About
I am a final-year Ph.D. candidate in Electrical and Computer Engineering at the University of Wisconsin-Madison. My research and expertise are centered around the field of reinforcement learning with a specific focus on multi-objective reinforcement learning (MORL) and its applications in real-world scenarios. I have in-depth knowledge of reinforcement learning algorithms and have published a paper on MORL at the International Conference on Learning Representations (ICLR). This work and more can be reached through my GitHub profile. My expertise spans diverse domains of machine learning, encompassing machine learning algorithms at the edge, sustainable AI, and innovative energy harvesting solutions leveraging run-time energy management algorithms. Additionally, I have valuable experience in brain-computer interfaces and remote health applications, further enhancing my skill set.
- 8+ years of experience in embedded machine learning and signal processing,
- 5+ years of experience in reinforcement learning and its applications,
- 3+ years of expertise in energy management, encompassing convex optimization and reinforcement learning,
- Proficient in initiating, advancing, and concluding research projects, notably with DARPA and NSF,
- Authorship of 10+ conference papers at top-tier venues, underlining my research acumen and dedication
- Excellent communication and presentation skills, verbal and written, with technical and non-technical audiences, demonstrated through mentorship experiences, and academic publications.
I am actively seeking a full-time position with a strong desire to apply my expertise, enthusiasm, and track record of accomplishments to drive innovation in machine learning and artificial intelligence through involvement in cutting-edge projects.
Email me at basaklar@wisc.edu if you are interested in talking to me!
Research Highlights
DTRL: Decision Tree-based Multi-Objective Reinforcement Learning for Runtime Task Scheduling in Domain-Specific System-on-Chips
Toygun Basaklar, A. Alper Goksoy, Anish Krishnakumar, Suat Gumussoy, Umit Y. Ogras. Oral and Poster Presentation at ESWEEK 2023 [Paper]
A Self-Sustained CPS Design for Reliable Wildfire Monitoring
Yigit Tuncel, Toygun Basaklar, Dina Carpenter-Graffy, Umit Y. Ogras. Oral and Poster Presentation at ESWEEK 2023 [Paper]
PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm
Toygun Basaklar, Suat Gumussoy, Umit Y. Ogras. Accepted in ICLR 2023 and Presented in Deep Reinforcement Learning Workshop NeurIPS 2022[Paper][Code]
GEM-RL: Generalized Energy Management of Wearable Devices using Reinforcement Learning
Toygun Basaklar, Yigit Tuncel, Umit Y. Ogras. Oral and Poster Presentation at DATE 2023 [Paper]
tinyMAN: Lightweight Energy Manager using Reinforcement Learning for Energy Harvesting Wearable IoT Devices
Toygun Basaklar, Yigit Tuncel, Umit Y. Ogras. Accepted in RL4RealLife Workshop NeurIPS 2022 and tinyML Research Symposium 2022[Paper]