Experience & Projects

Work Experience (Relevant)*: National Institute of Health (NIH) Biosketch.

January 1, 2022-Present: Assistant Professor (tenure-track faculty) in Department of Computer Science and with a joint appointment in Biology, School of Natural Sciences and Mathematics at Claflin University (HBCU/MSI), Orangeburg, South Carolina, USA. Course coordinator for Bioinformatics major. Enhanced the established teaching program by enhancing the learning and research opportunities for students in the School of Natural Sciences and Mathematics. Promoted peer-peer learning, hands-on laboratory assignments to enhance critical thinking skills [classes including Probability & Statistics I & II, Biostatistics, Data Analysis (topics including descriptive & inferential statistics, variable types, distribution properties, discrete & continuous types, R functions, probability distributions (Discrete, Binomial, Poisson, Continuous Uniform, Chi-squared, Student-t, Fisher, Exponential, Normal, Chi-Square)
, Analysis of Variance (ANOVA), receiver operating characteristic (ROC), linear and the quadratic discriminant analysis (LDA and QDA), T-test, correlation, chi-Square, regression ((linear, multiple, logistic)), etc.), Honors & Junior Seminar, Bioinformatics (topics including sequence alignment algorithms, scoring matrices, microarray analysis, phylogenetic analysis, bootstrapping, tree plot rooted, unrooted tree structure, building, visualization: heat maps, volcano plots, pie charts, blast, Gene Expression Omnibus (GEO) datasets mining, Read, Pre-processing/Normalization (Affy, Oligo, Limma-RMA, Robust Multiarray normalization, Basic Local Alignment Search Tool, Quantile, Mas5.0), Fold change expression analysis, Gene Set Enrichment Analysis (GSEA), Pathways and protein downstream interactome analysis. Sequence alignments (Margaret Dayhoff, Point Access Mutations (PAM), File formats (Fasta, etc.), blossom (Block Substitution Matrix) scoring matrices, global & local alignment), secondary & tertiary structure prediction, homology modeling, and protein folding)], Intro to Digital Logic Design and Lab (Emphasis on digital computer hardware and software, fundamentals of Boolean algebra (MATH111), switching and switching functions, Digital logic gates, applications to logic design, minimization of Boolean function, logic design with arrays, finite state model for sequential state minimization, design abstractions, representations, process, Karnaugh maps, K-map simplification, combinatorial components, multiplexers, decoders, selectors, Read-Only Memory (ROMs), Programmable Logic Array (PLAs), hybrid components, sequential logic, Mealy/Moore finite state machines, state minimization, encoding, control unit design), Object Oriented Programming (topics including inheritance, msg passing, polymorphism, recursion, abstraction, encapsulation, software design techniques, etc.), (STAT341, STAT401, CSCI/HNTH391/392, BTEC620, BIOL560, STAT451, CSCI225, BIOL441, BTEC599/699), CSCI462  (App Development Lifecycle (ADLC), user interface (UI) design, programming languages (Java, Kotlin for android studio, Swift, Xcode for iOS, React Native for cross platform), database management, application logic, testing methodologies, deployment processes, maintenance strategies  mobile development frameworks, cloud services, performance optimization, and security practices), CSCI101, Introduction to computer technology (computer hardware (processors, LMC, storage, I/O devices, software life cycle), software components and applications, programming constructs, secure computing (threats, malware, phishing, vulnerability), Exploratory Data Analysis (visualization plots), statistical tests (T-test, correlation, ANOVA, chi-square) functions, ethics in computing, promoted open door policy for improving student-teacher relations, and promoting virtual teaching to ensure competency with global culture. Contributions towards graduate Accreditation Board for Engineering and Technology (ABET) accreditation proposal for School of Natural Sciences and Mathematics. Engaged in faculty and staff enhancement activities by monthly departmental meetings and development workshops, serve the college and community by participating in science fairs and promoting STEM program in local community, involved in research and faculty development activities. Worked on course amendments and new course development (curriculum, pedagogical content creation) for improvising syllabus structure of junior, senior and honors computer science seminar classes CSCI 391, HNTH 391 and Data Science (Data wrangling, handling, visualization, Machine Learning QDA, LDA, ROC, Decision Trees, Regularization, Text Analysis Feature Engineering, Classification and Model Evaluation, Regression: Basics and Prediction, Evaluation and Interpretation, Clustering, etc.) course. Biotechnology Program Advisory Board, Faculty search committee member, Department of Mathematics and Computer Science for hiring new Computer Engineering and Cyber Security faculty. Academic Advisor (thesis & project) and mentored 41 students (HBCU graduates, National Institute of Health (NIH) Undergraduate Research Training Initiative for Student Enhancement (U-RISE), Biomedical Research Summer Internship Program (BR-SIP), high-school BR-SIP, interns) to successfully transition them to medical, graduate schools and STEM jobs (University of Connecticut Medical School, Farmington, University of Alabama, Birmingham, USA, Microsoft, Amazon, Seattle, Washington, USA,  Novartis Cambridge, Massachusetts, USA, etc.). Current projects in collaboration with Dr. Liles, Smart Home Claflin University seed funding, Dr. Bagasra, “Coronavirus transcriptomics”, Dr. Chowdhary, “Prostate Biomarkers”, Dr. Sahu, “Machine learning applications (generative adversarial network (GAN)) in cybersecurity”, Dr. Tisdale, National Science Foundation (NSF) South Carolina Established Program for Stem Cooperative Research (SC EPSCoR), RII Track-1 Award Grant/award/project title: “AI-enabled Devices for the Advancement of Personalized and Transformative Healthcare in South Carolina, ADAPTaward”, NSF Identifier: 000879633, Award Number: 2242812, Award/Fund Agency Code: 4900, Program Element/Reference Code’s (PEC/Congressional District): 193Y00, 075Z/7715/8037/9150/SMET/03, Assistance Listing Number: 47.083,
(August 1, 2023- August 31, 2027) [*2023:9, 2024:16], [**2024:47, **2025:52, 53], 
[**38, 40, 42, 43], [*2025:10], [**2024:37], Techniques of computer vision for image analysis Dr. Konneman Daniel, “Systematics in Coccoloba (Polygonaceae)”, “Deep learning for predicting biofilm patterns from surface-enhanced Raman spectroscopy (SERS)” with Dr. Tzeng, Dr. Anker, Dr. Rao, & Dr. Bhattacharya, Clemson University, South Carolina, USA, Dr. Derrick Swinton, Kean University, Union, New Jersey, USA, “Machine learning for nanoparticle property prediction”, “Comprehensive Approach to Cardio-Renal Health in Lupus: Investigating the Role of Sex, Endothelial Dysfunction, and Social Determinants of Health” with Dr. Jim Oates, at Medical University of South Carolina (MUSC), Charleston, USA. Dr. Shahid Mukhtar, Clemson University, South Carolina, USA, “Artificial intelligence & Big data of genomics Learning Experiences to Careers (ABLE2C)”, Dr. Gao Zhi, Clemson University Subaward, Clemson University https://cecas.clemson.edu/biophotonics/, South Carolina, USA GAIN CRP award [**43, 50],
(Grants for Applications in Industry and Networking Collaborative Research Program): “AI-Enabled Construction of Aligned Collagen Using Two-Photon Techniques”, Dr. Theppatorn & Dr. Desowky Scired: Scientific Research & Development at ClaflinUniversity, Orangeburg, South Carolina, USA. As a principal investigator (PI) and Co-PI, our research is currently (2023-2025) supported by extramural grants (National Science Foundation, The Department of Defense) & internal award (seed) funding ($1M). Teaching-student-advising: https://campuspress.yale.edu/shrikantpawar/teaching-student-advising/ Faculty Profile: https://www.claflin.edu/academics-research/faculty-research/meet-our-faculty/dr.-pawar-shrikant. Research currently funded by Center for Excellence in Teaching and Learning (CETL), Georgia State University (May 1, 2018); Create-X, Georgia Institute of Technology, Atlanta, USA (May 1, 2019); Yale University, New Haven, Connecticut, USA, Rothberg Fund (January 1, 2020); Entrepreneurship Foundation Fund (January 1, 2020), Connecticut, USA; Culinda Technologies, Texas, USA (January 1, 2020); SC Independent Colleges & UniversitiesSCICU Undergraduate Student/Faculty Research Program (February 1, 2022-December 31, 2022); Microsoft for Startups Founders Hub (May 1, 2022); Oracle forResearch; Institutional Development Award (IDeA), Networks of Biomedical Research Excellence (INBRE), Research Education of Teachers SC INRE South Carolina Established Program for Stem Cooperative Research South Carolina Established Program for Stem Cooperative Research (SC EPSCoR), Research Experience for Teachers (RET) program (May 1, 2022- August 31, 2022); Claflin University, Orangeburg, South Carolina, USA, Smart Home, Center of Excellence Seed Grant (May 1, 2022- August 31, 2022); Google HBCU Career Readiness Capacity Grant (May 1, 2023- August 31, 2023); National Science Foundation South Carolina Established Program for Stem Cooperative Research (SC EPSCoR), RII Track-1 Award: AI-enabled Devices for the Advancement of Personalized and Transformative Healthcare in South Carolina; National Science Foundation South Carolina Established Program for Stem Cooperative Research (SC EPSCoR), RII Track-1 Award (August 1, 2023- August 31, 2027), Award Number: 2242812, Award/Fund Agency Code: 4900, Program Element/Reference Code’s (PEC/Congressional District): 193Y00, 075Z/7715/8037/9150/SMET/03, Assistance Listing Number: 47.083,
Grant/award/project title: “AI-enabled Devices for the Advancement of Personalized and Transformative Healthcare in South Carolina (ADAPT)”, GAIN CRP Subaward, Clemson University (Grants for Applications in Industry and Networking Collaborative Research Program (May 1, 2024- August 31, 2025); The Department of Defense (DoD), Army Materiel Command (AMC), HBCU/MI Equipment/Instrumentation grant award (May 1, 2024- August 31, 2025).
January 1, 2020-Present: Research affiliate at Yale University School of Medicine, Department of Genetics, New Haven, United States of America (USA).
January 2023-Present: Georgia Research Consulting (GRC) LLC, Research & Training in STEM Studies, Atlanta: Title: Co-founder. Research and teaching consultant for graduate and undergraduate students. (https://www.saashub.com/georgia-research-consulting-grc-llc-alternatives https://www.f6s.com/profile/5298554 https://www.crunchbase.com/organization/georgia-research-consulting-grc-llc)

January 1, 2024-Present: Independent contractor, Snorkel AI.

January 1, 2020-Present 2020: Yale University, School of Medicine, Department of Genetics, Yale Center for Genome Analysis (YCGA) New Haven, USA. Title: Associate Research Scientist (https://medicine.yale.edu/profile/shrikant_pawar/), current projects in collaboration with Dr. Christian Griñán Ferré, Univesity of Barcelona, Spain, “G9a/GLP transcriptomics”; Dr. Steven. Kleinstein, Yale University, “IMMuno Phenotyping Assessment in a COVID-19 Cohort (IMPACC)”, New Haven, Connecticut, USA, Dr. Ruth Montgomery, Yale University, New Haven, Connecticut, USA, “Single Cell analysis, Cytometry by time of flight (cytOF)”; Dr. Mohammad. Uduman, Dana Farber Harvard, Cambridge, MA, USA, “ICOS gene transcriptomics”; Dr. George. Tegos, Gamma Therapeutics, “Probiotics efficacy”; Dr. Chandrajit. Lahiri, Sunway University, Malaysia, “Cancer Biomarkers”; Dr. Allen. Bale, Dr. Hui. Zhang, DNA Diagnostic Lab at Yale University, New Haven, Connecticut, USA; Dr. Insoo. Kang, “T cell Transcriptomics”; Dr. Kei-Hoi Chung, Linkedimm; and Dr. Leying Guan, “Supervised bayesian factor analysis” at Yale University, New Haven, Connecticut, USA.

January 1, 2020-Present: ChestAi, New Haven, USA. Title: Founding member (https://www.chestai.org/ & https://www.crunchbase.com/person/shrikant-pawar-f817). ChestAi was started with computer scientists and geneticists at Yale university, New Haven, Connecticut, USA with a common motivation of providing a free and open source artificial intelligence (AI) platform for rapid and robust diagnosis of human pathologies identified by radiological examinations. (https://www.ai4hlth.org/product-profiles/ChestAi). (https://www.crunchbase.com/organization/chestai https://www.f6s.com/company/chestai https://tracxn.com/d/companies/chestai/__MB57iTXFVTO2fhlmUZpozcbLBTim3zBYEfD1xFox4mI https://theorg.com/org/chestai https://www.startupranking.com/chestai https://www.sideprojectors.com/project/41226/chestai
https://www.delhionline.in/business/chestai-51996
https://www.freelistingindia.in/listings/chestai https://www.cybo.com/US-biz/yale-aids-program_2K https://www.hotfrog.com/company/da94eb8a85049a717759d381bc7edbf1 https://www.justdial.com/Mumbai/Engineering-Companies/
https://www.manta.com/c/m1wy0z8/chestai https://www.merchantcircle.com/chestai-orangeburg-s https://in.enrollbusiness.com/BusinessProfile/6817822/ChestAi https://www.showmelocal.com/37520422-chestai-columbia https://www.callupcontact.com/b/businessprofile/ChestAI/9426702
https://startupbuffer.com/compare-atlantica-vs-chestai https://www.saashub.com/chestai-alternatives).
ChestAi Demo: https://youtu.be/5BfRpzYU-T8
2January 1, 2019- January 1, 2020: Karyosoft, no-code genomics software and data science augmented
innovations, Indianapolis, Indiana, USA. Title: Genomics Data Scientist, worked on angular, nodejs, flask, AWS, MongoDB, Rabbit-mq, Nginx webserver, Jbrowse techniques for data mining and software visualization.

January 1, 2019-May 1, 2019: Synergy (Plus+) LLC.P.O. Atlanta, Georgia, USA. Title: Data Scientist, worked on web development, statistical and data mining techniques for platform optimization.

January 1, 2018-May 31, 2018: Georgia State University, Department of Biology, Atlanta, USA. Title: Instructor of Record. Next generation sequencing (NGS) analysis in R, BIOL6930 (Introduction to R, Microarrays: gene expression analysis, algorithms, databases, data visualization: heat maps, pie-charts, Venn diagrams.), Introduction to operating server and High Performance Computing cluster. Current projects in collaboration with Dr. Zehava, Eichenbaum, “Biofilm transcriptomics”, Dr. Ritu. Aneja, Dr. Nathan J. Bowen, The Center for Cancer Research and Therapeutic Development (CCRTD) at Clark Atlanta University, Georgia, USA, “Ovarian Biomarkers“, Dr. Charles. Derby, “Chemosensory transcriptomics”, & Dr. Chung-Dar Lu, “Spermine transcriptomics”, Dr. Harrison, “Machine Learning for studying drug resistance in Human immunodeficiency (HIV) virus” and Dr. Weber, “X-ray crystallography in HIV”.

January 1, 2018-May 31, 2018: Georgia State University, Department of Computer Science & Biology, Atlanta, USA. Title: Ahmed T. Abdelal Fellow in Molecular Genetics and Biotechnology.

January 1, 2013-July 31, 2013: Freie Universität Berlin, Berlin, Germany. Title: Center for International Collaborative (CIC) Research Fellow. “Transcriptomic analysis of Nitrogen Metabolism”, Dr.Claus-Peter Witte: https://www.fu-berlin.de/en/sites/brazil/media/csf_stellen/alt/Witte_OpenPosition_2015.pdf
January 1, 2012-August 31, 2012: University of Iowa, Department of Biology, Iowa City, USA. Title: Visiting Research Fellow. Current projects in collaboration with Dr. Claire. Rinehart & Dr. Cheryl. Davis, “Toxoplasma gondi transcriptomics”.

Projects:

You can find all my projects and code repositories at Github following the link: https://github.com/spawar2 Award (Start date- End date).

Important & Interesting project mentions:

  • Android utility app: This project was focused on development of android application with several use case utilities ####https://github.com/spawar2/Android-Utility-App-####[Java: android.content.Context, android.support.test.InstrumentationRegistry, android.support.test.runner.AndroidJUnit4, org.junit.Test, org.junit.runner.RunWith] https://csds.gsu.edu/^^^selected method(actionPerformed, actionPerformed, addOutput, addInput, mouseClicked, evaluateBoolExpr). Date created/updated: December, 9, 2024.
  • A PHP, MySQL based online shopping portal: This project was focused on development of online shopping portal similar to Amazon and ebay ####https://github.com/spawar2/Final_Project_PHP_SQL####https://vimeo.com/356775874?activityReferer=1 [PHP, CSS, HTML, JavaScript: mysql_import.sql] https://csds.gsu.edu/^^^Cascading Style Sheets (CSS), JavaScript, Structured Query Language (SQL) database, Hypertext Preprocessor (PHP) application. selected function(ObjectProperty, reset, login, loginBtn, createBtn, analysis, logOut, invalidLogin, invalidForm, cv2.VideoCapture, imwrite, imread, str, imshow, load, get_user, validate, add_user). Date created/updated: December, 9, 2024. 

https://yalegenomics.shinyapps.io/deployment/?_ga=2.91441946.1803750112.1677552931-1693957918.1677552931

  • Regression-Analysis-Alzheimers-Disease: This project was focused on utilizing machine learning tools for feature classification in Alzheimers ####https://github.com/spawar2/Regression-Alzheimers-Disease#### [R: MASS, car, glm.predict]^^^Regression-Alzheimers-Disease.R: Read variables Subject (PTID) Participant ID RID Participant roster ID Image.Data.ID MRI ID Modality Image type Visit 1=screening scan Acq.Date MRI date DX.bl Diagnosis at baseline EXAMDATE Examination Date AGE Age at baseline PTGENDER Sex PTEDUCAT Years of Education PTETHCAT Ethnicity PTRACCAT Race APOE4 APOE4 genotype MMSE MMSE score for Alzheimers Disease, FIT ORDINAL REGRESSION, perform predictions. selected function(factor, glm.predict, ordinal.fit). Testing: table(testing$V2,pred_test) Prediction_test alive dead alive 214 5 dead 31 11 ((214+11)/(nrow(testing)))*100 [1] 86.2069. Date created/updated: December, 9, 2024. 
  • Machine Learning Classification Pulmonary-Embolism-Master: This project was focused on utilizing machine learning tools for feature classification in Embolism ####https://github.com/spawar2/Pulmonary-Embolism-Master#### [Python: numpy, sklearn, pandas, os, MATPLOTLIB]^^^Pulmonary-Embolism-Master.py: Pulmonary Embolism Variable read Subject (PTID) Participant ID RID Participant roster ID Image.Data.ID MRI ID Modality Image type Visit 1=screening scan Acq.Date MRI date DX.bl Diagnosis at baseline EXAMDATE Examination Date AGE Age at baseline PTGENDER Sex PTEDUCAT Years of Education PTETHCAT Ethnicity PTRACCAT Race Wells Score, 1-hot encoding, Train/Test Split, Logistic Regression, Random Forest, K nearest neighbors KNN, neural nets, prediction Evaluation Metrics: accuracy, precision, sensitivity, specificity, fscore. selected function(LogisticRegression, RandomForestClassifier, KNeighborsClassifier, MLPClassifier, log_clf.fit, log_clf_preds). Date created/updated: December, 9, 2024. 
  • DARTO: Program to identify orthologs for genes: ####https://github.com/spawar2/DARTO#### [Python: os, Bio.Blast, ssl, tkinter, askopenfilename, filedialog], collaboration with Dr. Chandrajit. Lahiri, Sunway University, Malaysia. https://scholar.google.co.in/citations?user=cZaBPOoAAAAJ&hl=en^^^DARTO.py: Read the fasta file. Delta-BLAST 100 hits, BLASTp 1000 hits, RefSeq, tBLASTn, BLASTx, BLASTn as Database. selected function(UploadAction, NCBIWWW.qblast, NCBIXML.parse). Date created/updated: December, 9, 2024. 
  • Neural-Networks-for-Ovarian-Carcinomas: This project was focused on utilizing machine learning tools for feature classification in Ovarian-Carcinomas: Springer Intelligent Sustainable Systems Paper, ####https://github.com/spawar2/Neural-Networks-for-Ovarian-Carcinomas#### 1, 2, 3, [R: curatedOvarianData, tidyverse, boot, plyr, e1071].  Poster Link, Presentation video, PPT^^ ML-Ovarian-Carcinoma.R: Ovarian Microarray data read, robust multi array (RMA) Normalization, neuralnet, Support vector Machine classification, evaluation. selected function(neuralnet, colMedians, do.call, compute). Testing: table(testing$V2,pred_test) Prediction_test alive dead alive 214 5 dead 31 11 ((214+11)/(nrow(testing)))*100 [1] 86.2069. Date created/updated: December, 9, 2024. 

  • Chest-X-ray-Neural-Nets: This project was focused on utilizing CNN’s for X-ray image classification: https://github.com/spawar2/Chest-X-ray-Neural–Nets Demo Poster Link, Product, [*2024:16, 2023:4, 9; 2021: 17, 23], [**23, 29, 30, 37, 42], [*2025:10], [**2024:37], [Python: fastai.vision, torchvision.models, pandas, Path], Date created/updated: December, 9, 2024.  1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9,10,11.12.13. Testing:  Score(160px, FE): 0.878; score(160px, FT): 0.879; score(320px, FE): 0.887. https://github.com/spawar2/CNN-X-ray-images/

  •  

[https://github.com/rushikeshchopaderc https://in.linkedin.com/in/rushikesh-chopade-88470615b https://github.com/SurajK7/ https://in.linkedin.com/in/surajkumar1004 This project in collaboration with **Rushikesh Chopade, Suraj Kumar Undergraduate student: Indian Institute of Technology (IIT), Kharagpur, India. Project: CHEST-AI: AI tool for detection of lung diseases from chest X- ray data (Spring 2021). Springer Computational Vision and Bio-Inspired Computing, Springer Intelligent Sustainable Systems, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, bioRxiv Paper, Paper, Paper, Paper, Paper,  https://link.springer.com/chapter/10.1007/978-981-19-9819-5_49 https://link.springer.com/chapter/10.1007/978-981-19-7660-5_7 https://campuspress.yale.edu/shrikantpawar/files/2024/11/ICCVBIC.pdf https://www.researchsquare.com/article/rs-1129014/latest.pdf https://www.youtube.com/watch?v=Y6skvhHVR2w&ab_channel=ShrikantPawar https://www.youtube.com/watch?v=988lbQ4ekao&ab_channel=ShrikantPawar

https://www.biorxiv.org/content/10.1101/2021.09.21.461307v1.abstract https://dl.acm.org/doi/abs/10.1145/3469213.3469214 http://20.169.253.49:5001/login https://aws.amazon.com/marketplace/seller-profile?id=seller-b6otd3wry7lkk https://bpb-us-w2.wpmucdn.com/campuspress.yale.edu/dist/7/3679/files/2023/10/ChestAi-300×167.png] collaboration with Dr. Anand. Narayanan, Johnson & Johnson, Pennsylvania, USA. https://anandnarayananphd.com/ (National Science Foundation (NSF) South Carolina Established Program for Stem Cooperative Research (SC EPSCoR), Grant/award/project title: “AI-enabled Devices for the Advancement of Personalized and Transformative Healthcare in South Carolina (ADAPT)”, RII Track-1 award funded project, Role: Co-PI/co-PI (Principal Investigator), NSF Identifier: 000879633, Award Number: 2242812, Award/Fund Agency Code: 4900, Program Element/Reference Code’s (PEC/Congressional District): 193Y00, 075Z/7715/8037/9150/SMET/03, Assistance Listing Number: 47.083, (August 1, 2023- August 31, 2027) (Direct costs, Effort=100%, 1.50 person per month release)), Poster, Presentation video, PPT, PPT^^ Date created/updated: December, 9, 2024.

https://yalegenomics.shinyapps.io/myapp/?_ga=2.91441946.1803750112.1677552931-1693957918.1677552931

  • Single-Cell-RNA-Analysis: This project was focused on single cell analysis techniques: https://github.com/spawar2/Single-Cell-RNA-Analysis & https://github.com/spawar2/Single-Cell-Analysis [Python: pandas, numpy, matplotlib.pyplot, string, anndata, defaultdict, OrderedDict, sklearn.preprocessing, TruncatedSVD], collaboration with Dr. Mihika. Kozma, Georgia State University, Atlanta, USA. https://loop.frontiersin.org/people/2548907/overview^^^selected function(getGEO, normalize.quantiles, merge, cluster_analysis, hclust, Kmeans, mas5, rowMeans, randomForest, survfit, chisq.test, pData, rep, colnames, factor, eBayes, decideTests, topTable, read.tree, plot, str, write.tree, library, setwd, ReadAffy, exprs, read.csv, CreateSeuratObject, FeatureScatter, NormalizeData, reduce.dimensions, FindNeighbors, FindClusters, RunTSNE, RunUMAP, use.phate, get.species.cells, make_analysis_from_table, plotCurveHeatmaps, plotPseudoTime, runPseudoTimeDGE, runSlignshot, read.delim, write.table, roundPhylogram, unroot, str, write.tree, RMA, read.table, BGmix, ccParams, TailPP, ccTrace, histTailPP, FDRplotTailPP, histccPred, plotFDR, plotPredChecks, exprSet). Date created/updated: December, 9, 2024.

  • CellLine Dependency Analysis: https://github.com/spawar2/CellLine-Dependency [R: DESeq2]^Pseudocode.Rd: Read cell lines H1299 and HCT116 dependency single cell headcount data, DESeq differential expression analysis, Mean-Average MA Plotting the expression, Kegg enrichment analysis. selected function(DESeqDataSetFromMatrix, results, DESeq, mapIds, sort, enrichKEGG). Date created/updated: December, 9, 2024. 

  • COVID-SwabSeq-Testing-Run: This project was focused on testing Swab-Seq technique on COVID swab tests: https://github.com/spawar2/COVID-SwabSeq-Testing-Run [R: ggbeeswarm, MASS, speedglm, furrr, readxl, magrittr, tidyverse]^ Date created/updated: December, 9, 2024. 

  • Object-Recognition-Python: This project was focused on object recognition using OpenCV: https://github.com/spawar2/Object-Recognition-Python bioRxiv Paper, Demo, Product [Python: numpy, os, urllib, sys, tarfile, tensorflow, zipfile, cv2, csv, time, collections, defaultdict, StringIO, matplotlib, PIL]^^Spotting_Program.py: Data read: OpenCV video capture, Test-Train Split, Neural, plotting, noise removal, Convolution 2D network training, confusion matrix, accuracy, sensitivity, specificity, precision, recall, confusion matrix, log-loss, and area under curve and receiver operating characteristic, AUC-ROC evaluation. open_parking_alert.py, vehicle_detection_main.py: Kivy application development, Mask-RCNN. selected function(cv2.VideoCapture, imwrite, imread, str, imshow, print, draw_bbox, build, MaskRCNN, model.load_weights, VideoCapturemodel.detect, cap.release, cv2.destroyAllWindows). Date created/updated: December, 9, 2024.

  • Quasi-quantum model for potentization: This project was focused on potentization analysis: https://github.com/spawar2/Shrodinger-Equation [R], Git, PPT^^^ Date created/updated: December, 9, 2024.

  • Gene set enrichment analysis for RNA expression data: https://github.com/spawar2/Fold-Change-Comparisons [R: GenomicFeatures, clusterProfiler, enrichplot, ggplot2]^^^selected function(getGEO, normalize.quantiles, merge, cluster_analysis, hclust, Kmeans, mas5, rowMeans, randomForest, survfit, chisq.test, pData, rep, colnames, factor, eBayes, decideTests, topTable, read.tree, plot, str, write.tree, library, setwd, ReadAffy, exprs, read.csv, read.delim, write.table, roundPhylogram, unroot, str, write.tree, RMA, read.table, BGmix, ccParams, TailPP, ccTrace, histTailPP, FDRplotTailPP, histccPred, plotFDR, plotPredChecks, exprSet). Date created/updated: December, 9, 2024.

  • Kivy app interface development in R: https://github.com/spawar2/Kivy-GUI-R [Python: kivy.app, kivy.lang, Builder, Screen, ObjectProperty, Popup, Label, DataBase]^ Date created/updated: December, 9, 2024.

    main.py: Kivy User Interface. database.py: backend. user.py: credentials.

    selected function(ObjectProperty, reset, login, loginBtn, createBtn, analysis, logOut, invalidLogin, invalidForm, cv2.VideoCapture, imwrite, imread, str, imshow, load, get_user, validate, add_user). Date created/updated: December, 9, 2024.

  • Structural–variant-Detection tool: https://github.com/spawar2/Structural-variant-Detection [R]^Plot_SVs.R: Plotting different structural variants SV’s for different coverages of Pacbio data, Creating objects with different coverages, Finding the list of common SV’s from all uniques throughout. selected function(merge, cluster_analysis, hclust, cutree, rbind, heatmap.2, setwd, read.csv, library, set.seed, sample.split, subset, na.omit, scale, svm, predict, table, plot). Date created/updated: December, 9, 2024. 

  • Program to Count-relative-frequency-of-amino-acids: https://github.com/spawar2/Count-relative-frequency-of-amino-acids [Python: itertools, product, combinations, Counter]^^Pawar-assignment.py.txt: get codon for amino acids, create translation_table, prepare the dictionary of translation_table codons, query_codons, prepare dictionary of counts, calculation of frequency, print results. selected function(expanded_code, truncate_list_of_amino_acid, defaultdict, get_codon_for_amino_acids, truncate_list_of_amino_acids). Date created/updated: December, 9, 2024. 

  • Text to voice conversion application: https://github.com/spawar2/Text-to-Voice-Application [Python: os, numpy, shlex, subprocess, sys, wave, deepspeech, Model, printVersions, timeit]^^ Date created/updated: December, 9, 2024.   

  • CT brain hemorrhage training: https://github.com/spawar2/CNN_Training [Python: matplotlib.pyplot, torch, time, numpy, collections, OrderedDict, torch.autograd, PIL, lr_scheduler, copy, json, os]^^ct_scan_brain_hemorrhage.py: Computerized Tomography (CT) scan data read, Test-Train Split, Neural, plotting, noise removal, Convolution 2D network training, confusion matrix, accuracy, sensitivity, specificity, precision, recall, confusion matrix, log-loss, and area under curve and receiver operating characteristic, AUC-ROC evaluation. selected function(pd.read_csv, plt.figure, plt.Circle, plt.pie,plot_hist, add_gaussian_noise, Model, model.fit, evaluate_model, network, confusion_matrix, model.predict, model.load_weights, model.compile, model.add, model.summary, plot_confusion_matrix, Sequential). Testing: Score(160px, FE): 0.878; score(160px, FT): 0.879; score(320px, FE): 0.887. A hemorrhage is bleeding from a damaged blood vessel. Many things can cause bleeding inside and outside of your body. Types of hemorrhages range from minor (like a bruise) to major (like bleeding in your brain). Date created/updated: December, 9, 2024. 

  • Evaluating performance of regression and classification models with prognostic markers in lung carcinomas: https://github.com/spawar2/Regression-Lung-Carcinoma^^1, 2, 3, 4, 

    Paper, [R: randomForest, caret], collaboration with Dr. Chandrajit. Lahiri, Sunway University, Malaysia. https://scholar.google.co.in/citations?user=cZaBPOoAAAAJ&hl=en

    er   Presentation video, PPT, Date created/updated: December, 9, 2024.

    Springer Bioinformatics and Biomedical Engineering Paper. Regression.R: Lung cancer Microarray data read, robust multi array (RMA) Normalization, LOGISTIC REGRESSION, Support vector machine, confusion matrix, accuracy, sensitivity, specificity, precision, recall, confusion matrix, log-loss, and area under curve and receiver operating characteristic, AUC-ROC. selected function(neuralnet, colMedians, do.call, compute, randomForest, predict, confusionMatrix, svm, ggplot, predict, table, factor, glm, wald.test, as.numeric, sum). Testing: table(testing$V2,pred_test) Prediction_test alive dead alive 214 5 dead 31 11 ((214+11)/(nrow(testing)))*100 [1] 86.2069.   

  • Hemorhage–Detection-CT-Scan: https://github.com/spawar2/Hemorhage-Detection-CT-Scan [**33], Poster Presentation, Springe,r [Python: numpy, pandas, pydicom, matplotlib.pyplot, math, cv2, tensorflow, keras]. Testing Accuracy: 0.98. Date created/updated: December, 9, 2024.

[https://github.com/CoolSubash https://np.linkedin.com/in/subash-neupane-aa07ba228?trk=public_profile_browsemap This project in collaboration with **Subash Neupane+π, (Claflin University, Orangeburg, South Carolina, USA. Seed award funded project Role: PI, (Direct costs, Effort=100%)) (May 1, 2023- August 31, 2023), Undergraduate student: Claflin University, Orangeburg, South Carolina, USA. (Fall 2023). Utilization of Machine Learning Techniques for Aiding Detection of Ischemic Stroke Lesion, Infarct Volumes, and Small-artery Occlusion https://www.claflin-computation.com/_files/ugd/81dd80_e12daf8e87c348c5a9347af693993739.pdf] Project: https://campuspress.yale.edu/shrikantpawar/files/2024/04/Seed-Report-2023-d26fc72513e269e3.docx^^inceptionv3-keras-pawar.ipynb, intracranial-hemorrhage-pawar.ipynb, keras-efficientnet-pawar.ipynb: Computerized Tomography (CT) Brain Hemorrhage scan Data read, Test-Train Split, Neural, plotting, noise removal, ImageNet Convolution 2D network training, confusion matrix, accuracy, sensitivity, specificity, precision, recall, confusion matrix, log-loss, and area under curve and receiver operating characteristic, AUC-ROC evaluation. function(cv2.VideoCapture, imwrite, imread, str, imshow, print, draw_bbox, build, MaskRCNN, model.load_weights, VideoCapturemodel.detect, cap.release, cv2.destroyAllWindows) selected function(pd.read_csv, ImageDataGenerator, tf.keras.Sequential , model.evaluate_generator, cv2.imread, cv2.cvtColor, cv2.resize, tf.keras.models.load_model, np.argmax, cv2.ellipse). A stroke happens when there is a loss of blood flow to part of the brain. Your brain cells cannot get the oxygen and nutrients they need from blood, and they start to die within a few minutes. This can cause lasting brain damage, long-term disability, or even death. 

  • Anovos feature engineering process to increase efficiency tool contributor:  https://github.com/spawar2/Anovos-Contributor-User^ Date created/updated: December, 9, 2024. 

  • Techniques of brain segmentation from CT scan: https://github.com/spawar2/Image_Segmentation [Python: pydicom, numpy, cv2, os, math, pylab, matplotlib, scipy, ndimage, skimage, morphology]^^ct_scan_brain_segmentation.py: Computerized Tomography (CT) brain hemorrhage scan Data read, Test-Train Split, Neural, plotting, noise removal, image transformation: Padding, Cropping, Masking. inceptionv3-keras-segmented-pawar.ipynb, inceptionv3-keras-unsegmented-pawar.ipynb: Convolution 2D network training, confusion matrix, accuracy, sensitivity, specificity, precision, recall, confusion matrix, log-loss, and area under curve and receiver operating characteristic, AUC-ROC evaluation. selected function(cv2.VideoCapture, imwrite, imread, str, imshow, print, draw_bbox, build, MaskRCNN, model.load_weights, VideoCapturemodel.detect, cap.release, cv2.destroyAllWindows) selected function(pd.read_csv, ImageDataGenerator, tf.keras.Sequential , model.evaluate_generator, cv2.imread, cv2.cvtColor, cv2.resize, tf.keras.models.load_model, np.argmax, cv2.ellipse). Date created/updated: December, 9, 2024. 

  • Stroke risk stratification with neural nets: [*2024:9],[**2024:36], https://www.youtube.com/watch?v=PtjHqf4xlbI&ab_channel=ShrikantPawar  https://github.com/spawar2/Neural-Networks-Stroke Springer Intelligent Sustainable Systems Paper, 1, 2, 3, 4, 5, [R: neuralnet], Presentation video, PPT, (Claflin University  Orangeburg, South Carolina, USA, seed funded project), Role: PI, (Direct costs, Effort=100%) (May 1, 2023- August 31, 2023)^^Neural-Networks-Stroke.R: Stroke variables data read, Transform the data using a max-min normalization technique, Data Test-Train Split, Neural, neuralnet training, Evaluation Metrics: accuracy, precision, sensitivity, specificity, fscore for Hemorrhagic, Ischemic, One sided face, One sided arm, One sided leg, Asymmetry, Not ambulatory, Not able to speak, Visual disturbances, Abnormal sensation, Mental change, and Not able to grasp outcome, Visualization. selected function(neuralnet, colMedians, do.call, compute, randomForest, predict, confusionMatrix, svm, ggplot, predict, table, factor, glm, wald.test, as.numeric, sum, maxmindf). Testing:  Sensitivity = 0.946564885496183 Specificity = 0.745901639344262 fscore = 0.934673366834171 Precision = 0.923076923076923 Accuracy = 0.899029126213592. Date created/updated: December, 9, 2024. 

  • System-Level-Programming: https://github.com/spawar2/System-Level-Programming, https://csds.gsu.edu/^^^test.c, test2.c, stat.c: number of white spaces, Uppercase Letters, Lowercase Letters, Number of words, Number of spaces, Number of vowels, Number of digits, Number of special characters. selected method(count). Date created/updated: December, 9, 2024. 

  • Data-Structures: https://github.com/spawar2/Data-Structures, https://csds.gsu.edu/^^^Wordcount.java [java.util., java.io.].: Counts the amount of words in the file. A word can end with a — space/tab, EOLN character or a punctuation mark (which will be part of the word). Count the amount of lines in the file. Count the amount of alphanumeric characters in the file. Count the number of sentences in the file. Count the amount of vowels in the file – only a, e, i, o, u (upper & lower case) are vowels. Count the amount of punctuations in the file. it outputs a output file with all the above information. Selected method (Record_System_tabs, getconnection, show_users_in_jtable, jButton5ActionPerformed, jComboBox1ActionPerformed, jTable1MouseClicked, users). Date created/updated: December, 9, 2024. 
  • CS-Introduction: https://github.com/spawar2/CS-Introduction, https://csds.gsu.edu/^^^selected method(GradesAverage). Date created/updated: December, 9, 2024. 
  • Advanced-Graphic-Algorithms: https://github.com/spawar2/Advanced-Graphic-Algorithms, https://csds.gsu.edu/^^^selected method(processUsingCpu, rgbaToGreyscaleCpu,clSetKernelArg). Date created/updated: December, 9, 2024. 
  • Fundamentals of Bioinformatics: https://github.com/spawar2/Bioinformatics-scripts, https://csds.gsu.edu/^^^selected function(dna_to_protein, palin, multiply_by_words, codons.dna_to_protein). Date created/updated: December, 9, 2024. 
  • Nano-particles property prediction with random forests: https://github.com/spawar2/RF-ENP [R Shiny: MissForest, randomForest, caret, UI, Server], collaboration with Dr. Swinton, Kean University. ENP-RF-Pawar.Rd: Engineered Nano Particles (ENP) properties, Data read, miss forest imputation for missing values, random forest, confusion matrix, accuracy, sensitivity, specificity, precision, recall, confusion matrix, log-loss, and area under curve and receiver operating characteristic, AUC-ROC evaluation. server.R, UI.R: User interface and backend for R Shiny application. selected function(hcmap, fluidPage, renderHighchart, shinyApp, missForest, randomForest, predict, confusionMatrix). https://www.kean.edu/directory/derrick-swinton https://yalegenomics.shinyapps.io/appenp/?_ga=2.91441946.1803750112.1677552931-1693957918.1677552931^^ Testing Accuracy : 1, 95% CI : (0.5407, 1), No Information Rate : 0.6667, P-Value [Acc > NIR] : 0.08779, Kappa : 1, Sensitivity : 1.0000, Specificity : 1.0000, Pos Pred Value : 1.0000, Neg Pred Value : 1.0000, Prevalence : 0.3333, Detection Rate : 0.3333, Detection Prevalence : 0.3333, Balanced Accuracy : 1.0000, Date created/updated: December, 9, 2024. 

https://yalegenomics.shinyapps.io/app-smart-home/

SC Independent Colleges & Universities (SCICU): https://scicu.org/events/scicu-undergraduate-student-faculty-research-symposium-4/ [https://github.com/eniolla https://www.linkedin.com/in/priscilla-fatokun-35007119a https://github.com/mayor90/thesis Thesis video presentation: https://youtu.be/NUPr-kXKCaU https://campuspress.yale.edu/shrikantpawar/files/2023/12/SCICU-research-poster.pptx This project in collaboration with **Mr. Owalabi Oluwamayowa+π, (South Carolina Independent Colleges & Universities SCICU award funded project Role: PI, (Direct costs, Effort=100%)),  **Priscilla E. Fatokun+π, (South Carolina Independent Colleges & Universities SCICU award funded project Role: PI, (Direct costs, Effort=100%)), (February 1, 2023-December 31, 2023), Undergraduate student: Claflin University, Orangeburg, South Carolina, USA. (Fall 2023). Project: SMART-HOME proposal “collection and processing of health-care data for African-American subjects from wrist wearable devices. https://campuspress.yale.edu/shrikantpawar/files/2023/12/SCICU-research-poster.pptx https://campuspress.yale.edu/shrikantpawar/files/2024/02/Priscilla-Research-Presentation-0b920a0c624e2982.pptx] Project: https://www.claflin-computation.com/_files/ugd/81dd80_88f5decdd4c44ce497f7f2f71018c63b.docx?dn=Building%20a%20Responsive%20SmartHome.docx PPT: https://www.claflin-computation.com/_files/ugd/81dd80_65cf61cfe8b8429fae9cfcb31f099f15.pptx?dn=Building%20a%20Responsive%20Smart%20Home.pptx Project: https://www.claflin-computation.com/_files/ugd/81dd80_5add3a1670ff4c68a3cb307ddbe7e811.docx?dn=Priscilla%20Fatokun%27s%20Thesis.docx PPT: https://www.claflin-computation.com/_files/ugd/81dd80_9ea49363c6704e198ccbd724c57a3fdc.pptx?dn=Priscilla%20Fatokun%27s%20Presentation.pptx Date created/updated: December, 9, 2024.

^^Claflin University, School of Natural Sciences and Mathematics, Department of Computer Science and Biology, Orangeburg, South Carolina, United States of America (USA).

^Yale University, School of Medicine, Department of Genetics, Yale Center for Genome Analysis (YCGA), Connecticut, New Haven, USA.

^^^Georgia State University, College of Arts and Sciences, Department of Computer Science and Biology, Atlanta, USA.

^^^^Western Kentucky University, Department of Biology, Bowling Green, Kentucky, USA.

π: Classes taught: CSCI/HNTH391/392