Publications:
Journals:
1) Nitin Satpute, R. Naseem, E. Pelanis, J. Gomez-Luna, F. Alaya Cheikh, O. J. Elle, J. Olivares, “GPU acceleration of liver enhancement for tumor segmentation”, published in Computer Methods and Programs in Biomedicine 184 (2020) 105285, DOI:https://doi.org/10.1016/j.cmpb.2019.105285. (CMPB – Q1, IF 3.632).
2) Nitin Satpute, J. Gomez-Luna, and J. Olivares, “Accelerating Chan-Vese Model with Cross-Modality Guided Contrast Enhancement for Liver Segmentation” published in Computers in Biology and Medicine (2020) 103930, doi: https://doi.org/10.1016/j.compbiomed.2020.103930. (Q1, IF 3.434).
3) Nitin Satpute, R. Naseem, R. Palomar, O. Zachariadis, J. Gomez-Luna, F. Alaya Cheikh, and J. Olivares, “Fast Parallel Vessel Segmentation”, published in Computer Methods and Programs in Biomedicine (2020) 105430. DOI: https://doi.org/10.1016/j.cmpb.2020.105430. (CMPB – Q1, IF 3.632).
4) O. Zachariadis, A. Teatini, Nitin Satpute, J. Gomez-Luna, O. Mutlu, O. J. Elle, and J. Olivares, “Accelerating B-spline Interpolation on GPUs: Application to Medical Image Registration”, published in Computer Methods and Programs in Biomedicine (2020) 105431, DOI: https://doi.org/10.1016/j.cmpb.2020.105431. (CMPB – Q1, IF 3.632).
5) O. Zachariadis, Nitin Satpute, J. Gomez-Luna, and J. Olivares, “Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores” published in Computers and Electrical Engineering, Volume 88, 2020, 106848, ISSN 0045-7906, https://doi.org/10.1016/j.compeleceng.2020.106848. (Q2, IF 2.663).
6) Nitin Satpute, J. Gomez-Luna, and J. Olivares, “Fast Parallel Cropping for Liver Segmentation and Volume Assessment” under internal review 2020.
7) R. Naseem, Nitin Satpute, Z. A. Khan, A. Beghdadi, O. J. Elle, J. Gomez-Luna, J. Olivares, and F. A. Cheikh “Cross Modality Guided Liver CT Enhancement for Improved Tumor Segmentation” under internal review (2020).
8) A. Shriram, N. Dhabekar, M. Hussain, P. Jumle and Nitin Satpute, “Segmentation & Classification of MRI Brain Images using Texture Features”, published in the International Journal of Machine Intelligence & Applications (2011).
Conferences:
1) M. Mohammadi, Nitin Satpute, R. Ronge, J. Chandiramani, S K Nandy, A. Raihan, T. Verma, R. Narayan and S. Bhattacharya, “A Flexible Scalable Hardware Architecture for Radial Basis Function Neural Networks” published in the International Conference on VLSI Design and Embedded Systems, 2015, DOI: 10.1109/VLSID.2015.91.
2) B. Kumar Koora, Nitin Satpute and A. Adiga, “Tabu Search based implementation of object tracking using Joint Colour Texture Histogram” published in the International Conference on Industrial and Information Systems, IIT Chennai, IEEE Explore, August 6, 2012, pp. 1-6, DOI: 10.1109/ICIINFS.2012.6304829
3) Nitin Satpute, J. Gomez-Luna, and J. Olivares, “GPU based Liver Image Segmentation” at VII Congreso Científico de Investigadores en Formación de la Universidad de Córdoba, Feb 2019.
4) Nitin Satpute, Juan Gomez-Luna, and Joaquin Olivares, “Evaluation of GPU Region Growing Methods on NVIDIA GPUs” in JAI (III Jornadas Andaluzas de Informática) 2017, Malaga, Spain.
5) Nitin Satpute, Roberto Giorgi, “Comparing and Evaluating GPU Platforms with a Single Point” in the Eleventh International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems – ACACES 2015.
Posters:
1) Nitin Satpute, J. Gomez-Luna, and J. Olivares, “Fast Parallel Liver Segmentation”, presented a poster at the 7th Annual Meeting of the European Computer Assisted Liver Surgery Society (ECALSS), Bern, Switzerland (www.ecalss.org), Oct 2019.
2) Nitin Satpute, J. Gomez-Luna, and J. Olivares, “GPU based Liver Image Segmentation”, poster at VII Congreso Científico de Investigadores en Formación de la Universidad de Córdoba, Feb 2019.
3) Nitin Satpute, J. Gomez-Luna, and J. Olivares, “Fast Parallel Seeded Region Growing for Liver Segmentation”, presented a poster at HiPerNav Training Event in University of Corodba, Spain, Sept 2018 – https://hipernav.eu/wp-content/uploads/2018/11/CHW-Full-program-R.pdf
4) Nitin Satpute, “Matrix Multiplication Performance Characterization on GPUs with a Single Point” presented a poster in Programming and tUning Massively Parallel Systems – PUMPS 2015 at Barcelona Supercomputing Center (BSC), Spain.
5) Nitin Satpute, and R. Giorgi, “Comparing and Evaluating GPU Platforms with a Single Point” presented a poster in the Eleventh International Summer School on Advanced Computer Architecture and Compilation for High-Performance and Embedded Systems – ACACES 2015.
Projects:
1. GPU Acceleration for Enhancement and Segmentation of Pre-operative and Intra-operative Images: I am involved in the development and implementation of high performance parallel algorithms for liver enhancement and segmentation. We propose fast parallel cross modality based liver enhancement and accelerate region growing and Chan-Vese algorithms for the segmentation of liver, vessels and tumors providing average speedup of 100 times compared to the CPU implementation. Environments and Platforms: Linux, C++, CUDA, OpenCL, Python, and NVIDIA GPUs GeForce GTX 1050, RTX 2070 and 2080 Ti.
2. Convolutional Deep Neural Network (CNN) for Breast Cancer Detection: I have implemented convolutional, activation (ReLU and Sigmoid), pooling, fully connected and softmax layers. I have developed mathematical models for robust feature learning. It includes learning from adversarial examples and making classifiers perform robustly when confronted with such hard positive/negative examples. The parameters responsible for feature learning are number of each of the mentioned layers, selection of the activation functions, pooling parameters (max or mean, stride depth, pool size) and the type and size of the filters. The flow starts by choosing number of parameters randomly and initializing them with random numbers. Then the experimental and mathematical analysis is done to update the filters. I have implemented back-propagation algorithm (stochastic gradient descent (SGD)) for error minimization. (Environment – Linux, Python and MATLAB)
3. Static Approach for One Dimensional Task Placement on FPGA: In One Dimensional Task Placement on FPGA, I have explored the static resource allocation of the various tasks.
4. Basic CPU Design using Verilog HDL and its implementation on FPGA: An 8-bit processor is designed and implemented using Bottom up approach. The design is compiled and simulated under the integrated development environment of Quartus II.
5. Bulk synchronous parallel computing (BSPC) on H.265 video decoder: BSPC provides a robust model for parallel computation and a programming framework which facilitates the development of portable algorithms and performance prediction. It is capable of providing a cost model to design, analyse and optimize massively parallel algorithms for various applications. (https://www.youtube.com/watch?v=6m4Tt4305_E&feature=youtu.be)
6. Segmentation & Classification of MRI Brain Images using Texture Features: Segmentation and classification of MRI brain images as normal or abnormal are performed using K Nearest Neighbor classification algorithm with large number of input test images for better accuracy. Dealt with the some of the Mathematical Statistical concepts related to segmentation and clustering algorithms such as Distributions, Bayes theorem, Entropy, Mean, Mode, Median etc.
7. Tabu Search based implementation of object tracking using Joint Colour Texture Histogram: A new robust methodology has been proposed which uses Tabu search algorithm along with joint color texture histogram to track a moving object efficiently.
8. Implementation of Wireless Sensor Nodes for Temperature Measurement: The Wireless Sensor Nodes were implemented using ARM7 Micro-controller LPC2148 and CC25OO based RF Modules employing FHSS modulation scheme for communicating between both nodes. The LM35 transistor was used as the temperature sensor. A Half-Duplex communication was used to send temperature values at Real-Time basis from one node to another and the values of temperature of both Nodes were displayed on their Individual LCDs. The code for Embedded C was designed and compiled in Keil Compiler.
9. Design & Simulation of Piezo-Resistive MEMS Strain Sensor: A MEMS strain Sensor was designed and simulated using Intellimask, 3DBuilder and Intellisuite. An unbounded corrugated structure was designed and its results were compared, the structure showed smaller stress range but higher sensitivity.
Following attachments are related to the publications.
Satpute_2017_Evaluation_of_GPU
Achievements:
1. Awarded Marie Skodowska-Curie grant from the project High Performance Soft-tissue Navigation (HIPERNAV – H2020-MSCA-ITN-2016) in an Innovative Training Network (ITN) at University of Cordoba, Spain.
2. Assisted Prof. Donald Reay (Associate Professor in the School of Engineering and Physical Sciences at Heriot-Watt University, Edinburgh UK) in conducting three days Faculty Development Program (FDP) on Digital Signal Processing for Educators at International Institute of Information Technology, Bangalore (IIIT-B), VNIT Nagpur and NIT Patna.
3. Conferred funding from Ministry of Electronics and Information Technology (MeitY), India (Jan 2016 – May 2017)
4. Attended “The 2015 LOFAR Surveys Meeting” held at Leiden, Netherlands
(https://www.strw.leidenuniv.nl/cms/web/2015/20150914/info.php3?wsid=44)
5. Attended “AXIOM Face to Face Meet” held at Barcelona Super-computing Center (BSC), Spain
6. Acceptance for PUMPS 2015, BSC, Spain (http://bcw.ac.upc.edu/PUMPS2015/) and ACACES 2015, Fiuggi, Italy (http://acaces.hipeac.net/2015/) Summer Schools
7. Conferred GATE scholarship during Master of Engineering from BITS Pilani, India (Aug 2011 – July 2013)
8. Full fee waiver for securing one of the top five ranks in the State Engineering Entrance Examination (Aug 2007 – June 2011)
9. Percentage: 86.83% in XII with 93% marks in Maths and 88.26% in X with 91.33% marks in Maths
10. Delivered Workshop on “Development of Embedded Processors using ARM Cortex M0+ Processors” at Global Academy of Technology, Bangalore, India
11. Invited as a Guest for 72nd Independence Day at South Point School, Nagpur
12. Delivered Workshop on “Machine Learning and Artificial Intelligence, Industry Requirements and Applications” at YCCE, Nagpur, India (22-23 Dec, 2018)
13. Conducted Student Development Program (SDP) on “Deep Learning: Industry Requirements and Applications” at YCCE, Nagpur, India (10-11 Aug, 2019) https://www.youtube.com/watch?v=_7eGwmhFi-E
14) Delivered a talk on “U-Net and YOLO for Liver Cancer Diagnosis” at the Faculty Development Program (FDP) conducted by COEP Pune and MTU Imphal, India (17 Jul 2020).
Nitin R Satpute 