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Dr. A. R. Jac Fredo, Ph.D
Assistant Professor
School of Bio-Medical Engineering IIT (BHU)
jack.bme@iitbhu.ac.in
+91 9444555798
Area of Interest: 
Bio-Medical Signal and Image Processing, Bio-Medical Instrumentation, Computational Neuroscience, Developmental Psychology, Neuro-Informatics, Machine Learning, Composite Science

Dr. Jac Fredo did his undergraduate in Electrical and Electronics Engineering from Anna University during 2004- 2008. He did first project study in 2007, as part of his undergraduate degree under Dr. Amalin Prince, BITS Pilani, K.K.Birla Goa Campus, India. This group worked with biomedical signal and image processing methods in application to FPGA devices. During this project work, he developed various filter methods to pre-process the vibro-arthrographic (VAG) signals and he got experience in biomedical signal processing, and coding platform like Labview. Dr. Jac started his research career in 2009 as a Masters student working under Dr. S. Ramakrishnan at Department of Instrumentation Engineering, Madras Institute of Technology, Anna University, Chennai, India. This group worked with different biomedical signal and image processing, pattern recognition, and machine learning algorithms in application to biomedical instrumentation. Dr. Jac participated in developing test systems for human brain evoked auditory signals using Virtual Audiometer and got experience in pattern recognition and machine learning algorithms, and coding platform like Rstudio. The outcome of the study was published in a conference held in Pune, India. Since 2010, Dr. Jac joined as a Junior Research Fellow in Neuro-informatics with the grant from University Grant Commission, Department of Science and Technology, India working under Dr. G. Kavitha, Anna University, Chennai, India and started to work on his Ph.D. thesis. This group worked in close collaboration with Dr. S. Ramakrishnan at the Non-Invasive Imaging and Diagnostics Laboratory, Biomedical Division, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India, on several projects of brain imaging. Dr. Jac’s Ph.D. thesis was devoted to the Neuro-informatics study of identifying structural brain based autistic traits in autism using sMRI, image processing and pattern recognition methods. Dr. Jac was trained in advanced image processing algorithms, brain imaging toolboxes such BSE, BET, Brain suite, Neuron, SPM8, and coding platform like Matlab during this tenure. Dr. Jac and his colleagues found that subcortical regions of brain can serve as an effective biomarker for the diagnosis of autism spectrum disorder and proved the presence of structural brain based autistic traits in autism. Dr. Jac also assisted in Electronics Labs and teaches basic Matlab for the students of Faculty of Electronics Engineering (Anna University) during this tenure. He has published 6 journals and 5 conference publications as part of his Ph.D thesis. Further, Dr. Jac travelled to Germany, The Netherlands, and United States of America through different travel grants and participated in workshops, presented research outcomes in conferences.  
After his Ph.D. in Neuro-informatics in 2015, Dr. Jac joined as a Project Associate in the same Lab under Dr. S. Ramakrishnan and was in charge for the projects in different fields including Brain imaging and EMG processing. He served in organizational committee for the conferences hosted by the lab during this tenure. He obtained skills in planning in vitro and in ​vivo experiments, statistical analysis, writing grant proposals, articles, patents, and working in an interdisciplinary team. Later, Dr. Jac joined as an Assistant Professor (Senior Grade) in 2016 at VIT University, Vellore, India and delivered courses on Bio-Medical Instrumentation, Sensors, Medical Physics and Rstudio for students. Further, Dr. Jac supervised three undergraduate projects, which have improved his skills in mentoring and support in career objectives. He undergone research in VAG signals, developed machine learning model for the diagnosis of articular diseases and published the outcome in a journal. Further, he developed a process pipeline to identify the damages in composite materials using digital images and published in 4 leading journals sooner and later. Dr. Jac was funded grant by Indo-Us Science and Technology Forum/ Science Engineering Research Board, India to pursue Post-Doctoral studies under Prof. Ralph Axel Mueller at Brain Development Imaging Lab, San Diego State University, USA in 2016. This group is pioneer in autism spectrum disorder research using behavioural, clinical measures, multi-model imaging modalities like sMRI, fMRI, DTI and EEG. He worked in two projects including machine learning models for autism using resting-state fMRI and identification of subtypes in autism using multi-model imaging methods. During this tenure, Dr. Jac was trained in resting-state fMRI processing, DTI processing and training in brain imaging tool boxes like FSL, AFNI, Freesurfer, coding in bash script and working on High Performance Computing through remote server. Based on his studies, Dr. Jac has published two papers (1 journal and 1 conference) related to machine learning models for autism. In 2018, Dr. Jac joined as a Research Fellow in Nanyang Technological University, Singapore under the supervision of Prof. Justin Dauwels. The lab is pioneer in developing advanced brain connectivity estimation methods and machine learning algorithms in application to brain development research. He got opportunity to work in brain connectivity analysis methods in collaboration with Prof. Georg Langs, Medical University of Vienna, Austria. The outcomes of this research study are published in a journal and a conference poster. During this tenure, Dr. Jac acquired a strong background in neuro-informatics (brain network connectivity estimation methods), machine learning (deep learning), high complexity algorithms, and coding platforms like python.
In the mid of 2020, Dr. Jac got Advanced Research Opportunities (AROP) Scholarship to wok under Dr. Kerstin Konrad, Clinics & Institute, Clinic for Psychiatry, Psychosomatic, and Psychotherapy of childhood and adolescents in RWTH Aachen, Germany. This group work in autism traits, neural mechanism, child development, gender variation, behavioural dimensions, neuroimaging, functional brain connectivity, and diagnostic classification of neuro developmental disorders. Recently, Dr. Jac joined as an Assistant Professor in the School of Bio-Medical Engineering in IIT (BHU), Varanasi, India.
2020-Present Assistant Professor in the School of Bio-Medical Engineering, IIT (BHU), Varanasi, India. Delivering courses in Bio-Medical Instrumentation and Medical Imaging Modalities, Bio-materials, Artificial Intelligence and its application in Bio-Medical Engineering, Electronic Measurements and Instrumentation for Bio-Medical Applications for undergraduates, Masters and Ph.D students
2020 Research Fellow in Clinics & Institute, Clinic for Psychiatry, Psychosomatic, and Psychotherapy of childhood and adolescents in RWTH Aachen, Germany. Studied a project under the title “Investigation of autistic traits in typical developing fMRI of brain using sparse inverse co-variance estimation methods and machine learning approaches” under Prof. Kerstin Konrad.
2018-2020 Research Fellow in the Department of Electrical Engineering, Nanyang Technological University, Singapore. Participated in a research project “Multimodal brain imaging and network inference to capture changes due to autism” under Prof. Justin Dauwels, Nanyang Technological University, in collaboration with Prof. George Langs, Medical University of Vienna, Austria.
2017-2018 Research Fellow in Brain Development Imaging Lab, Department of Psychology, San Diego State University, USA. Studied gender specific functional brain connectivity in autism which was found in a project on “Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity” under the supervision of Prof. Ralph Axel Mueller.
Participated in a study “Assessment of subtypes of autism spectrum disorder based on structural, functional and clinical scores” under the supervision of Prof. Ralph Axel Mueller.
2016-2017 Assistant Professor, Department of Biomedical Engineering, VIT University, Vellore, India. Delivered courses in Bio-Medical Instrumentation, Sensors, Medical Physics and Rstudio for Beginners courses for groups of about 60 undergraduate students.
2015-2016 Research Associate in Department of Applied Mechanics, Biomedical Division, Indian Institute of Technology Madras, Chennai, India. Project leader in a research project “Corpus callosum: A structural brain biomarker for autism diagnosis” under the supervision of Dr. S. Ramakrishnan.
2011-2015 Teaching Assistant, Department of Electronics Engineering, Anna University. Assisted in Electronics Labs and teaches basic Matlab for Beginners courses for groups of about 30 undergraduate students.
2008-2010 Teaching Assistant, Department of Instrumentation Engineering, Anna University. Assisted in Electrical Machines Lab and teaches Rstudio and Labview for Beginners courses for groups of about 30 undergraduate students.
List of Book Publications
  1. Abirami S, John T, Yuvaraj R and Jac Fredo AR (2021), “A comparative study on EEG features for neonatal seizure detection”, edited book chapter in Springer, titled as, Biomedical signal-based computer aided diagnosis for neurological disorders.

List of Journal Publications

  1. S Shaji, Jac Fredo AR, AK Ramaniharan, R Swaminathan (2022) ‘Study on the Effect of Extreme Learning Machine and its Variants in Differentiating Alzheimer Conditions from Selective Regions of Brain MR Images, Expert Systems with Applications, 118250 (Elsevier publishers, IF:8.665)
  2. Rakshit Mittal; A. Amalin Prince; Jac Fredo AR (2022) ‘Time-sliced architecture for efficient accelerator to detrend high-definition electroencephalograms’, IEEE Transactions on Instrumentation and Measurement, vol. 71 (IEEE publishers, IF:5.332).
  3. Femi Robert, Amalin Prince A, JacFredo AR (2021), ‘Influence of wire electrical discharge machine cutting parameters on the magnetization characteristics of electrical steel laminations’ Materials Today: Proceedings, https://doi.org/10.1016/j.matpr.2021.10.141 (Elsevier publishers, IF: 1.24)
  4. Amalin Prince, Rakshit Mittal, Saif Nalband, Femi Robert, Jac Fredo AR (2021), ‘Modified-MaMeMi Filter Bank for Efficient Extraction of Brainwaves from Electroencephalograms’, Biomedical Signal Processing & Control, https://doi.org/10.1016/j.bspc.2021.102927 (Elsevier publishers, IF:3.137)
  5. Jac Fredo AR, John T, Prasanth T, Vineetha K, Georg L & Justin D (2020), ‘Diagnostic classification of autism using resting-state fMRI data improves with full correlation functional brain connectivity compared to partial correlation’, Journal of Neuroscience Methods, https://doi.org/10.1016/j.jneumeth.2020.108884 (Elsevier publishers, IF:2.785)
  6. Maya AR, Afrooz J, Jac Fredo AR, Inna F, Barbara B & Ralph-Axel M (2020), ‘Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity’, Neural Computing and Applications, https://doi.org/10.1007/s00521-020-05193-y (Springer publishers, IF:4.774)
  7. Rakshit M, Amalin PA, Saif N, Femi R, & Jac Fredo AR (2020), ‘Low-power hardware accelerator for detrending measured biopotential data’, IEEE Transactions on Instrumentation and Measurement. (IEEE publishers, IF:3.658)
  8. Jac Fredo AR, Abilash RS, Femi R, Sri Madhava Raja N, & Suresh Kumar C (2020) ‘Automated damage detection and characterization of polymer composite images using Tsallis-particle swarm optimisation based multi-level threshold and multifractals’ Polymer Composites, https://doi.org/10.1002/pc.25611 (Wiley publishers, IF: 2.268)
  9. Suresh Kumar C, Arumugam V, Kenned JJ, Karthikeyan R, & Jac Fredo AR (2019) ‘Experimental investigation on the effect of glass fiber orientation on impact damage resistance under cyclic indentation loading using AE monitoring’ Nondestructive Testing and Evaluation, https://doi.org/10.1080/10589759.2019.1684491 (Taylor and Francis publishers, IF: 1.735)
  10. Femi R, Sharma A, Katare H, & Jac Fredo AR (2019) ‘Investigation of graphene as a material for electrical contacts in the application of microrelays using finite element modeling’ Materials Research Express, vol. 6, no. 9, pp. 1-14 (IOP Science publishers, IF: 1.449)
  11. Jac Fredo AR, Abilash RS, Femi R, Sri Madhava Raja N, & Suresh Kumar C (2019), ‘Characterization of global and local damages in composite images using geometrical and Fourier-Hu moment based shape descriptors’, Journal of Testing and Evaluation, https://doi.org/10.1520/JTE20180701 (ASTM International publishers, IF: 0.711)
  12. Jac Fredo AR, Abilash RS, Femi R, Mythili A, & Suresh Kumar C (2018), ‘Classification of damages in composite images using Zernike moments and support vector machines’, Composites B: Engineering, vol. 168, pp. 77-86. (Elsevier publishers, IF: 6.864)
  13. Jac Fredo AR, Abilash RS, & Suresh Kumar C (2017), ‘Segmentation and analysis of damages in composite images using multi-level threshold methods and geometrical features’, Measurements, vol. 100, pp. 270-278. (Elsevier publishers, IF: 2.794)
  14. Jac Fredo AR, Josena TR, Rajkumar E, & Mythili A (2017), ‘Classification of normal and knee joint disorder vibroarthrographic signals using multi fractals and support vector machines’, Biomedical Engineering: Applications, Basis and Communications, vol. 29, no. 3, pp. 1-9. (World Scientific publishers)
  15. Karthick PA, Navaneethakrishna M, Punitha N, Jac Fredo AR, & Ramakrishnan S (2016), ‘Analysis of muscle fatigue conditions using time-frequency images and GLCM features’, Current Directions in Biomedical Engineering, vol. 2, pp. 1-4. (De Gruyter publishers)
  16. Jac Fredo AR,  Kavitha G & Ramakrishnan S (2015), ‘Automated segmentation and analysis of corpus callosum in autistic MR images using fuzzy c-means based level set’, Journal of Medical and Biological Engineering, vol. 35, no. 3, pp. 331-337. (Springer publishers, IF: 1.211) 
  17. Jac Fredo AR,  Kavitha G & Ramakrishnan S (2015), ‘Segmentation and analysis of corpus callosum in autistic MR brain images using reaction diffusion level sets’, Journal of Medical Imaging and Health Informatics, vol. 5, pp. 1-5. (American Scientific publishers, IF: 0.549)
  18. Jac Fredo AR,  Kavitha G & Ramakrishnan S (2015), ‘Subcortical region segmentation using fuzzy based augmented Lagrangian multiphase level set method in autistic MR brain images’, Biomedical Sciences Instrumentation, vol. 51, pp. 323-331.  (Instrumentation Society of America)
  19. Jac Fredo AR,  Kavitha G & Ramakrishnan S (2014), ‘Segmentation and analysis of brain sub-cortical regions using regularized multi-phase level set in autistic MR Images’, International Journal of Imaging Systems and Technology, vol. 24, no. 3, pp. 256-262. (Wiley publishers, IF: 1.423)
  20. Jac Fredo AR, Kavitha G & Ramakrishnan S (2014), ‘Segmentation and morphometric analysis of sub-cortical regions in autistic MR brain images using fuzzy Gaussian model based distance regularized multi-phase level set’, International Journal of Biomedical Engineering and Technology, vol.15, no.3, pp. 211-223. (Inderscience publishers)
  21. Jac Fredo AR,  Kavitha G & Ramakrishnan S (2014), ‘Analysis of cortical and subcortical regions in autistic MR images using level set method and structure tensors’, Biomedical Sciences Instrumentation, vol. 50, pp. 140-149. (Instrumentation Society of America)
List of Conference Publications
  1. Vaibhav Jain, Abirami Selvaraj, Rakshit Mittal, Priya Rani, Anandh Kilpattu Ramaniharan, Jac Fredo AR (2022) ‘Automated diagnosis of autism spectrum disorder condition using shape-based features extracted from brainstem’, Challenges of Trustable AI and Added-Value on Health,European Federation for Medical Informatics (EFMI), 32nd Medical Informatics Europe Conference (MIE2022), Nice, France, May 27-30, 53-57.
  2. Edwin M, Saif N, Jac Fredo AR, & Amalin Prince A 2020, ‘Analysis and classification of vibroarthrographic signals using tuneable ‘Q’wavelet transform’, 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN), pp.65-70.
  3. Jac Fredo AR, Georg L. & Justin D, 2019, ‘Classification of typical developing and autism spectrum disorder using connectivity matrix and support vector machines’, IEEE International conference on Engineering in Medicine and Biology, Berlin, Germany.
  4. Jac Fredo AR, Maya R, Afrooz J & Ralph AM, 2018, ‘Classification of autism and control on resting state fMRI using conditional random forest’, IEEE International conference on Engineering in Medicine and Biology, Honolulu, Hawaii.
  5.  Jac Fredo AR,  Kavitha G & Ramakrishnan S 2015 ‘Analysis of corpus callosum and its sub-anatomical regions in autistic MR brain images using structure tensors’, Second International Conference on Biomedical Systems, Signals and Images, IIT Madras, 2015. 
  6. Jac Fredo AR, Kavitha G & Ramakrishnan S 2014, ‘Segmentation of sub-cortical regions of autistic MR brain images using combination of fuzzy c-means and Gaussian distribution model based augmented Lagrangian multi-phase level sets’, Nineteenth International Conference on Mechanics in Medicine and Biology, Bologna, Italy, pp. 431-434, ISBN: 978-88-901675-1-5.
  7. Jac Fredo AR,  Kavitha G & Ramakrishnan S 2014, ‘Analysis of sub-cortical regions in cognitive processing using fuzzy c-means clustering and geometrical measure in autistic MR images’, 40th North East Bio-Engineering Conference, Boston, United States of America, pp. 1-2, doi: 10.1109/NEBEC.2014.6972791. 
  8. Jac Fredo AR, Kavitha G & Ramakrishnan S 2014, ‘Segmentation and analysis of subcortical regions of autistic MR brain images using Gaussian distribution model based reaction diffusion multi-phase level sets and geometric feature’, Frontiers in Neuroinformatics, doi: 10.3389/conf.fninf.2014.18.00090. Leiden, The Netherlands
  9. Jac Fredo AR, Kavitha G & Ramakrishnan S 2014, ‘Characterization of autistic MR brain images using fuzzy c-means based reaction diffusion multi-phase level sets and structure tensor’, National Conference on Present Scenario and Future Trends in Biomedical Engineering and Healthcare Technologies, IIT Varanasi, India. 
  10. Jac Fredo AR, Ramakrishnan S, Jaginth C, & Srinivasan S 2010, ‘Virtual Audiometer‘, International Conference on Instrumentation, Instrumentation Society of India, Pune, India.
  11. Jac Fredo AR 2007, ‘SCADA-Automation in thermal power plant‘, Conference on Efactory Technologies and Challenges, IRTT Erode, India.
Conferences
  • IEEE International conference on Engineering in Medicine and Biology, Berlin, Germany, 2019 (poster presentation), Hawaii, USA, 2018 (oral presentation).
  • IEEE North East Bio-Engineering Conference, Boston, USA, 2014 (oral presentation).
  • International Conference on Mechanics in Medicine and Biology, Bologna, Italy, 2014 (oral presentation).
  • INCF congress of Neuro-informatics, University of Leiden, Leiden, The Netherlands, 2014 (oral presentation).
  • National Conference on Present Scenario and Future Trends in Biomedical Engineering and Healthcare Technologies, IIT Varanasi, India, 2014 (oral presentation).
  • International Conference on Instrumentation, Instrumentation Society of India, Pune, India, 2010 (oral presentation).
Courses
August, 22-23, 2014 INCF short course on “Introduction to neuro-informatics”, University of Leiden, Leiden, The Netherlands
September, 20-28, 2012 BBCI summer school on “Advances in neuro-technology”, Technical University of Berlin, Berlin, Germany
October, 15-16, 2012 Workshop on “Image processing framework using FPGA”, Anna university, Chennai, India

Awards:
1. Distinguished Alumina Award, 14/05/2022, Department of Instrumentation Engineering, Madras Institute of Technology, Anna University, India.

Grants and Funding:
 

Sl.No Type of funding Scheme Agency Location Amount
1.  Research Grant  DST-TIH IIT Kanpur India 36k Euros approximately
1. Research Grant Startup Research Grant SERB, DST India 20k Euros approximately
2. Research Grant Seed Grant IIT (BHU) India 11.5k Euros
3. Exchange Fellowship Grant AROP RWTH Aachen Germany 11k Euros
4. Post-doctoral Fellowship Grant Overseas Grant IUSSTF, SERB/DST India-USA 42k Euros approximately
5. Doctoral Fellowship Grant MANF UGC India 20k Euros approximately
6. Travel Grant BBCI Summer workshop Technical University of Berlin Germany 500 Euros
7. Travel Grant Neuro-informatics workshop INCF The Netherlands 500 Euros
8. Travel Grant Conference TSCST India 500 Euros approximately

Current Team

Name Position
Sriram Kumar P Ph.D Student (QIP scheme)
Vaibhavi  Ph.D Student (Institute Teaching Assistance Fellowship)
Saumya Singh Ph.D Student (CSIR Fellowship)
Chetan Rakshe Junior Research Fellow
Praveen Kumar Masters Student
Vaibhav IDD Student
Vinay Kumar IDD Student
Gokul Manoj IDD Student
Aditi Summer Intern
Rohan Summer Intern
Aleem Exploratory Project
Vedhantham  Exploratory Project

Foreign Collaborators
 

Name Institute
Dr. John Thomas McGill University, Canada
Dr. Priya Rani RMIT University, Australia
Dr. Yuvraj Rajamanickom National Institute of Education, Nanyang Technological University, Singapore
Dr. Nagarajan TU Braunschweig, Germany
Dr. Anandh Kilpattu Ramaniharan The University of Alabama at Birmingham, United States America

Aluminees 

Name Position in Lab Current Position
Abirami S Masters Student Project Fellow in IIT Kanpur
S. No. Title of Lecture/Lecture Series Date, Place and Programme where lectures delivered
1 Teaching seminar of electrodes for ECG, EEG, and EMG Department of Electrical and Electronics Engineering, SRM University, Chennai,17/06/2022
1.  Neuroimaging methods for neurodevelopmental disorders Keynote talk in International Conference on Innovative Engineering and Technology, 02/06/2022, DMI College of Engineering, Chennai, Tamilnadu. 
2.  fMRI time series analysis methods  Five days FDP on "Internet of Everything - IoE", 21/05/2022, VIT Univerisity, Vellore, Tamilnadu.
3.  Sparse inverse covariance methods for fMRI time series  Six days online AICTE-AU-STTP on "Data Science Applied to Measurement and Control", 03/02/2022, Department of Instrumentation Engineering, Madras Institute of Technology, Anna University, Chennai, Tamilnadu. 
4. Artificial intelligence methods for time series fMRI data analysis Guest Lecture on 21/12/2022 in Department of Medical Informatics, TU Brunsweig, Germany
5.  Artificial intelligence methods for volumetric sMRI data analysis Guest Lecture on 16/12/2022 in Clinical Child Neuropsychology, RWTH Aachen Univeristy, Aachen, Germany
 6. Neuroimage processing for ASD diagnosis Instrumentation, signals and images for the evolution of physiological systems, 18/08/2021, at Department of Instrumentation and Control Engineering, NIT-Trichy, Tamilnadu.
 7. Application of Machine Learning in Medical Imaging Advances in Medical Imaging, on 18/03/2021, at IIT (BHU), Varanasi, Uttar Pradesh.
 8. Neuro-informatics methods for neuroimaging Hands on project based approach for biomedical signal analysis using MATLAB, on 06/02/2021 at Kakatiya Institute of Technology and Science Warangal, Telangana.
 9. Machine Learning in Neuroimaging Biomedical Signal Processing in Precision Health on 18/12/2020, organized by ECE Department, Thiagarajar College of Engineering, Madurai, Tamilnadu.
 10. Multi-model Neuroimage analysis Research Scholars Day, on 05/09/2020, Department of Instrumentation, MIT Campus, Anna University, Chennai, Tamilnadu.

IIT (BHU)

Level Course No. & Title
P.G BM511: Artificial Intelligence and its Application in Biomedical Engineering
P.G. BM509: Bioinstrumentation
U.G. BM401: Bioinstrumentation and Medical Imaging Modalities
U.G BM301: Electronic Measurement and Instruments for Biomedical Applications
U.G. BM204: Biomaterials

VIT University:

Level Course No. & Title
UG ECE1011: Medical Physics and Biomedical Instrumentation
UG ECE1005: Sensors and Instrumentation
UG ECE1001: Fundamentals of Electrical Circuits Laboratory

Post-doctoral Positions

Postdoc candidates (having fellowship from CSIR, DST, DBT etc.)  or wish to apply may contact me by sending detailed CV with research interests.(Candidates with Engineering backgrounds are preferred)

Ph.D. Positions

Ph.D. positions are available in my lab for students who have qualified CSIR/UGC/DBT JRF/ DST inspire fellowship. Interested candidate have to follow guidelines of IIT-BHU PhD admission (Candidates with Engineering backgrounds or proficiency in coding platforms like Matlab, Python or Rstudio are preferred)

Summer or Winter internships

Summer or Winter internships are available in my lab for Masters and Undergraduate students. Candidates can sent their CV and project proposal.

1. Mr. Gokul Manoj, Fourth year IDD student awarded DAAD-Combined Study and Practice Stays for Engineers from Developing Countries (KOSPIE) to pursue research under Prof. Kerstin Konrad, RWTH Aachen University, Aachen, Germany from September 2022 to March 2023.
2. Mr. Vaibhav Jain, Fourth year IDD student published a conference paper in Challenges of Trustable AI and Added-Value on Health,European Federation for Medical Informatics (EFMI), 32nd Medical Informatics Europe Conference (MIE2022), Nice, France, May 27-30, 2022.
3. Mrs. Abirami, Second year M.Tech student published a chapter in Springer, titled as, Biomedical signal-based computer aided diagnosis for neurological disorders, 2021.
4. NAS server available in our lab, which permits to access the medical data available in our lab from anywhere around the campus. 
5. UPS available in our lab, which can support the NAS and workstation to get continues power supply.