Vijaya B. Kolachalama, PhD, FAHA

Assistant Professor, Medicine

Vijaya Kolachalama
617.358.7253
72 East Concord Street, Evans 636

Biography

Phenotyping neurodegeneration: We build machine learning frameworks to process multimodal data and identify specific signatures of neurodegeneration. We have experience in dealing with large data cohorts such as the Framingham Heart Study and established several computational pipelines to efficiently process volumetric images of the brain, neuropathology and other modes of data and use them for further analysis. We collaborate with a diverse team of neurologists, neuropsychologists, neuropathologists and neuroradiologists to validate our computational findings. 

Digital pathology: We develop novel computational frameworks based on deep learning to assist the pathologist. Our current application areas include kidney disease and lung cancer. 

Devices, drugs and interfaces: We use a multidisciplinary approach to quantify device-artery interactions and the interfacial mechanisms driving the performance of endovascular devices. Our studies have explained how physiologic factors modulate spatiotemporal arterial distribution patterns in drug-eluting devices as a function of intrinsic device design, relative device position and pulsatile nature of blood flow. We have extended models simulating idealized settings of physiology to real-world issues and further examined arterial response that varies due to procedural settings, device composition, wall ultrastructure and disease, changes within complex vascular anatomies, vascular injury and the mode of drug delivery.

Other Positions

  • Member, Whitaker Cardiovascular Institute, Boston University
  • Member, Evans Center for Interdisciplinary Biomedical Research, Boston University
  • Founding Assistant Professor, Computing & Data Sciences Administration, Boston University School of Medicine, Graduate Medical Sciences

Education

  • Indian Institute of Technology, Kharagpur, India, BS
  • University of Southampton, UK, PhD

Classes Taught

  • GMSMS650

Publications

  • Published on 2/28/2022

    De Anda-Duran I, Alonso CF, Libon DJ, Carmichael OT, Kolachalama VB, Suglia SF, Au R, Bazzano LA. Carotid Intima-media Thickness and Midlife Cognitive Function: Impact of Race and Social Disparities in the Bogalusa Heart Study. Neurology. 2022 Feb 28. PMID: 35228334.

    Read at: PubMed
  • Published on 1/13/2022

    Au R, Kolachalama VB, Paschalidis IC. Redefining and Validating Digital Biomarkers as Fluid, Dynamic Multi-Dimensional Digital Signal Patterns. Front Digit Health. 2021; 3:751629. PMID: 35146485.

    Read at: PubMed
  • Published on 1/4/2022

    Romano MF, Kolachalama VB. Deep learning for subtyping the Alzheimer's disease spectrum. Trends Mol Med. 2022 02; 28(2):81-83. PMID: 34996710.

    Read at: PubMed
  • Published on 10/29/2021

    Chang GH, Park LK, Le NA, Jhun RS, Surendran T, Lai J, Seo H, Promchotichai N, Yoon G, Scalera J, Capellini TD, Felson DT, Kolachalama VB. Subchondral Bone Length in Knee Osteoarthritis: A Deep Learning-Derived Imaging Measure and Its Association With Radiographic and Clinical Outcomes. Arthritis Rheumatol. 2021 12; 73(12):2240-2248. PMID: 33973737.

    Read at: PubMed
  • Published on 8/31/2021

    Xue C, Karjadi C, Paschalidis IC, Au R, Kolachalama VB. Detection of dementia on voice recordings using deep learning: a Framingham Heart Study. Alzheimers Res Ther. 2021 08 31; 13(1):146. PMID: 34465384.

    Read at: PubMed
  • Published on 7/28/2021

    Zhang JD, Baker MJ, Liu Z, Kabir KMM, Kolachalama VB, Yates DH, Donald WA. Medical diagnosis at the point-of-care by portable high-field asymmetric waveform ion mobility spectrometry: a systematic review and meta-analysis. J Breath Res. 2021 07 28; 15(4). PMID: 34252887.

    Read at: PubMed
  • Published on 7/1/2021

    Xu D, Zhou F, Sun W, Chen L, Lan L, Li H, Xiao F, Li Y, Kolachalama VB, Li Y, Wang X, Xu H. Relationship Between Serum Severe Acute Respiratory Syndrome Coronavirus 2 Nucleic Acid and Organ Damage in Coronavirus 2019 Patients: A Cohort Study. Clin Infect Dis. 2021 07 01; 73(1):68-75. PMID: 32720678.

    Read at: PubMed
  • Published on 6/27/2021

    Verma A, Chitalia VC, Waikar SS, Kolachalama VB. Machine Learning Applications in Nephrology: A Bibliometric Analysis Comparing Kidney Studies to Other Medicine Subspecialities. Kidney Med. 2021 Sep-Oct; 3(5):762-767. PMID: 34693256.

    Read at: PubMed
  • Published on 5/23/2021

    Zheng Y, Cassol CA, Jung S, Veerapaneni D, Chitalia VC, Ren KYM, Bellur SS, Boor P, Barisoni LM, Waikar SS, Betke M, Kolachalama VB. Deep-Learning-Driven Quantification of Interstitial Fibrosis in Digitized Kidney Biopsies. Am J Pathol. 2021 08; 191(8):1442-1453. PMID: 34033750.

    Read at: PubMed
  • Published on 5/17/2021

    Weizenbaum EL, Fulford D, Torous J, Pinsky E, Kolachalama VB, Cronin-Golomb A. Smartphone-Based Neuropsychological Assessment in Parkinson's Disease: Feasibility, Validity, and Contextually Driven Variability in Cognition. J Int Neuropsychol Soc. 2022 Apr; 28(4):401-413. PMID: 33998438.

    Read at: PubMed

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