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Mehdi Jokar is listed as Machine Learning Engineer at Superluminal Medicines Inc., based in Boston, Massachusetts, United States. AeroLeads shows a matched LinkedIn profile for Mehdi Jokar.
Mehdi Jokar previously worked as Graduate Research Assistant at Purdue University and Lead Teaching Assistant - ME270 at Purdue University. Mehdi Jokar holds Doctor Of Philosophy - Phd, Mechanical Engineering from Purdue University.
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Self-driven machine learning scientist with 6+ years of hands-on experience applying ML and DL tools to real-world problems.
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Boston, Massachusetts, Us
- Integrated ML solutions into drug discovery processes with cross-functional teams- Built ML-based drug screening pipelines on GCP, incorporating both active and passive learning- Supervised an intern in developing ML-based predictive pipelines
West Lafayette, In, Us
Mainly focused on machine learning-based scientific computing. - Collaborated on several multidisciplinary research projects, - Published 8 journal articles and 1 patent (pending), attended several conferences, - Collaborated in writing three research project proposals on novel ML-based computations and structural assessments - Mentored 3 MS and BS students to get on board with research activities. - Served as the lead teaching assistant for multiple semesters; supervised and coordinated 12+ assistants of ME270 (statics).Notable Projects:1- Developed a fundamentally new deep learning-based framework for the simulation of physical systems. Used BRNNs, LSTM, MLP, and CNN in the neural networks of the framework. A seq2seq approach was implemented to model both static and transient (time series) problems. Won 3rd place in Computational Mechcanics in EMI 2022. 2- Used deep autoencoders and CNN-based classifiers to develop a design methodology for acoustic metamaterials. The design parameters are first encoded into a latent space. Encoded data is processed via a secondary neural network to predict the metamaterial topology. 3- Utilized CLDNN and BRNN to accurately characterize the parameters of a fractional calculus model, resulting in a significantly reduced (2+ O. of magnitude) solution time compared to the existing optimization-based techniques. The project won 2nd place in Poromechanics in EMI 2022.4- Utilized Transformers (BERT NLP model) for sentiment analysis.5- Designed broadband wave-damping structures based on acoustic black holes (patent pending).In the above projects, I developed automated batch simulation codes (SLURM and PBS) and parallel computing techniques, linked MATLAB, python, and COMOSL on HPC clusters, ran numerous simulations (100k+), and generated large-scale training datasets.
West Lafayette, In, Us
Supervised and coordinated teaching assistants of Basic Mechanics I (ME270)
West Lafayette, In, Us
Supervised and coordinated teaching assistant of Basic Mechanics I (ME270)
West Lafayette, In, Us
- Fall 2021: Teaching Assistant of Basic Mechanics I (Statics - ME270) - Spring 2021: Teaching Assistant of Basic Mechanics II (Dynamics- ME274)
West Lafayette, In, Us
- Designed a broadband acoustic wave damping device via Helmholtz resonator and acoustic black holes (patent # 11514878).- Collaborated on developing a nondestructive imaging approach for identifying structural damages.- Coached 3 MS and BS students
- Developed 8+ proposals containing feasibility studies, cost estimation, building Gantt charts, defining and arranging project tasks, and execution time estimation (conversion rate ~40%). - Managed two research initiatives from incubation to delivery, resulting in 7 conference proceeding and journal publications, - Won distinguished research project award at the 24th Research Festival of the University of Tehran. - Mentored 5 junior engineers in intelligent structures and bio-inspired systems. - As a senior mechanical engineer, participated in 10+ analytical and experimental industrial research projects. Used ANSYS, COMSOL, MATLAB, and LabVIEW to design, simulate and identify intelligent mechanical systems involving different sensing/actuation mechanisms, such as strain gauges, accelerometers, DC motors, potentiometer sensors, piezoelectric, and shape memory alloy actuators.
- Designed a control system for a walking assistant robot- Collaborated in 4 research projects- Published 4 conference proceedings
Quick answers generated from the profile data available on this page.
Mehdi Jokar works for Superluminal Medicines Inc..
Mehdi Jokar is listed as Machine Learning Engineer at Superluminal Medicines Inc..
Mehdi Jokar is based in Boston, Massachusetts, United States while working with Superluminal Medicines Inc..
Mehdi Jokar has worked for Superluminal Medicines Inc., Purdue University, and Cast (Center Of Advanced Systems And Technology).
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Mehdi Jokar holds Doctor Of Philosophy - Phd, Mechanical Engineering from Purdue University.
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