Research Interest:  Non-point source, soil heavy metal, absorbing Material, and restoration

Research Interest:  Biomedical  instrumentation,  Health  monitoring  system,  System  modeling  and control, robotics

Research Interest:  Biofabrication, Selective laser sintering, Nanotechnology, 3D Printing Biomaterials, Tissue Engineering

Research Interest:  Designing and preparing new nanobiomaterials Characterizing physical and chemical properties, biocompatibility and bioactivity of the nanobiomaterials

Research Interest: His research focuses on computer assisted surgery, including medical image analysis, surgical navigation, surgery simulation, surgical robots, biomedical manufacturing, etc.

Research Interest: Electroporation, Electroloading, Electrochemotherapy, Drug and Gene Delivery Systems, Molecular Imaging (EPR imaging; optical imaging; multimodal imaging – MRI/EPR, MRI/optical), Cancer Biochemistry

Research Interest:  His research interests concentrate on the biosensors (e.g. living cell sensor, DNA sensor and protein sensor) and BioMEMS system.

Research Interest:  Cell Printing, Now, he is especially interested in the novel cell printing method. With the different own designed cell printers, the project about how to printing vessels and the organ at the same time is underway. Organ on a chip, Now, he is especially interested in designing new method to 3D printing microfluidic chips which can be used in cell culture and the prototype of organ

Research Interest: Medical Image Analysis and Processing  Computer Simulations of Nanoscale Systems  Communications and Mobile Computing  Bioinformatics and Computational Biology Computational Neuroscience and Vascular Flow Dynamics Biometrics and Bio-robotics Computer Aided Diagnosis and Guided Surgerya

Research Interest: Super-resolution technology; Stochastic Optical Reconstruction Microscopy(STORM); Cell Imaging and Structure; Propagation and Scattering of Light in Random and Complex Media; Classical Coherence Theory; Laser Communications and LaserRadar Systems; Near-field Scattering; Optical Imaging System

Research Interest: Stem cells and Regenerative Medicine, Tissue Regeneration, Tissue Engineering Stem Cells Biology and Differentiation, Stem cells biomaterials interaction, Mechanotransduction

Biography:

My research focuses on establishing the clinical applicability of two new diagnostic parameters (to detect coronary artery disease) using a set of bench-top experiments, computational analysis, pre-clinical and clinical trials in our research group. These proposed diagnostic parameters based on fluid dynamic principles, pressure drop coefficient and lesion flow coefficient, have the potential to make a real paradigm shift in clinical decision making related to cardiovascular intervention. As part of my research involving pre-clinical and clinical trials I had collaborated with clinicians and scientists at College of Medicine, University of Cincinnati and at Cincinnati Children's Hospital and Medical Center. Preliminary results from these studies have concluded the clinical applicability of these parameters to distinguish between stenoses of various severity.
More recently, at Weill Cornell Medical College, I am working on using 3D printing, machine learning and computational fluid dynamics to predict and prevent coronary artery disease from non-invasive CCTA imaging data.

Research Interest: 3D printing, Computational fluid dynamics, clinical radiology, non-invasive CCTA scanning, machine learning, interventional cardiology, applied mathematics, bio-heat transfer

List of Publications:

1. Al'Aref SJ, Anchouche K, Singh G, Slomka PJ, Kolli KK, Kumar A, Pandey M, Maliakal G, van Rosendael AR, Beecy AN, Berman DS, Leipsic J, Nieman K, Andreini D, Pontone G, Schoepf UJ, Shaw LJ, Chang HJ, Narula J, Bax JJ, Guan Y, Min JK. Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging. Eur Heart J. 2018. Epub 2018/07/31. doi: 10.1093/eurheartj/ehy404. PubMed PMID: 30060039. Available from: https://www.ncbi.nlm.nih.gov/pubmed/30060039.

2. Kolli KK, Min JK. Image-based computational fluid dynamic analysis for surgical planning of sequential grafts in coronary artery bypass grafting. Accepted as Contributed full paper for publication in Conference Proceedings for IEEE Engineering in Medicine and Biology Society Conference. 2018. [Accepted]

3. van Rosendael AR, Maliakal G, Kolli KK, Beecy A, Al'Aref SJ, Dwivedi A, Singh G, Panday M, Kumar A, Ma X, Achenbach S, Al-Mallah MH, Andreini D, Bax JJ, Berman DS, Budoff MJ, Cademartiri F, Callister TQ, Chang HJ, Chinnaiyan K, Chow BJW, Cury RC, DeLago A, Feuchtner G, Hadamitzky M, Hausleiter J, Kaufmann PA, Kim YJ, Leipsic JA, Maffei E, Marques H, Pontone G, Raff GL, Rubinshtein R, Shaw LJ, Villines TC, Gransar H, Lu Y, Jones EC, Pena JM, Lin FY, Min JK. Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry. J Cardiovasc Comput Tomogr. 2018;12(3):204-9. Epub 2018/05/14. doi: 10.1016/j.jcct.2018.04.011. PubMed PMID: 29753765. Available from: https://www.ncbi.nlm.nih.gov/pubmed/29753765.

4. Singh G, Al'Aref SJ, Van Assen M, Kim TS, van Rosendael A, Kolli KK, Dwivedi A, Maliakal G, Pandey M, Wang J, Do V, Gummalla M, De Cecco CN, Min JK. Machine learning in cardiac CT: Basic concepts and contemporary data. J Cardiovasc Comput Tomogr. 2018; 12(3):192-201. Epub 2018/05/15. doi: 10.1016/j.jcct.2018.04.010. PubMed PMID: 29754806. Available from: https://www.ncbi.nlm.nih.gov/pubmed/29754806.

5. Beecy AN, Chang Q, Anchouche K, Baskaran L, Elmore K, Kolli KK, Wang H, Al'Aref S, Pena JM, Knight-Greenfield A, Patel P, Sun P, Zhang T, Kamel H, Gupta A, Min JK. A Novel Deep Learning Approach for Automated Diagnosis of Acute Ischemic Infarction on Computed Tomography. JACC Cardiovascular imaging. 2018. Epub 2018/05/21. doi: 10.1016/j.jcmg.2018.03.012. PubMed PMID: 29778866. Available from: https://www.ncbi.nlm.nih.gov/pubmed/29778866.

6. Peelukhana SV, Banerjee R, van de Hoef TP, Kolli KK, Effat M, Helmy T, Leesar M, Kerr H, Piek JJ, Succop P, Back L, Arif I. Evaluation of lesion flow coefficient for the detection of coronary artery disease in patient groups from two academic medical centers. Cardiovascular Revascularization
Kranthi Kolli 6 10/05/2018Medicine. 2018;19(3 Pt B):348-54. Epub 2017/10/19. doi: 10.1016/j.carrev.2017.08.018. PubMed PMID: 29037762. Available from: https://www.ncbi.nlm.nih.gov/pubmed/29037762.

7. Han D, Starikov A, Xiong G, Hartaigh B, Granser H, Kolli KK, Lee J, Rizvi A, Baskaran L, Schulman-Marcus J, Lin FY, Min JK. Relationship between endothelial wall shear stress and high-risk atherosclerotic plaque characteristic for identification of coronary lesions that cause ischemia: A direct comparison to fractional flow reserve. Journal of the American Heart Association. 2016; 5(12). doi: 10.1161/JAHA.116.004186. PubmMed PMID: 27993831. Available from: https://www.ncbi.nlm.nih.gov/pubmed/27993831

8. Kolli KK, Min JK, Ha S, Soohoo H, Xiong G. Effect of Varying Hemodynamic and Vascular Conditions on Fractional Flow Reserve: An In Vitro Study. Journal of the American Heart Association. 2016;5(7). doi: 10.1161/JAHA.116.003634. PubMed PMID: 27364988. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27364988.

9. Kolli KK, van de Hoef TP, Effat MA, Banerjee RK, Peelukhana SV, Succop P, Leesar MA, Imran A, Piek JJ, Helmy TA. Diagnostic cutoff for pressure drop coefficient in relation to fractional flow reserve and coronary flow reserve: A patient-level analysis. Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions. 2016;87(2):273-82. doi: 10.1002/ccd.26063. PubMed PMID: 26424295. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26424295.

10. Peelukhana SV, Effat M, Kolli KK, Arif I, Helmy T, Leesar M, Kerr H, Back LH, Banerjee R. Lesion flow coefficient: a combined anatomical and functional parameter for detection of coronary artery disease--a clinical study. The Journal of invasive cardiology. 2015;27(1):54-64. PubMed PMID: 25589702. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25589702.

11. Peelukhana SV, Banerjee R, Kolli KK, Fernandez-Ulloa M, Arif I, Effat M, Helmy T, Kerr H. Benefit of ECG-gated rest and stress N-13 cardiac PET imaging for quantification of LVEF in ischemic patients. Nuclear medicine communications. 2015;36(10):986-98. doi: 10.1097/MNM.0000000000000352. PubMed PMID: 26225941. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26225941.

12. Peelukhana SV, Kolli KK, Leesar MA, Effat MA, Helmy TA, Arif I, Schneeberger EW, Succop P, Banerjee RK. Effect of myocardial contractility on hemodynamic end points under concomitant microvascular disease in a porcine model. Heart and vessels. 2014;29(1):97-109. doi: 10.1007/s00380-013-0355-9. PubMed PMID: 23624760. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23624760.

13. Peelukhana SV, Kerr H, Kolli KK, Fernandez-Ulloa M, Gerson M, Effat M, Arif I, Helmy T, Banerjee R. Benefit of cardiac N-13 PET CFR for combined anatomical and functional diagnosis of ischemic coronary artery disease: a pilot study. Annals of nuclear medicine. 2014;28(8):746-60. doi: 10.1007/s12149-014-0869-y. PubMed PMID: 24950752. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24950752.

14. Kolli KK, Helmy TA, Peelukhana SV, Arif I, Leesar MA, Back LH, Banerjee RK, Effat MA. Functional diagnosis of coronary stenoses using pressure drop coefficient: a pilot study in humans. Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions. 2014;83(3):377-85. doi: 10.1002/ccd.25085. PubMed PMID: 23785016. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23785016.

15. Kolli KK, Effat MA, Peelukhana SV, Succop P, Back LH, Leesar MA, Helmy TA, Imran A, Banerjee RK. Hyperemia-free delineation of epicardial and microvascular impairments using a basal index. Annals of biomedical engineering. 2014;42(8):1681-90. doi: 10.1007/s10439-014-1020-x. PubMed PMID: 24806315. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24806315.
Kranthi Kolli 7 10/05/2018

16. Kolli KK, Arif I, Peelukhana SV, Succop P, Back LH, Helmy TA, Leesar MA, Effat MA, Banerjee RK. Diagnostic performance of pressure drop coefficient in relation to fractional flow reserve and coronary flow reserve. The Journal of invasive cardiology. 2014;26(5):188-95. PubMed PMID: 24791716. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24791716.

17. Kolli KK, Paul AK, Back LH, Effat MA, Banerjee RK. Optimization of balloon obstruction for simulating equivalent pressure drop in physiological stenoses. Biorheology. 2013;50(5-6):257-68. doi: 10.3233/BIR-130640. PubMed PMID: 24398608. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24398608.

18. Peelukhana SV, Banerjee RK, Kolli KK, Effat MA, Helmy TA, Leesar MA, Schneeberger EW, Succop P, Gottliebson W, Irif A. Effect of heart rate on hemodynamic endpoints under concomitant microvascular disease in a porcine model. American journal of physiology Heart and circulatory physiology. 2012;302(8):H1563-73. doi: 10.1152/ajpheart.01042.2011. PubMed PMID: 22287585. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22287585.

19. Kolli KK, Banerjee RK, Peelukhana SV, Effat MA, Leesar MA, Arif I, Schneeberger EW, Succop P, Gottliebson WM, Helmy TA. Effect of changes in contractility on pressure drop coefficient and fractional flow reserve in a porcine model. The Journal of invasive cardiology. 2012;24(1):6-12. PubMed PMID: 22210582. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22210582.

20. Rajabi-Jaghargh E, Kolli KK, Back LH, Banerjee RK. Effect of guidewire on contribution of loss due to momentum change and viscous loss to the translesional pressure drop across coronary artery stenosis: an analytical approach. Biomedical engineering online. 2011;10:51. doi: 10.1186/1475-925X-10-51. PubMed PMID: 21658283; PMCID: 3141581. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21658283.

21. Kolli KK, Banerjee RK, Peelukhana SV, Helmy TA, Leesar MA, Arif I, Schneeberger EW, Hand D, Succop P, Gottliebson WM, Effat MA. Influence of heart rate on fractional flow reserve, pressure drop coefficient, and lesion flow coefficient for epicardial coronary stenosis in a porcine model. American journal of physiology Heart and circulatory physiology. 2011;300(1):H382-7. doi: 10.1152/ajpheart.00412.2010. PubMed PMID: 20935151. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20935151.

Research Interest: Berber phonetics, Automatic Speech processing, Speech disorders Acoustic phonetics, Automatic Speech Recognition, Speech Synthesis, Artificial Neural NetworksArabic phonetics

Research Interest: Biophotonics, BioMEMS, Optofluidics, Surface Wettability, Drug Delivery

Research Interest: Scaffold Design For Tissue Engineering, Composites hydrogels For Bone Repair, Electrospinning and Electrospraying technology, Scanning and Trasmission Electron Microscopy, Image Analysis For Porosity Measurements, Chemical And Physical Properties Characterization Of Composite And/Or Polymeric Substrates, Injectable Composite Cements For Bone Cavity Filling.