Jeet Dhoriyani
Contact
E-Mail: jd825 at cornell dot edu
Jeet Dhoriyani
Cornell University
136 Hoy Road,
Ithaca, NY-14850
You can find me on Twitter, Linkedin, Github.
Please find my CV here.
Research Interests
I am interested in working on the intersection of the Machine learning, Mathematical Optimization and Quantum Computing.In my recent work, I have been applying novel decomposition techniques to solve non-linear optimization problems. These techniques have allowed me to break down large optimization problems into smaller, more manageable sub-problems, which can be solved individually and then combined to obtain an optimal solution. Additionally, I have also developed a Quanvolotional Neural Network (QVNN) for image segmentation. This is a hybrid neural network that combines the power of quantum computing with convolutional neural networks to provide high-accuracy image segmentation results. Finally, I have also applied algorithmic game theory to decision-making in transactive energy systems. This work has helped me explore the potential of game theory to solve problems related to energy markets and renewable energy systems. These projects have further strengthened my expertise in optimization, machine learning, and game theory, and I look forward to continuing to explore these fields through my research work. . More on these work is coming on the Github.
About
I am a second year M.S. Systems Engineering Student in Cornell University, fortunate to be part of PEESE Research group.
Prior to joining Cornell, I have worked at Accenture consulting as a Application Analyst. At Accenture, I was introduced to world of CRM software and Software as a Servic(SaaS), I enjoyed my tenure working on cross continental team, designing digital solutions for the client. I obtained my Bachelor's from one of the oldest engineering school of India the L.D. College of Engineering, India..
Education and Work
- 2021-2023, Masters in Science, Cornell University
- 2016-2020, Bachlor in Engineering, L.D. College of Engineering, India, .
Work
- 2021-now, Graduate Researcher, PEESE Lab
- 2020-2021, Application Analyst, Accenture Consulting
Publications
Here is a link to my Google Scholar.
Professionl Service(Conference Reviewer)
- AI4Mat-2023 NeurIPS
- 2023 IEEE Transactions on COntrol of NEtwork Systems (CONES)
- 2023 Science Advances (AAAS)
- 2023 62nd IEEE Conference on Decision and Control (CDC)
- 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME 2023)
- 2023 IEEE International Conference on Mechanical, Automotive and Mechatronics Engineering 2023
- 2023 IEEE Transactions on Automatic Control (TACON)
- 2022 American Control Conferences (ACC 2022)
- 2022 International Symposium of Automation, information and Computing (ISAIC 2022)
- 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2021)
- 2020 IEEE Region 10 Conference (TENCON)
Teaching
- Spring 2023: INFO 2950 Introduction to Data Science (TA)
- Fall 2022: INFO 5101 Learning Analystics (TA)
- Summer 2022: CS 2110 Object Oriented Programming and Data Structure (TA)
- Spring 2022: CS 5356 Building Startup Systems (TA)
- Fall 2021: SYS 5300 Six Sigma Methodology for systems Design (TA)
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