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 learning: Efficient design of generalist AI models that can process multiple modalities of data.
-- Representation learning: Construction of efficient neural models 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

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




Mechanisms of drug-coated balloon therapy
09/01/2021 - 08/31/2025 (PI)
NIH/National Heart, Lung, and Blood Institute
5R01HL159620-02

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


Utilizing Technology and AI Approaches to Facilitate Independence and Resilience in Older Adults
06/01/2023 - 05/31/2024 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
Johns Hopkins University NIH NIA
5P30AG073104-03

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.


Smartphone image analysis for real time adequacy assessment during kidney biopsy
09/15/2022 - 08/31/2023 (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 - 08/31/2023 (Multi-PI)
PI: Vijaya B. Kolachalama, PhD, FAHA
NIH/National Cancer Institute
1R21CA253498-01

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.


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


Showing 10 of 11 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. Bacon KL, Felson DT, Jafarzadeh SR, Kolachalama VB, Hausdorff JM, Gazit E, Stefanik JJ, Corrigan P, Segal NA, Lewis CE, Nevitt MC, Kumar D. Gait alterations associated with worsening knee pain and physical function: a machine-learning approach with wearable sensors in the Multicenter Osteoarthritis Study. Arthritis Care Res (Hoboken). 2024 Mar 24.View Related Profiles. PMID: 38523250
     
  2. Surendran T, Park LK, Lauber MV, Cha B, Jhun RS, Capellini TD, Kumar D, Felson DT, Kolachalama VB. Survival analysis on subchondral bone length for total knee replacement. Skeletal Radiol. 2024 Feb 22.View Related Profiles. PMID: 38388702
     
  3. Ding H, Kim M, Searls E, Sunderaraman P, De Anda-Duran I, Low S, Popp Z, Hwang PH, Li Z, Goyal K, Hathaway L, Monteverde J, Rahman S, Igwe A, Kolachalama VB, Au R, Lin H. Digital neuropsychological measures by defense automated neurocognitive assessment: reference values and clinical correlates. Front Neurol. 2024; 15:1340710.View Related Profiles. PMID: 38426173; PMCID: PMC10902432; DOI: 10.3389/fneur.2024.1340710;
     
  4. Ahangaran M, Sun E, Le K, Sun J, Wang WM, Tan TH, Burdine LJ, Dvanajscak Z, Cassol CA, Sharma S, Kolachalama VB. A web-based tool for real-time adequacy assessment of kidney biopsies. medRxiv. 2024 Feb 05.View Related Profiles. PMID: 38370740; PMCID: PMC10871452; DOI: 10.1101/2024.02.01.24302147;
     
  5. Popp Z, Low S, Igwe A, Rahman MS, Kim M, Khan R, Oh E, Kumar A, De Anda-Duran I, Ding H, Hwang PH, Sunderaraman P, Shih LC, Lin H, Kolachalama VB, Au R. Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research. J Am Heart Assoc. 2024 Jan 16; 13(2):e031247.View Related Profiles. PMID: 38226518; PMCID: PMC10926806; DOI: 10.1161/JAHA.123.031247;
     
  6. De Anda-Duran I, Sunderaraman P, Searls E, Moukaled S, Jin X, Popp Z, Karjadi C, Hwang PH, Ding H, Devine S, Shih LC, Low S, Lin H, Kolachalama VB, Bazzano L, Libon DJ, Au R. Comparing Cognitive Tests and Smartphone-Based Assessment in 2 US Community-Based Cohorts. J Am Heart Assoc. 2024 Jan 16; 13(2):e032733.View Related Profiles. PMID: 38226519; PMCID: PMC10926794; DOI: 10.1161/JAHA.123.032733;
     
  7. Sunderaraman P, De Anda-Duran I, Karjadi C, Peterson J, Ding H, Devine SA, Shih LC, Popp Z, Low S, Hwang PH, Goyal K, Hathaway L, Monteverde J, Lin H, Kolachalama VB, Au R. Design and Feasibility Analysis of a Smartphone-Based Digital Cognitive Assessment Study in the Framingham Heart Study. J Am Heart Assoc. 2024 Jan 16; 13(2):e031348.View Related Profiles. PMID: 38226510; PMCID: PMC10926817; DOI: 10.1161/JAHA.123.031348;
     
  8. Romano MF, Shih LC, Paschalidis IC, Au R, Kolachalama VB. Large Language Models in Neurology Research and Future Practice. Neurology. 2023 Dec 04; 101(23):1058-1067.View Related Profiles. PMID: 37816646; PMCID: PMC10752640; DOI: 10.1212/WNL.0000000000207967;
     
  9. Shazly T, Uline M, Webb C, Pederson B, Eberth JF, Kolachalama VB. Novel Payloads to Mitigate Maladaptive Inward Arterial Remodeling in Drug-Coated Balloon Therapy. J Biomech Eng. 2023 Dec 01; 145(12). PMID: 37542712; PMCID: PMC10578076; DOI: 10.1115/1.4063122;
     
  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. medRxiv. 2023 Sep 25.View Related Profiles. PMID: 37808872; PMCID: PMC10557812; DOI: 10.1101/2023.09.22.23295984;
     
Showing 10 of 82 results. Show More

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

Bar chart showing 82 publications over 17 distinct years, with a maximum of 12 publications in 2023

YearPublications
20072
20082
20092
20112
20123
20132
20142
20152
20164
20172
20186
201910
20205
20219
202210
202312
20247


BU Ignition Awards to Accelerate Products for Repairing Damaged Teeth, Fighting Cancer, Boosting Reading Skills, and More

The Brink 9/19/2023

From mild cognitive impairment to Alzheimer's: Predicting risk

Medical News Today 8/10/2023

BU Researchers Look To Quantify The Risk Of Alzheimer's Disease Progression

WBZ Radio 8/4/2023

Best of The Brink 2022: BU’s Most-Read Science and Research Stories

BU Today 12/13/2022

Alzheimer's-Diagnosing AI Better Than Medical Experts? New Study Shows It Can Solve Physician Shortage

Tech Times 8/3/2022

Two Technologies That Can Make Diagnosing Dementia Easier for Doctors and Patients

Mirage News 6/25/2022

AI may detect dementia just as well as doctors: study

The Hill 6/21/2022

Artificial intelligence may diagnose dementia as accurately as clinicians

United Press International 6/20/2022

Researchers develop novel AI algorithm for digital pathology analysis

Longevity Technology 5/26/2022

Researchers Create New AI-Based Techniques for Analyzing Digital Pathology Data

AzoRobotics 5/24/2022

Novel AI algorithm developed for assessing digital pathology data

News Medical 5/23/2022

Artificial intelligence aids nephrologists in directing kidney care

Healio 6/10/2021

New Measure to Determine Severity of Knee Osteoarthritis with AI

AZO Robotics 5/13/2021

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

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

2024 The Framingham Heart Study: Executive Committee
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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