Kirti M. Yenkie

Kirti M. Yenkie

Kirti M. Yenkie

Assistant Professor 

Kirti M. Yenkie  

Biography:

  • Assistant Professor in Chemical Engineering, Rowan University, (09/2017-present)
  • Postdoctoral Researcher (04/2017-08/2017) in Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, USA
  • Postdoctoral Researcher (01/2015-03/2017) in Department of Chemical and Biological Engineering, University of Wisconsin-Madison, USA
  • Ph.D. in Bioengineering (01/2011-12/2014), University of Illinois at Chicago, USA and Vishwamitra Research Institute (VRI-CUSTOM), Crystal Lake, IL, USA
  • M. Tech in Chemical Engineering (07/2008-08/2010), IIT Bombay (Indian Institute of Technology, Bombay), India
  • B. Tech in Chemical Engineering (07/2004-05/2008) from LIT (Laxminarayan Institute of Technology), Nagpur University, Nagpur, India
  • Higher Diploma in German Language (08/2005-05/2008), Department of Foreign Languages, Nagpur University, Nagpur, India

Research Interests:

  • Mathematical modeling, optimization and control
  • Systems medicine
  • Sustainability
  • Uncertainty characterization and stochastic processes

Courses:

  • CHE 06502/06490 Process Optimization (Spring 2018)
  • CHE 06405 Process Dynamics and Control (Fall 2017)
  • Junior/Senior Research Clinics (Fall and Spring)

Publications:

Peer-Reviewed Publications

Journal Publications:

  1. Yenkie, K. M.; Diwekar, U. 2013. Stochastic optimal control of seeded batch crystallizer applying Ito process. Ind. Eng. Chem. Res., 52:108-122.
  2. Yenkie, K. M.; Diwekar, U.; Bhalerao, V. 2013. Modeling the superovulation stage in in-vitro fertilization. IEEE Trans. Biomed. Eng., 60(11): 3003-3008.
  3. Yenkie, K. M.; Diwekar, U. 2014. Optimal control for predicting customized drug dosage for superovulation stage of in-vitro fertilization. Journal of Theoretical Biology, 355: 219-228.
  4. Yenkie, K. M.; Diwekar, U.; Bhalerao, V. 2014. Modeling and prediction of outcome for the superovulation stage in in-vitro fertilization. JFIV Reprod.Med.Genet. 2(2):1000122(1-8).
  5. Yenkie, K. M.; Diwekar, U. 2014. Comparison of optimal control methods for customized drug dosage prediction in superovulation stage of in-vitro fertilization. Computers and Chemical Engineering, 71: 708-714.
  6. Yenkie, K. M.; Diwekar, U. 2014. Uncertainty in clinical data and stochastic model for in-vitro fertilization. Journal of Theoretical Biology, 367: 76-85.
  7. Doshi, R.; Diwekar, U.; Benavides, P.; Yenkie, K.; Cabezas, H. 2014. Maximizing sustainability of ecosystem model through socio-economic policies derived from multivariable optimal control theory. Clean Technologies and Environmental Policy, 1-11.
  8. Yenkie, K. M.; Diwekar, U.; Linninger, A. A. 2016. Simulation-free estimation of reaction propensities in cellular reactions and gene signaling networks. Computers and Chemical Engineering, 87: 154-163.
  9. Yenkie, K. M.; Wu, W.; Clark, R. L.; Pfleger, B. F.; Root, T. W.; Maravelias, C. T. 2016. Roadmap for selection of separation technologies in the recovery of bio-based chemicals: matching biological and process feasibility. Biotechnology Advances, 34(8): 1362-1383.
  10. Wu, W.; Yenkie, K. M.; Maravelias, C. T. 2016. A superstructure based framework for bio-separation network synthesis. Computers and Chemical Engineering, 96: 1-17.
  11. Yenkie, K. M.; Wu, W.; Maravelias, C. T. 2017. Synthesis and analysis of separation networks for the recovery of intracellular chemicals generated from microbial-based conversions. Biotechnology for Biofuels, 10:119.
  12. Yenkie, K. M.; Diwekar, U. M. The ‘No sampling’ parameter estimation algorithm for stochastic differential equations. Chemical Engineering Research & Design, 129: 376-383.

Conference Publications:

  1. Yenkie, K. M.; Singh, K. P.; Jadhav, S.; Wangikar, P. P. Morphological model to correlate morphology and metabolism in Actinomycetes, Chemference 2010, Session 5:Bioprocess Engineering, S-501, Kanpur, UP, India.
  2. Yenkie, K. M.; Diwekar, U. M.; Bhalerao, V. 2012. Modeling the superovulation stage in in-vitro fertilization. Proceedings of the 11th International symposium on Process Systems Engineering (PSE), 840-844.
  3. Yenkie, K. M.; Diwekar, U. M. 2014. Comparison of optimal control methods for customized drug dosage prediction in superovulation stage of in-vitro fertilization. Proceedings of the 8th International conference on Foundations of Computer-Aided Process Design (FOCAPD), 807-812.
  4. Yenkie, K. M.; Diwekar, U. M. 2015. Uncertainty in clinical data and stochastic model for superovulation stage in in-vitro fertilization. Proceedings of the 12th International symposium on Process Systems Engineering (PSE) and 25th European Symposium on Computer-Aided Process Engineering (ESCAPE).

Selected Conference Presentations and Posters:

Summary – 17 podium presentations and 9 poster presentations

Selected Podium Presentations:

  1. Yenkie, K.M.; Diwekar, U. Stochastic optimal control for prediction of robust drug dosing policies in superovulation stage of in-vitro fertilization. AIChE Annual Meeting, 2015, 393d, Salt Lake City, UT.
  2. Yenkie, K.M.; Diwekar, U.; Linninger, A. Parameter estimation in cellular systems modeled as stochastic differential equations. AIChE Annual Meeting, 2014, 235g, Atlanta, GA.
  3. Yenkie, K.M.; Diwekar, U. Uncertainty in clinical data and stochastic model for in-vitro fertilization. AIChE Annual Meeting, 2014, 376f, Atlanta, GA.
  4. Yenkie, K.M.; Diwekar, U.; Linninger, A.;  Kim, S. A new  method  for  parameter  estimation  in stochastic differential equations. AIChE Annual Meeting, 2013, 589e, San Francisco, CA.
  5. Yenkie, K.M.; Diwekar, U. Comparison of different methods for predicting customized drug dosage in superovulation stage of in-vitro fertilization. INFORMS Healthcare 2013, MC-06(2), Chicago, IL.
  6. Yenkie, K.M.; Diwekar, U.; Bhalerao, V. Modeling the superovulation stage in in-vitro fertilization (IVF). AIChE Annual Meeting, 2012, 312b, Pittsburgh, PA. 
  7. Yenkie, K.M.; Diwekar, U. Optimal control for predicting drug dosage in superovulation stage of in-vitro fertilization. INFORMS Annual Meeting, 2012, TD-20(2), Phoenix, AZ.
  8. Yenkie, K.M.; Diwekar, U. Stochastic optimal control in batch crystallization applying Ito Processes. AIChE Annual Meeting, 2011, 131c, Minneapolis, MN.

Selected Poster Presentations:

  1. Yenkie, K.M.; Diwekar, U.; Bhalerao, V. IVF modeling, optimal control, and customized drug treatment: Results of the first Clinical trial. AIChE Annual Meeting, 2017, 585ae, Minneapolis, MN.
  2. Yenkie, K.M.; Wu, W.; Maravelias, C. T. Assessment of bioseparation technology options for bio-based chemicals generated from microbial cultures. AIChE Annual Meeting, 2016, 228dg, San Francisco, CA.
  3. Yenkie, K.M.; Diwekar, U. Uncertainty in clinical data and stochastic model for in-vitro fertilization. Health Systems Optimization Workshop at Northwestern University, 12-13 September, 2014.
  4. Yenkie, K.M.; Diwekar, U.; Bhalerao, V. Modeling the superovulation stage in in-vitro fertilization (IVF). Midwest Biomedical Engineering Career Conference (MBECC) 2013, UIC, Chicago, IL.
  5. Yenkie, K.M.; Diwekar, U. Uncertainties and stochastic optimal control in batch crystallization for different types of objective functions. AIChE Annual Meeting, 2012, 599f, Pittsburgh, PA.

Contact Information

Email: yenkie@rowan.edu

Phone: 856-256-5375

Office: Rowan Hall 329

Office Hours: Monday and Wednesday 2 to 3 PM or by appointment

LinkedIn: https://www.linkedin.com/in/yenkiekm

Research Group: https://yenkiekm.com/

Resume: yenkie_resume.pdf