Mohammad Pivezhandi

Curriculum Vitae

Summary

Assistant Professor (Teaching) of Computer Science at Wayne State University and Researcher in the Vehicle Health group at the General Motors R&D Center. Ph.D. in Computer Science (Wayne State University, December 2025, GPA 4.0/4.0) specializing in AI-guided energy- and thermal-aware scheduling, reinforcement learning, and reconfigurable computing. First-author and co-author of 10+ papers including Ph.D. dissertation and ArXiv preprints in top-tier venues (e.g., IJCAI-ECAI, RTSS, RTCSA, ECRTS). Proficient in Python, TensorFlow, PyTorch, VHDL, and FPGA design, with extensive research and teaching experience in academia and industry.

U.S. permanent resident (green card). No visa sponsorship required.

Experience

Assistant Professor (Teaching), Computer Science — Wayne State University, Detroit, MI (Aug 2026–Present)

  • Full-time, non-tenure-track faculty appointment in the Department of Computer Science, teaching within the online Artificial Intelligence degree program.
  • Instructor for Software Engineering (CSC 4110) and AI Literacy (CSC 1001), Fall 2026.
  • Contributing to curriculum development, assessment, student recruitment, and departmental service.

Researcher, Vehicle Health Group (Contractor) — General Motors R&D Center, Warren, MI (Apr 2026–Present)

  • Developing AI/ML-based solutions for vehicle health management and predictive diagnostics in energy and propulsion systems at the GM Research & Development Center.
  • Applying physics-based modeling and machine learning techniques to analyze large-scale vehicle telemetry data for fault detection and performance optimization.
  • Continuing on a reduced, part-time schedule since August 2026, concurrent with the Wayne State University faculty appointment.

Graduate Research Assistant, Computer Science — Wayne State University, Detroit, MI (2022–2025)

  • Engineered a Hierarchical Multi-Agent Reinforcement Learning (HMARL) framework for energy- and performance-aware scheduling of OpenMP DAG workloads on heterogeneous multicore platforms (NVIDIA Jetson TX2, Intel Core i7), achieving 49.06% makespan reduction and 40.95% energy reduction compared to state-of-the-art multi-agent baselines; published as RTSS 2024 WIP.
  • Designed a statistical learning framework using Random Forest, backward stepwise regression, and Pearson correlation for feature-aware task-to-core allocation, reducing energy by 10% and core temperature by 5°C; published at RTCSA 2025.

Graduate Research Assistant, Computer Science — Iowa State University, Ames, IA (2021–2022)

  • Architected energy-aware scheduling algorithms for DAG-based inputs on Intel Xeon processors in data-processing clusters, improving job completion time by 15% via a dynamic resource allocation simulator; published at PDCAT 2021.
  • Developed a reinforcement learning-based scheduler using Graph Neural Networks (GNNs) for high-volume ETL processing in data warehouse systems, achieving up to 15% improvement in job completion time; published at PDCAT 2021.
  • Designed an FPGA-based architecture for histogram generation to support event-based camera optical flow calculation, reducing time encoding from 32 to 7 bits with ~3% loss in histogram accuracy; published at ASAP 2020.

Research Intern, Full-Stack Hardware Accelerator Design — Moffett Systems, Inc., Los Altos, CA (2020–2021)

  • Optimized FPGA prototyping, RTL design, compiler development, firmware, and runtime for hardware accelerators, reducing verification latency by 15% through debugging and bring-up enhancements.

Graduate Teaching Assistant, Electrical and Computer Engineering — Iowa State University, Ames, IA (2019–2022)

  • Mentored 180+ undergraduate students in Advanced Object-Oriented Programming (CprE 327, Fall/Spring 2020), teaching algorithms, data structures, and advanced C programming through tutoring sessions and exam proctoring.
  • Guided 140+ undergraduate students in Introduction to C Programming (CprE 185, Fall 2021), covering pointers, memory management, and file I/O, enhancing comprehension via weekly tutoring sessions.
  • Served as course instructor for Computer Organization (CprE 381, Spring 2022, 200+ undergraduate students), teaching 32-bit pipelined MIPS processor implementation in VHDL and Assembly, developing course materials and managing all instructional responsibilities.

FPGA/ASIC Design Researcher — Mashhad Researchers Center, Mashhad, Iran (2015–2018)

  • Developed high-throughput matrix inversions for MIMO wireless applications using the Gauss-Jordan algorithm on FPGA, improving processing speed by 20%.
  • Implemented fault-tolerant systems on FPGA using HDL and SystemC, achieving 99% reliability through MATLAB-based simulations.
  • Optimized AES cryptography algorithm on Spartan-6 FPGA with RTL design, reducing area by 12%; simulated using ActiveHDL and ISE Design Suite.

Graduate Research and Teaching Assistant, Digital Electronics — Shahid Beheshti University, Tehran, Iran (2013–2015)

  • Designed a low-power, high-frequency ASIC layout for an 8-bit multiplier using pseudo-nMOS and pseudo-pMOS gates, reducing power consumption by 18%.
  • Developed statistical-based models for CNT-FET applications using support vector regression and random forest, achieving 9% error for off-state current; published in Springer J. Comput. Electron. 2017.
  • Designed an ASIP for CORDIC-based DFT and DCT algorithms, reducing gate count by 84% for DFT and 86% for DCT; published at ICCKE 2016.
  • Built a statistical-based neural network for human activity recognition, achieving over 99% accuracy; published in Int. J. Comput. Appl. 2015.
  • Taught Machine Learning course for the first time in the department to 50+ undergraduate and graduate students, developing all lecture content, assignments, and course materials using MATLAB and Python from scratch.

Education

Doctor of Philosophy (Ph.D.), Computer Science — Wayne State University, Detroit, MI (2022–2025) CGPA: 4.0/4.0 Dissertation: Data-Efficient AI-Guided Energy- and Thermal-Aware Scheduling on Heterogeneous Multicore Systems (December 2025) — PhD-Thesis-Public

Master of Science (M.Sc.), Computer Science/Engineering — Iowa State University, Ames, IA (2019–2022) CGPA: 3.76/4.0 Thesis: Toward Real-Time Energy-Aware Automation of Resource Scheduling Using Reinforcement Learning

Master of Science (M.Sc.), Digital Electronics — Shahid Beheshti University, Tehran, Iran (2013–2015) CGPA: 4.0/4.0 Thesis: Statistical Analysis, Design, and Implementation of Artificial Neural Networks for Human Activity Recognition Task (Nominated as Best Research in ECE Department)

Bachelor of Science (B.Sc.), Electronic Engineering — Ferdowsi University of Mashhad, Mashhad, Iran (2008–2013) Last Two Semesters: 16.68/20 Thesis: Design and Implementation of a Mobile Communication System Using Microcontrollers (Nominated as Best Bachelor’s Final Project)

Publications

Ph.D. dissertation, 4 ArXiv preprints, 2 journal articles, and 9 conference papers. The complete list is on the Publications page.

Honors and Service

  • Aug 2026 — Presented GraphPerf-RT at the International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2026), Special Track on AI4Tech: AI Enabling Critical Technologies, Bremen, Germany.
  • May 2025 — Awarded a travel grant to attend the IEEE Real-Time Computing and Applications Symposium (RTCSA) in Singapore, recognizing contributions to energy-aware scheduling research.
  • 2022–2026 — Invited as peer reviewer for prestigious journals and conferences, including ACM Transactions on Embedded Computing Systems (TECS), Conference on Neural Information Processing Systems (NeurIPS 2026), Association for the Advancement of Artificial Intelligence (AAAI 2026), and Artificial Intelligence and Statistics (AISTATS). Served as TPC member in International Symposium on Parallel and Distributed Processing with Applications (ISPA) and International Wireless Communications and Mobile Computing Conference (IWCMC) 2026 Machine Learning Symposium.
  • 2022–2025 — Secured National Science Foundation (NSF) funding for research on AI-guided energy- and thermal-aware scheduling for heterogeneous multicore systems.
  • 2016–2026 — Published as first or second author in prestigious conferences, including IJCAI-ECAI, RTSS, RTCSA, ECRTS, HPCC, PDCAT, ASAP, and ICCKE.
  • Sep 2018 — Received Ph.D. admission offers from top universities in the USA, Europe, Australia, Canada, and Iran.
  • Sep 2015 — M.Sc. Thesis nominated as Best Research in the Shahid Beheshti University ECE Department.
  • Sep 2013 — Senior design project nominated as Best Bachelor’s Final Project at Ferdowsi University of Mashhad.
  • Aug 2008 — Ranked in the 95th percentile in International Physics and Mathematics exam.
  • Aug 2008 — Ranked in the 99th percentile in National Azad University entrance exam in Physics and Mathematics.

Skills

  • Programming: MATLAB, Python, C, C++, Java, MIPS Assembly, Shell, R
  • ML/AI Frameworks: TensorFlow, PyTorch, CUDA, OpenCV, OpenMP, MPI, PGAS
  • Hardware Design: VHDL, Verilog HDL, SystemC
  • Simulation Tools: Proteus, ModelSim, Active HDL, Spice
  • CAD/EDA: Virtuoso, Proteus, Altium Designer, OrCAD, Microsoft Visio
  • Productivity: LaTeX, Microsoft Office, Eclipse, NetBeans, Vivado HLS, Vivado HLx, AMS, Quartus, Unix, Git, Slack
  • Languages: English (Fluent), Persian (Native)

Courses

  • Deep Learning (Iowa State University, A, Dec 2020)
  • Computational Perception (Iowa State University, A, May 2020)
  • High Performance Computing (Iowa State University, A, Dec 2019)
  • Application of Parallel Computers (University of California, Berkeley, A, May 2019)
  • Probabilistic Methods and Algorithms (Iowa State University, A, May 2019)
  • Linear Integrated Circuit Designs (Shahid Beheshti University, 17.25/20, Mar 2015)
  • Semiconductor Devices I (Shahid Beheshti University, 18.2/20, Mar 2015)
  • Application Specific Instruction Set Processor Designs (ASIP) (Shahid Beheshti University, 16.5/20, Aug 2014)
  • Digital Image Processing (Shahid Beheshti University, 16.62/20, Aug 2014)
  • VLSI Circuits Design (Shahid Beheshti University, 18.6/20, Mar 2014)
  • Automatic Digital Circuit Designs with VHDL (Shahid Beheshti University, 18/20, Mar 2014)

Certificates

Hobbies

Aerial Shooting, Guitar Playing, Chess, Cooking, Running, Swimming. More on the Hobbies page.

References

Available upon request.