Vijaya B. Kolachalama, PhD, FAHA
Assistant Professor
Boston University School of Medicine
Dept of Medicine
Computational Biomedicine

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




The Kolachalama laboratory is broadly focused on developing advanced machine learning algorithms to tackle complex biomedical datasets, with particular emphasis on medical imaging.

Phenotyping neurodegeneration using machine learning: 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.

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

Machine learning for musculoskeletal diseases: We develop machine learning frameworks to bring efficiency to the analysis of large-scale studies such as Osteoarthritis Initiative (OAI) and Multicenter osteoarthritis (MOST) study. We are particularly interested to quantify structures that are responsible for pain and factors that contribute to the progression of knee osteoarthritis.

Member
Boston University
Whitaker Cardiovascular Institute


Member
Boston University
Evans Center for Interdisciplinary Biomedical Research


Founding Assistant Professor
Boston University School of Medicine, Graduate Medical Sciences
Computing & Data Sciences Administration



2021 Karen Toffler Charitable Trust: Toffler Scholar in Neuroscience
2020 Faculty of Computing & Data Sciences, Boston University: Founding Member
2019 Institute for Health System Innovation & Policy, Boston University: Institute Fellow
2019 American Heart Association: Fellow
2018 Hariri Institute for Computing and Computational Science & Engineering, Boston University: Junior Faculty Fellow
2008 United States Food and Drug Administration: ORISE Fellowship
2005 Massachusetts Institute of Technology: Young Researcher Fellowship


Integrated Digital Technology Platform for Optimization of Precision Brain Health
07/01/2020 - 06/30/2024 (Co-PI)
PI: Rhoda Au, PhD
American Heart Association


PRISTINE: Pre-cancer histology identification of Endobronchial biopsies using deep learning
09/01/2020 - 08/31/2022 (Co-PI)
PI: Jennifer E. Beane-Ebel, PhD
NIH/National Cancer Institute
1R21CA253498-01

Mechanisms of drug-coated balloon therapy
07/01/2017 - 06/30/2021 (PI)
American Heart Association


Biomarkers of lung squamous premalignant progression using deep learning on pathology imagesBiomarkers of lung squamous premalignant progression using deep learning on pathology images
06/01/2020 - 05/31/2021 (Co-PI)
PI: Jennifer E. Beane-Ebel, PhD
Johnson & Johnson Enterprise Innovation, Inc.


Novel antibody design using deep learning
01/01/2018 - 12/31/2019 (PI)
Visterra, Inc.




Title


Yr Title Project-Sub Proj Pubs

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

iCite Analysis       Copy PMIDs To Clipboard

  1. Zhou X, Qiu S, Joshi PS, Xue C, Killiany RJ, Mian AZ, Chin SP, Au R, Kolachalama VB. Enhancing magnetic resonance imaging-driven Alzheimer's disease classification performance using generative adversarial learning. Alzheimers Res Ther. 2021 03 14; 13(1):60.View Related Profiles. PMID: 33715635
     
  2. Chang GH, Felson DT, Qiu S, Guermazi A, Capellini TD, Kolachalama VB. Correction to: Assessment of knee pain from MR imaging using a convolutional Siamese network. Eur Radiol. 2020 Dec; 30(12):6968.View Related Profiles. PMID: 32700018
     
  3. 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 SARS-CoV-2 nucleic acid(RNAemia) and Organ Damage in COVID-19 Patients: A Cohort Study. Clin Infect Dis. 2020 Jul 28. PMID: 32720678
     
  4. Qiu S, Joshi PS, Miller MI, Xue C, Zhou X, Karjadi C, Chang GH, Joshi AS, Dwyer B, Zhu S, Kaku M, Zhou Y, Alderazi YJ, Swaminathan A, Kedar S, Saint-Hilaire MH, Auerbach SH, Yuan J, Sartor EA, Au R, Kolachalama VB. Development and validation of an interpretable deep learning framework for Alzheimer's disease classification. Brain. 2020 06 01; 143(6):1920-1933.View Related Profiles. PMID: 32357201
     
  5. Azar D, Lott JT, Jabbarzadeh E, Shazly T, Kolachalama VB. Surface Modification Using Ultraviolet-Ozone Treatment Enhances Acute Drug Transfer in Drug-Coated Balloon Therapy. Langmuir. 2020 05 05; 36(17):4645-4653. PMID: 32271583
     
  6. Richard D, Liu Z, Cao J, Kiapour AM, Willen J, Yarlagadda S, Jagoda E, Kolachalama VB, Sieker JT, Chang GH, Muthuirulan P, Young M, Masson A, Konrad J, Hosseinzadeh S, Maridas DE, Rosen V, Krawetz R, Roach N, Capellini TD. Evolutionary Selection and Constraint on Human Knee Chondrocyte Regulation Impacts Osteoarthritis Risk. Cell. 2020 04 16; 181(2):362-381.e28. PMID: 32220312
     
  7. Chang GH, Felson DT, Qiu S, Guermazi A, Capellini TD, Kolachalama VB. Assessment of knee pain from MR imaging using a convolutional Siamese network. Eur Radiol. 2020 Jun; 30(6):3538-3548.View Related Profiles. PMID: 32055951
     
  8. Wollacott AM, Xue C, Qin Q, Hua J, Bohnuud T, Viswanathan K, Kolachalama VB. Quantifying the nativeness of antibody sequences using long short-term memory networks. Protein Eng Des Sel. 2019 12 31; 32(7):347-354. PMID: 31504835
     
  9. Joshi PS, Heydari M, Kannan S, Alvin Ang TF, Qin Q, Liu X, Mez J, Devine S, Au R, Kolachalama VB. Temporal association of neuropsychological test performance using unsupervised learning reveals a distinct signature of Alzheimer's disease status. Alzheimers Dement (N Y). 2019; 5:964-973.View Related Profiles. PMID: 31921970
     
  10. Walker JA, Richards S, Belghasem ME, Arinze N, Yoo SB, Tashjian JY, Whelan SA, Lee N, Kolachalama VB, Francis J, Ravid K, Sherr D, Chitalia VC. Temporal and tissue-specific activation of aryl hydrocarbon receptor in discrete mouse models of kidney disease. Kidney Int. 2020 03; 97(3):538-550.View Related Profiles. PMID: 31932072
     
Showing 10 of 46 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 46 publications over 14 distinct years, with a maximum of 10 publications in 2019

YearPublications
20072
20082
20092
20112
20123
20132
20142
20152
20164
20172
20186
201910
20206
20211


Recent (within 3 months)

Artificial Intelligence Boosts Alzheimer’s Disease Classification

healthitanalytics 3/16/2021

AI enhances brain MRI scans to better classify Alzheimer’s disease

Health Imaging 3/15/2021

AI Approach Helps Classify Alzheimer’s Disease with Improved Accuracy

AZO Robotics 3/10/2021
Older

Biogen’s New Alzheimer’s Drug Is “Hugely Important,” “One of the Biggest Moments” in 20 Years

The Brink 11/6/2020

New AI Algorithm Identifies Alzheimer’s Disease, Predicts Risk For Disease

Study Finds 5/19/2020

Algoritm Beats Experts In Alzheimer's Diagnosis

Futurity 5/7/2020

Deep Learning AI Accurately Predicts and Diagnoses Alzheimer’s Disease

Genetic Engineering & Biotechnology News 5/5/2020

Know What’s Good for your Health? Artificial Intelligence

BU Today 5/29/2019

Could Better Materials Lead to Better Outcomes with DCBs?

Medical Device and Diagnostic Industry 5/3/2019

Multimodal fusion model can better predict cognitive impairment

News Medical Life Sciences 10/4/2018
In addition to these self-described keywords below, a list of MeSH based concepts is available here.

Machine learning
Artificial intelligence
Deep learning
Computer vision
Digital pathology
Radiology
Deep neural networks
Adversarial learning
Alzheimer's disease
Osteoarthritis
Chronic kidney disease
Lung cancer
Vascular drug delivery
Drug coated balloons
Drug eluting stents

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