BSAC

Vision

My Electrical Engineering-driven research lab, Biological System Analysis and Control (BSAC), bridges the gap between Bioinformatics, Systems Biology, and Embedded Instrumentation. We leverage intelligent system analysis to engineer closed-loop strategies that transform multi-modal biological data into precise interventions to regulate dynamic disease states and advance precision medicine. 

Framework

Our research projects follow a rigorous Sense-Think-Act pipeline.

Sense: Biological Signals  ->  Think: Model & Analyse the System Dynamics  ->  Act: Control Efficiently

Using high-precision instruments, we capture physiological signals with maximum efficiency (Observation). We then process these signals using intelligent system analysis models to study the state of disease or health (System Identification). Beyond observation and analysis, we focus on developing closed-loop feedback control systems (Regulation). This holistic approach transforms passive biomedical tools into adaptive, intelligent systems that can dynamically adjust to a patient’s unique physiological state, ultimately advancing the goal of precision medicine.

Journal Publications

• Vundavilli, H., Datta, A., Sima, C., Hua, J., Lopes, R., & Bittner, M. (2018). In silico design and experimental validation of combination therapy for pancreatic cancer. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(3), 1010–1018. (Journal Indexing: WoS-SCIE-Q1; Impact factor: 3.4) 

• Vundavilli, H., Datta, A., Sima, C., Hua, J., Lopes, R., & Bittner, M. (2019). Bayesian inference identifies combination therapeutic targets in breast cancer. IEEE Transactions on Biomedical Engineering, 66(9), 2684–2692. (Journal Indexing: WoS-SCIE-Q2; Impact factor: 4.5)

• Vundavilli, H., Datta, A., Sima, C., Hua, J., Lopes, R., & Bittner, M. (2019). Cryptotanshinone induces cell death in lung cancer by targeting aberrant feedback loops. IEEE Journal of Biomedical and Health Informatics, 24(8), 2430–2438. (Journal Indexing: WoS-SCIE-Q1; Impact factor: 6.8) 

• Vundavilli, H., Datta, A., Sima, C., Hua, J., Lopes, R., & Bittner, M. (2021). Targeting oncogenic mutations in colorectal cancer using cryptotanshinone. PLoS One, 16(2), e0247190. (Journal Indexing: WoS-SCIE-Q2; Impact factor: 2.6) 

• Vundavilli, H., Tripathi, L. P., Datta, A., & Mizuguchi, K. (2021). Network modeling and inference of peroxisome proliferator-activated receptor pathway in high fat diet-linked obesity. Journal of Theoretical Biology, 519, 110647. (Journal Indexing: WoS-SCIE-Q2; Impact factor: 2.0) 

• Vundavilli, H., Datta, A., Sima, C., Hua, J., Lopes, R., Bittner, M., Miller, T., & Wilson-Robles, H. M. (2022). Anti-tumor effects of cryptotanshinone (C19H20O3) in human osteosarcoma cell lines. Biomedicine & Pharmacotherapy, 150, 112993. (Journal Indexing: WoS-SCIE-Q1; Impact factor: 7.5) 

• Gupta, S., Vundavilli, H., Osorio, R. S. A., Itoh, M. N., Mohsen, A., Datta, A., Mizuguchi, K., & Tripathi, L. P. (2022). Integrative network modeling highlights the crucial roles of Rho-GDI signaling pathway in the progression of non-small cell lung cancer. IEEE Journal of Biomedical and Health Informatics, 26(9), 4785–4793. (Journal Indexing: WoS-SCIE-Q1; Impact factor: 6.8) 

• Lahiri, A., Vundavilli, H., Mondal, M., Bhattacharjee, P., Decker, B., Del Priore, G., Reeves, N. P., & Datta, A. (2023). Drug target identification in triple negative breast cancer stem cell pathways: A computational study of gene regulatory pathways using Boolean networks. IEEE Access, 11, 56672–56690. (Journal Indexing: WoS-SCIE-Q2; Impact factor: 3.6) 

• Aparicio, A. M., Tidwell, R. S., Yadav, S. S., Chen, J.-S., Zhang, M., Liu, J., Guo, S., Pilié, P. G., Yu, Y., Song, X., & others. (2024). A Modular Trial of Androgen Signaling Inhibitor Combinations Testing a Risk-Adapted Strategy in Patients with Metastatic Castration–Resistant Prostate Cancer. Clinical Cancer Research, 30(13), 2751–2763. (Journal Indexing: WoS-SCIE-Q1; Impact factor: 10.2)

• Mondal, M., Lahiri, A., Vundavilli, H., Del Priore, G., Reeves, N. P., & Datta, A. (2024). A Computational Study of Efficient Combinations of FDA-approved drugs and dietary supplements in Endometrial Cancer. IEEE Access, 12, 190746–190759. (Journal Indexing: WoS-SCIE-Q2; Impact factor: 3.6) 

• Dhanka, S., Kumar, A., Sharma, A., Vundavilli, H., Maini, S., & Rajasekar, E. (2025). Advances in machine learning and deep learning for hormonal disorder diagnosis: an exhaustive review on PCOS, thyroid, and optimization techniques. Archives of Computational Methods in Engineering, 1–45. (Journal Indexing: WoS-SCIE-Q1; Impact factor: 12.1) 

• Dhanka, S., Sharma, A., Kumar, A., Maini, S., & Vundavilli, H. (2026). Advancements in hybrid machine learning models for biomedical disease classification using integration of hyperparameter-tuning and feature selection methodologies: A comprehensive review. Archives of Computational Methods in Engineering, 33(1), 289–324. (Journal Indexing: WoS-SCIE-Q1; Impact factor: 12.1)

Conference Publications & Abstracts

• Vundavilli, H., Tumiati, M., Hautaniemi, S., Datta, A., & Kauppi, L. (2022). Image Processing Pipeline to Compute Homologous Recombination Score. Proceedings of the 12th International Conference on Biomedical Engineering and Technology, 51–56. 

• Mondal, M., Lahiri, A., Vundavilli, H., Del Priore, G., Reeves, P., & Datta, A. (2023). Combination supplements for endometrial cancer. 2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE), 238–243.

• Viscuse, P. V., Tidwell, R., Liu, J., Guo, S., Vundavilli, H., Zhang, M., Subudhi, S. K., Zurita, A. J., Corn, P. G., Tu, S.-M., & others. (2022). DynAMo: A dynamic allocation modular sequential trial of approved and promising therapies in men with metastatic CRPC. American Society of Clinical Oncology.  

• Logotheti, S., Vundavilli, H., Papadaki, E., Zhao, Y., Estecio, M. R., Soundararajan, R., Shepherd, P., Dong, J., Hoang, A., Guo, S., & others. (2023). Candidate measures of lineage plasticity in aggressive phenotypes of prostate cancer. Cancer Research, 83(7_Supplement), 142–142.

Research Word cloud