Vijaya B. Kolachalama, PhD, FAHA
Associate Professor
Boston University Chobanian & Avedisian School of Medicine
Medicine
Computational Biomedicine

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



Our mission is to create methods to fit the science and not make science fit the methods.

Specifically, we are interested in the following questions that have clinical relevance:
-- Neurodegeneration: How can we develop software frameworks that can assist neurology practitioners in various real-world settings?
-- Digital pathology: How can we build clinical-grade software tools to complement the pathologist workflow?

We are also interested in the following frameworks that have computational relevance:
-- Multimodal machine learning: Efficient design of AI agents for multimodal data processing with incomplete information.
-- Representation learning: Construction of efficient neural networks on high resolution data to process local and contextual information.

Diversity, Equity, Inclusion and Accessibility

We value the importance of creating a diverse and equitable environment and take pride in maintaining a laboratory that has an equal number of trainees from both genders. The trainees are medical school students, graduate students from computer sciences, arts and engineering, undergraduate students, medical residents, and clinical fellows. Over 50 trainees have already been co-authors of journal papers and graduates from our laboratory are pursuing higher education, and accepted faculty appointments in research-intensive universities, as well as computer vision and machine learning intern and scientist roles in companies such as Microsoft and Bose.

We thrive on collaborative ideas and openly invite other faculty members to our group for discussions and forge new partnerships. For each project, we have a multidisciplinary team that brings together the needed perspectives to innovate and translate a computational framework to solve a clinically relevant problem. Our laboratory meetings are focused on mathematical concepts, coding hacks and algorithms, deeper dive on the clinical questions and overall translation of our findings.

Below are some specific contributions that reflect our DEIA initiatives:
2018 --- Faculty development and diversity committee, Boston University School of Medicine
2019-21 --- Mentor for Supporting Undergraduate Research Experience (SURE) Program (Grant# 55205494), American Heart Association; The focus of this program is to support undergraduate students from Historically Black Colleges and Universities and Hispanic Serving Institutions
2017-present --- Mentor to the following scholars.
• Shinobu Matsuura, PhD: K01 Grant Awardee (K01-OD025290), Project Title: The bone marrow extracellular matrix: scaffold of hematopoiesis
• Kathy Bacon, PhD: Rheumatology Research Foundation Career Development Awardee, Project Title: Machine learning analysis of longitudinal gait data in osteoarthritis
• Ileana De Anda-Duran, MD, MPH: AHA Postdoctoral Fellow (20SFRN35460031), Project Title: Integrated Digital Technology Platform for Optimization of Precision Brain Health
• Phillip Hwang, PhD: AHA Postdoctoral Fellow (20SFRN35460031), Project Title: Integrated Digital Technology Platform for Optimization of Precision Brain Health
• Huitong Ding, PhD: AHA Postdoctoral Fellow (20SFRN35460031), Project Title: Integrated Digital Technology Platform for Optimization of Precision Brain Health
• Kerry Costello, PhD: F32 Grant Awardee (F32-AR076907), Project Title: Machine learning for analysis of walking patterns and physical activity in knee osteoarthritis
• Claire Cordella, PhD: F32 Grant Awardee (F32-DC020342), Project Title: Detecting and classifying non-fluent speech in aphasia using machine learning
• Insa Schmidt, PhD: K01 Grant Awardee (F32-DK136973), Project Title: Deep learning approach for the assessment of arterial and arteriolar lesions in kidney biopsies and prediction of cardiovascular risk

Finally, we want to disseminate the value of data science education more broadly in the public domain. We have written articles about the value of machine learning education in medical (NPJ Digit Med. 2018 Sep 27;1:54. PMID: 31304333) as well as undergraduate (Artif Intell Med. 2022 Jul;129:102313. PMID: 35659392) institutions, and gave seminars to the scientific community on this topic. As a result, the curriculum that we designed for a graduate course in machine learning (MS650) is now being adapted by several researchers.

Member
Boston University
Whitaker Cardiovascular Institute


Member
Boston University
Evans Center for Interdisciplinary Biomedical Research


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




Digital Cognitive Assessment of Preclinical Alzheimer's Disease and Related Dementias
08/01/2024 - 04/30/2029 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
NIH/National Institute on Aging
1R01AG083735-01A1

Mechanisms of drug-coated balloon therapy
09/01/2021 - 08/31/2025 (PI)
NIH/National Heart, Lung, and Blood Institute
5R01HL159620-03

Smartphone image analysis for real time adequacy assessment during kidney biopsy
09/15/2022 - 08/31/2024 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
Arkana Laboratories NIH NIDDK
1R43DK134273-01

PRISTINE: Pre-cancer histology identification of Endobronchial biopsies using deep learning
09/01/2020 - 08/31/2024 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
NIH/National Cancer Institute
1R21CA253498-01

Utilizing Technology and AI Approaches to Facilitate Independence and Resilience in Older Adults
06/01/2023 - 07/31/2024 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
The Johns Hopkins University NIH NIA
5P30AG073104-03

Integrated Digital Technology Platform for Optimization of Precision Brain Health
07/01/2020 - 06/30/2024 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
American Heart Association


Using deep learning to advance lung cancer interception and early detection
01/01/2022 - 12/31/2023 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
Johnson & Johnson Enterprise Innovation, Inc.


Cognitive heterogeneity in those with high Alzheimer's Disease Risk
05/01/2020 - 04/30/2023 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
NIH/National Institute on Aging
1RF1AG062109-01A1

Predicting gene expression from pathology images in diabetic kidney disease
07/01/2021 - 12/31/2022 (Subcontract PI)
Augusta University NIH NIDDK
5U24DK115255-04

Biomarkers of lung squamous premalignant progression using deep learning on pathology images
06/01/2020 - 12/31/2021 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
Johnson & Johnson Enterprise Innovation, Inc.


Showing 10 of 12 results. Show All Results


Title

Predicting gene expression from pathology images in diabetic kidney disease
07/01/2021 - 06/30/2022 (PI)
NIDDK - DIABETIC COMPLICATIONS CONSORTIUM (DiaComp)

Toffler Scholar in Neuroscience
01/01/2021 - 12/31/2021 (PI)
The Karen Toffler Charitable Trust

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. Ding H, Ho K, Searls E, Low S, Li Z, Rahman S, Madan S, Igwe A, Popp Z, Burk A, Wu H, Ding Y, Hwang PH, Anda-Duran I, Kolachalama VB, Gifford KA, Shih LC, Au R, Lin H. Assessment of Wearable Device Adherence for Monitoring Physical Activity in Older Adults: Pilot Cohort Study. JMIR Aging. 2024 Oct 25; 7:e60209.View Related Profiles. PMID: 39454101
     
  2. Zheng Y, Conrad RD, Green EJ, Burks EJ, Betke M, Beane JE, Kolachalama VB. Graph Attention-Based Fusion of Pathology Images and Gene Expression for Prediction of Cancer Survival. IEEE Trans Med Imaging. 2024 Sep; 43(9):3085-3097.View Related Profiles. PMID: 38587959; PMCID: PMC11374469; DOI: 10.1109/TMI.2024.3386108;
     
  3. Jia S, Bit S, Searls E, Claus LA, Fan P, Jasodanand VH, Lauber MV, Veerapaneni D, Wang WM, Au R, Kolachalama VB. MedPodGPT: A multilingual audio-augmented large language model for medical research and education. medRxiv. 2024 Jul 12.View Related Profiles. PMID: 39040167; PMCID: PMC11261953; DOI: 10.1101/2024.07.11.24310304;
     
  4. Xue C, Kowshik SS, Lteif D, Puducheri S, Jasodanand VH, Zhou OT, Walia AS, Guney OB, Zhang JD, Pham ST, Kaliaev A, Andreu-Arasa VC, Dwyer BC, Farris CW, Hao H, Kedar S, Mian AZ, Murman DL, O'Shea SA, Paul AB, Rohatgi S, Saint-Hilaire MH, Sartor EA, Setty BN, Small JE, Swaminathan A, Taraschenko O, Yuan J, Zhou Y, Zhu S, Karjadi C, Alvin Ang TF, Bargal SA, Plummer BA, Poston KL, Ahangaran M, Au R, Kolachalama VB. AI-based differential diagnosis of dementia etiologies on multimodal data. Nat Med. 2024 Oct; 30(10):2977-2989.View Related Profiles. PMID: 38965435; PMCID: PMC11485262; DOI: 10.1038/s41591-024-03118-z;
     
  5. Amini S, Hao B, Yang J, Karjadi C, Kolachalama VB, Au R, Paschalidis IC. Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models. Alzheimers Dement. 2024 Aug; 20(8):5262-5270.View Related Profiles. PMID: 38924662; PMCID: PMC11350035; DOI: 10.1002/alz.13886;
     
  6. Ahangaran M, Sun E, Le K, Sun J, Wang WM, Tan TH, Yin L, Burdine LJ, Dvanajscak Z, Cassol CA, Sharma S, Kolachalama VB. Pilot Study of a Web-Based Tool for Real-Time Adequacy Assessment of Kidney Biopsies. Kidney Int Rep. 2024 Sep; 9(9):2809-2813.View Related Profiles. PMID: 39291211; PMCID: PMC11403039; DOI: 10.1016/j.ekir.2024.06.019;
     
  7. Laudon A, Zou A, Wang Z, Sharma R, Fan X, Ji J, Kim C, Qian Y, Ye Q, Chen H, Henderson JM, Zhang C, Kolachalama VB, Lu W. Digital pathology assessment of kidney glomerular filtration barrier ultrastructure in an animal model of podocytopathy. bioRxiv. 2024 Jun 17.View Related Profiles. PMID: 38948787; PMCID: PMC11212870; DOI: 10.1101/2024.06.14.599097;
     
  8. Ahangaran M, Zhu H, Li R, Yin L, Jang J, Chaudhry AP, Farrer LA, Au R, Kolachalama VB. DREAMER: a computational framework to evaluate readiness of datasets for machine learning. BMC Med Inform Decis Mak. 2024 Jun 04; 24(1):152.View Related Profiles. PMID: 38831432; PMCID: PMC11149315; DOI: 10.1186/s12911-024-02544-w;
     
  9. Zhou X, Balachandra AR, Romano MF, Chin SP, Au R, Kolachalama VB. Adversarial Learning for MRI Reconstruction and Classification of Cognitively Impaired Individuals. IEEE Access. 2024; 12:83169-83182.View Related Profiles. PMID: 39148927; PMCID: PMC11326336; DOI: 10.1109/access.2024.3408840;
     
  10. Lteif D, Sreerama S, Bargal SA, Plummer BA, Au R, Kolachalama VB. Disease-driven domain generalization for neuroimaging-based assessment of Alzheimer's disease. Hum Brain Mapp. 2024 Jun 01; 45(8):e26707.View Related Profiles. PMID: 38798082; PMCID: PMC11128757; DOI: 10.1002/hbm.26707;
     
Showing 10 of 99 results. Show More

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

Bar chart showing 99 publications over 17 distinct years, with a maximum of 23 publications in 2024

YearPublications
20072
20082
20092
20112
20123
20132
20142
20152
20164
20172
20186
201910
20205
20219
202210
202313
202423


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Artificial intelligence may diagnose dementia as accurately as clinicians

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Novel AI algorithm developed for assessing digital pathology data

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Artificial intelligence aids nephrologists in directing kidney care

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New Measure to Determine Severity of Knee Osteoarthritis with AI

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Artificial Intelligence Boosts Alzheimer’s Disease Classification

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

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AI Approach Helps Classify Alzheimer’s Disease with Improved Accuracy

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

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Deep Learning AI Accurately Predicts and Diagnoses Alzheimer’s Disease

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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

2024 The Framingham Heart Study: Executive Committee
2024 Indian Institute of Technology, Kharagpur: Young Alumni Achiever Award
2022 The Institute of Electrical and Electronics Engineers: Senior Member
2021 Karen Toffler Charitable Trust: Toffler Scholar in Neuroscience
2021 Department of Medicine, Boston University School of Medicine: Evans Junior Faculty Merit Award
2020 Faculty of Computing & Data Sciences, Boston University: Founding Member
2020 Department of Medicine, Boston University School of Medicine: Outstanding Research Collaborator
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

Available to Mentor as: (Review Mentor Role Definitions):
  • Advisor
  • Career Mentor
  • Co-Mentor or Peer Mentor
  • Diversity Mentor
  • Education Mentor
  • Project Mentor
  • Research / Scholarly Mentor
  • Work / Life Integration Mentor
Contact for Mentoring:

72 East Concord Street, Evans 636
Boston MA 02118
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