Ravindra Gajulapalli, PhD

I bring a unique combination of technical and programming depth along with an extensive experience across industries and business functions in AI, optimization and machine learning. I grasp the nuances of a business decision quickly,  am adept at breaking complex business requirements, and implementing actionable algorithms and models.  

I am developing a probabilistic distance clustering algorithm in Python that converges fast and seems to be an alternative to the well-known EM methods in machine learning for de-mixing distributions. 

I am also building LSNLOPT, an extensible and robust framework in C++20 for large scale nonlinear optimization that exploits super-sparsity, uses graph theoretic algorithms for fill-in reduction and addresses common pitfalls.   

I was a hands-on Manager, Decisions Sciences at Kohl’s; where, I used Python and tools like GAMS, GUROBI to build models for assortment planning and improving supply chain across 1100 stores nationwide. My expertise in building complex scalable algorithms helped me to prototype faster and get business approvals for the tradeoffs involved between decision granularity and model complexity. 

I am focused on advancing optimization methods and machine learning algorithms.

• Modeling: Machine Learning | Statistical Modeling | Math Programming | Discrete Event Simulation
• Algorithmic: Online Algorithms | Graph Algorithms | Vehicle Routing | Large Scale Nonlinear Optimization Algorithms
• Technologies: Python, C++, R, SAS, Java, FORTRAN | GUROBI, CPLEX, COIN-OR | GAMS, AMPL, SIGMA, SLAM | Oracle PL/SQL, Microsoft Transact SQL, Teradata SQL, HDFS – Hive QL.

• A Fast Tabu Search Implementation for Large Asymmetric Traveling Salesman - OPSEARCH, Springer (2012).
• Implementing Tabu Search to Exploit Sparsity in ATSP instances. W.P. No. 2008-10-02, Indian Institute of Management, Ahmedabad (2008).
• HCL Technologies: Employee First, Customer Second - Case Study UVA-OM-1366, Darden Business Publishing, University of Virginia (2008).
• Scaling Sparse Constrained Nonlinear Problems for Iterative Solvers - W.P. No. 2006-08-06, Indian Institute of Management, Ahmedabad (2006).
• Scaling Sparse Matrices for Optimization Algorithms - W.P. No. 2006-08-05, Indian Institute of Management, Ahmedabad (2006).
• Computational experience with a safeguarded barrier algorithm for sparse nonlinear programming - Computational Optimization and Applications, vol 19, pgs 107-120, Kluwer Academic Publishers (2001).
• A single server queue with cyclically indexed arrivals and service times - Queuing Systems: Theory and Applications, vol 15, pgs165-198, JC Baltzer AG, Science Publishers.
• INTOPT: an interior point algorithm for large scale nonlinear optimization - Doctoral Dissertation, The University of Texas at Austin.
• A textbook for managers on using quantitative methods - Mathematical Programming for Managers - TBD.

• Detecting wasteful data collection - US 8,825,609 · Issued Sep, (2014).
• Resource management using environments - US 8,635,624 · Issued Jan, (2014)

• Personal Interests:
  • Travel, Reading, Hiking, and supporting a Delhi non-profit Niramaya in addressing preventable blindness
• Fun Facts:
  • I go by initials GS. 
  • I have been serial entrepreneur – once in Austin, TX and twice in Silicon Valley.
  • I have done three trans-continental relocations.
  • I grew up in Kipling country – central India.
  • Along with English, I can speak four Indian languages - Hindi, Telugu, Bengali, and Bhojpuri