About
Holding a Ph.D. in Statistics from the University of South Florida, I am a passionate educator with nearly 15 years of experience inspiring students and bridging the gap between theoretical concepts and real-world applications. My journey in academia and research reflects a deep commitment to statistical excellence, creative problem-solving, and meaningful contribution to scientific knowledge.
I bring a unique blend of analytical rigor and creative insight to research design and data interpretation. Over the years, I have conducted extensive statistical research across diverse domains, including clinical and health-related data involving breast cancer, colon cancer, Alzheimer’s disease, and measles, among others.
As a qualified Mathematician and Statistician and a certified online educator, I am dedicated to lifelong learning and collaboration. With proven leadership skills and a keen eye for detail, I continue to contribute to both industry and academia while remaining open to new ideas and perspectives in the evolving world of data and statistical science.
Skills
| Statistics | Linear and Nonlinear Modeling, Data Analysis, Survival Analysis and Modeling, Multivariate Statistics, Non-parametric Methods, Categorical Analysis |
| Machine Learning | Decision Trees, Artificial Neural Networks, Deep Learning, Support Vector Machines (SVMs) |
| Statistical Software | SAS 9.4, SAS Enterprise Miner, SPSS, RPACT, nQUERY, MS Excel, MS Azure, R (intermediate), STATISTIX |
| Other Software | MS Office (Word, Excel, PowerPoint), HTML5, Acrobat |
Professional Profile
Expertise & Skills
- Experienced in RPACT, Estimand methodologies, and peer training in statistical methods.
- Expert resource in treatment switching methods in Oncology (RPSFT, Two-Stage approaches).
- Strong knowledge of CDISC standards (SDTM, ADaM); contributed to submission deliverables (CSR, SCE, SCS, CO).
- Advanced in statistical tools: SAS/Base, SAS/Stat, SAS Procedures, SAS Graphs.
- Applied machine learning techniques for complex data analysis projects.
- Outstanding leadership, communication, and presentation skills; adept at learning new technologies quickly.
Academic Contributions
- Author: STA 2023 Introductory Statistics Textbook, MacMillan Learning (ISBN: 9781319362997), 2019.
- Co-author: Artificial Neural Networks Textbook, Dominion Publications, 2005.
- Organizer: International Workshop on Basic Statistics using SPSS® and SAS®, India, 2019.
- Certified Online Educator: University of South Florida.
- Teaching Experience: 16+ years; known for connecting theory to real-world applications.
- Mentorship: Hired/trained statistics student assistants; advised 10+ undergraduate theses.
- Editorial Assistant: Stochastic Analysis and Applications (Taylor & Francis); Editor-in-Chief: Dr. G.S. Ladde.
Work Experience in Pharma
Principal Biostatistician, Novartis Healthcare Pvt. Ltd – Hyderabad, India
Dec 2022 – Present
- Managed statistical tasks for oncology trials with focus on quality, timelines, and peer collaboration.
- Supported protocol development and created Statistical Analysis Plans (SAPs) and TFL shells.
- Led global Estimand Training sessions to improve trial design rigor.
- Planned and executed exploratory analyses for posters/publications in Immunology.
- Reviewed submission documents and responded to Health Authority inquiries with statistical clarity.
- Acted as a liaison between statisticians and non-statisticians, explaining complex concepts clearly.
- Led statistical team discussions and promoted knowledge sharing across global teams.
My Research and Publications
Academic Publications
Research Publications
Fast Forest Quantile Regression Approach in Predicting Breast Cancer Tumor Sizes
2025
Mudunuru, V.R.
(In preparation)
Survival Analysis of Colon Cancer Data using Quantile Regression
2023
Vidya Bhargavi M., Veeramachaneni S., Mudunuru V.R.
Research Journal of Pharmacy and Technology, 16(3), 0000-0000
A Comparison of Artificial Neural Network and Decision Trees with Logistic Regression as Classification Models for Breast Cancer Survival
2020
Mudunuru, V. R., & Skrzypek, L. A.
International Journal of Mathematical, Engineering and Management Sciences, 5(6), 1170–1190
Colon Cancer Stage Classification Using Decision Trees
2020
Vidya Bhargavi M., Mudunuru V.R., Veeramachaneni S.
In: Raju K., Senkerik R., Lanka S., Rajagopal V. (eds) Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 1079. Springer, Singapore.
Prediction of Remaining Useful Life of an End Mill Using ANSYS
2020
Mudunuru V.R., Komarraju S.
In: Raju K., Senkerik R., Lanka S., Rajagopal V. (eds) Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 1079. Springer, Singapore.
Zero Factorial
2017
Mudunuru V., Vidya Bhargavi, Ravindharan Ethiraj
Scholars Journal of Physics, Mathematics and Statistics, 2017.
History of Breast Cancer - A Quick Review
2017
Mudunuru V., Sampath Reddy K., Vidya Bhargavi M.
International Journal of Current Research and Review, Vol 9, Issue 15, 2017.
Comparison of Activation Functions in Multilayer Neural Networks for Stage Classification in Breast Cancer
2016
Mudunuru V.
Neural, Parallel, and Scientific Computations, 36-2
Fall and Rise of Measles
2016
Rishi Kalia, Ravi Kalia, Raquib Zaman, Venkateswara Mudunuru
Journal of Applied Sciences, 16: 395-405. DOI: 10.3923/jas.2016.395.405
Statistical Analysis on Breast Cancer Tumor Sizes
2015
Mudunuru V., Chris Tsokos
Research Journal of Recent Sciences.
Comparison of Activation Functions in Multilayer Neural Networks for Stage Classification in Breast Cancer
2014
Mudunuru V., Vidya Bhargavi M.
In the Proceedings of International Conference on Mathematical Sciences: Chennai, India, Elsevier (pp.145–149).
International Conference Presentations
Fast Forest Quantile Regression Approach in Predicting Breast Cancer Tumor Sizes.
2021
Joint Mathematics Meetings AMS Special Session JMM 2021 – Virtual Meeting, USA
Colon Cancer Survival Analysis with Quantile Regression.
2021
Joint Mathematics Meetings AMS Special Session JMM 2021 – Virtual Meeting, USA
Colon Cancer Stage Classification using Decision Trees
2019
International Conference on Data Engineering and Communication Technology Stanley College of Engineering and Technology for Women, Hyderabad, India.
Prediction of Remaining Useful Life of an End-mill using ANSYS
2019
International Conference on Data Engineering and Communication Technology Stanley College of Engineering and Technology for Women, Hyderabad, India.
Statistical Outlier Detection and Treatment for the Breast Cancer Data
2016
International Conference on Applications of Mathematics to Nonlinear Sciences, Kathmandu, Nepal.
Comparison of Activation Functions in Multilayer Neural Networks for Stage Classification in Breast Cancer
2016
International Conference on Mathematical Sciences, Chennai, India.
Comparative Analysis of Artificial Neural Networks and Logistic Regression to Predict Survival of Breast Cancer Patients
2013
International Conference on Recent Advances in Mathematical Sciences and Applications (RAMSA), Visakhapatnam, India.
Sampling Techniques as Applied to Cancer Data
2013
Conference on Nonlinear Systems and Summer School-2013, Katmandu, Nepal.
Parametric and Non-Parametric analysis on Colon Cancer Data
2013
ENAR 2013 International Conference, Orlando.
Parametric Analysis of Breast Cancer
2011
Sixth International Conference on Dynamic Systems and Applications.
The Log-Logistic distribution as applied to the average tumor size of Colon cancer
2010
Fourth International Conference on Neural, Parallel & Scientific Computations.
Colorectal Cancer data Analysis
2009
American Cancer Society conference conducted by Department of Mathematics and Statistics, USF.
International Invited Presentations
| Year | Title | Event | Location |
|---|---|---|---|
| 2025 | Statistical Analysis in Quantum Computing Applications | Faculty Development Program | Stanley College of Engineering and Technology for Women, Hyderabad, India |
| 2022 | Application of Gradient Boosting Techniques for Breast Cancer Stage Classification | AMS Special Session, Joint Mathematics Meetings (JMM) | Virtual, Seattle, USA |
| 2022 | A Comparison of Multilayer Neural Networks and Decision Trees for Stage Classification of Colon Cancer Data | AMS Special Session, Joint Mathematics Meetings (JMM) | Virtual, Seattle, USA |
| 2021 | Fast Forest Quantile Regression Approach in Predicting Breast Cancer Tumor Sizes | AMS Special Session, Joint Mathematics Meetings (JMM) | Virtual Meeting, USA |
| 2021 | Colon Cancer Survival Analysis with Quantile Regression | AMS Special Session, Joint Mathematics Meetings (JMM) | Virtual Meeting, USA |
| 2018 | Mathematics is the Future | School Seminar | Ravindra Bharati Group of Schools, Hyderabad, India |
| 2017 | ‘Excel’lent Functions | Actuarial Sciences Organization | University of South Florida, Tampa, Florida, USA |
| 2016 | Engineering Mathematics or Mathematics in Engineering? | Research and Development Cell – Sigma | Stanley College of Engineering and Technology for Women, Hyderabad, India |
| 2015 | Estimating Breast Cancer Tumor Sizes using ANNs and Decision Trees | Conference on Awareness in Women in Modern India | Stanley College of Engineering and Technology for Women, Hyderabad, India |
Professional Memberships
- Member, Council on Undergraduate Research, USA
- Life Member, Indian Mathematical Society
- Life Member, International Indian Statistical Association
- Life Member, Indian Society for Probability and Statistics
- Member, ASA – American Statistical Association, USA
- Member, Statistics Club @ University of South Florida
- Member, Pi Mu Epsilon, Florida Chapter, USF, Tampa
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Contact
Email:
vnv3057@gmail.com
Call:
+91-8712729057