Ph.D. in Computer Science | Wayne State University (December 2025)
AI-guided scheduling, reinforcement learning, and real-time systems for heterogeneous multicore and embedded platforms
I recently completed my Ph.D. in Computer Science from Wayne State University (December 2025), specializing in:
- 🧠 AI-Driven System Optimization: Energy-, thermal-, and performance-aware scheduling using hierarchical multi-agent reinforcement learning
- 🖥️ Heterogeneous Computing: ARM, x86, NVIDIA Jetson platforms (TX2, Orin NX)
- 🚀 Embedded Systems: Real-time scheduling and resource management for OpenMP DAG workloads
- 🤖 Machine Learning: Deep reinforcement learning, graph neural networks, LLM-guided resource allocation
- 💻 Hardware Design: FPGA/ASIC design, VHDL, Verilog
U.S. Permanent Resident - No visa sponsorship required
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Technical Interview Preparation
Coverage:
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Generative AI Learning
Key Topics:
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Johns Hopkins University 9-Course Program
Completed Courses:
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Professional Portfolio & Research
Featured:
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📜 Click to view certifications
| Certificate | Institution | Year | Link |
|---|---|---|---|
| 🥇 Introduction to Software Engineering | IBM | 2024 | Verify |
| 🥇 Algorithmic Toolbox | UC San Diego | 2024 | Verify |
| 🥇 Java Programming: Solving Problems | Duke University | 2022 | Verify |
| 🥇 Coding Interview Preparation | Meta | 2024 | Verify |
| 🥇 Software Developer Career Guide | IBM | 2024 | Verify |
| Certificate | Institution | Year | Link |
|---|---|---|---|
| 🏆 Generative AI with Large Language Models | DeepLearning.AI | 2024 | Verify |
| 🏆 LangChain for LLM Application Development | DeepLearning.AI | 2024 | Course |
| 🏆 Generative AI: Elevate Software Development | IBM | 2024 | Verify |
| Certificate | Institution | Year | Link |
|---|---|---|---|
| ☁️ Introduction to Cloud Computing | IBM | 2024 | Verify |
| 🐍 Python for Data Science, AI & Development | IBM | 2024 | Course |
| Certificate | Score | Year | Link |
|---|---|---|---|
| 📈 The Data Scientist's Toolbox | 99.3% | 2015 | View PDF |
| 💻 R Programming | 100.0% | 2015 | View PDF |
| 🧹 Getting and Cleaning Data | 98.0% | 2015 | View PDF |
| 📊 Statistical Inference | 100.0% | 2015 | View PDF |
| 📝 Reproducible Research | 97.1% | 2015 | View PDF |
| 📉 Regression Models | 91.7% | 2015 | - |
| 🔍 Exploratory Data Analysis | 96.7% | 2015 | - |
| 🤖 Practical Machine Learning | 100.0% | 2015 | - |
| 🌐 Developing Data Products | 96.9% | 2015 | - |
| Course | Institution | Year | Link |
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| 🤖 Machine Learning | Stanford University | 2014 | Coursera |
| 🖥️ Application of Parallel Computers | UC Berkeley | 2019 | Course |
| 🧠 Deep Learning | Iowa State University | 2020 | - |
| 🎯 High Performance Computing | Iowa State University | 2019 | - |
Data-Efficient AI-Guided Energy- and Thermal-Aware Scheduling on Heterogeneous Multicore Systems
- Wayne State University, Computer Science Department
- GPA: 4.0/4.0
- Advisor: Dr. Abusayeed Saifullah
- ICLR 2026 Workshop: ZeroDVFS - Zero-Shot LLM-Guided Autonomous Agent for Energy-Aware Resource Allocation
- IEEE RTCSA 2025: Feature-Aware Task-to-Core Allocation via Statistical Learning
- IEEE RTSS 2024 WIP: Energy and Thermal-Aware Scheduling using HMARL for OpenMP DAG Workloads
- Euromicro ECRTS 2023: Precise Scheduling of DAG Tasks with Dynamic Power Management
See full publication list at pivezhan.github.io/publications
- 🎯 Achieved 49.06% makespan reduction and 40.95% energy reduction using Hierarchical Multi-Agent RL
- 🌡️ Reduced core temperature by 5°C through feature-aware task allocation
- 🔬 Published 10+ papers in top-tier venues (RTSS, RTCSA, ECRTS, HPCC, ASAP)
- 💰 Secured NSF funding for research on AI-guided scheduling
Graduate Research Assistant (2022-2025)
- Developed HMARL framework for energy-aware scheduling on heterogeneous platforms
- Achieved state-of-the-art results on NVIDIA Jetson TX2 and Intel Core i7
- Published research in IEEE RTSS and RTCSA
Graduate Research Assistant (2021-2022)
- Architected energy-aware scheduling algorithms for DAG workloads
- Developed GNN-based scheduler for data warehouse ETL processing
- Designed FPGA architecture for event-based camera systems
Graduate Teaching Assistant (2019-2022)
- Course Instructor: CprE 381 Computer Organization (200+ students)
- Teaching Assistant: CprE 327 Advanced OOP (180+ students)
- Teaching Assistant: CprE 185 Introduction to C Programming (140+ students)
Research Intern (2020-2021)
- Optimized FPGA prototyping and RTL design for hardware accelerators
- Reduced verification latency by 15% through debugging enhancements
