 

Undergraduate Thesis / Projects

Supervised more than 10 UG students Thesis workSupervised more than 80 Projects (SOP/LOP/DESIGN) for UG students 

Prof. R. Venkateswaran

1. Neurological Disorders: Amyotrophic Lateral Sclerosis (ALS),Multiple Sclerosis (MS), Stroke, Traumatic Brain Injury (TBI), Spinal cord Injury (SCI), Brain Tumor 

2. Neuroimaging: Structural MRI, functional MRI, Diffusion MRI, PET,  

3. Electrophysiology: EEG, Transcranial Magnetic Stimulation (TMS), EMG, Functional Electrical Stimulation (FES)

4. Other Research Areas: Biomechanics, Human Gait Analysis, Machine Learning, Neural Networks, Graph Theory (Brain Network Analysis)

Skills and Expertise: Diffusion MRI single shell, multi shell, Conventional MRI T1-w, T2-w, T2 relaxometry, Voxel Based Morphometry, Tensor Based Spatial statistics, cortical thickness analysis, TMS, EEG, EMG data processing, Tractography, Fractal analysis (mono and multi-fractal), ICA, Machine learning

Neuroimaging Softwares: FSL, SPM, DTI studio, Freesurfer, DSI studio, ExploreDTI, GAT, EEG Lab,

Other Softwares: working knowledge MATLAB, Python

More information can be found here https://universe.bits-pilani.ac.in/hyderabad/rajgopal/ResearchInterest

Dr. Rajesh Kumar Tripathy

1. Machine Learning and Deep Learning for Healthcare

2. Multisensor time-frequency Signal Processing

3. Graph Signal Processing and Vertex-Frequency Analysis

4. Sparse Representation and Dictionary Learning

5. Cardiovascular Signal Processing

6. Neural Signal Processing and Brain Computer Interface

7. Cognitive workload task classification and cognitive neuroscience

8. Cardio-Pulmonary Coupling and Circadian Monitoring

9. Electromyogram Signal Processing and Muscle Computer Interface

10. Multi-modal Affective Computing

11. Smart Health and Internet of Medical Things (IOMT)

12. Medical Image Processing and Automated Diagnostic system