Tegg Sung Email & Phone Number

San Diego, Ca, Us

United States

- Co-led neural combinatorial optimization research for real-world problems in chip scheduling, network communication, and IoT devices.- Designed and implemented a novel communication framework using mixed integer linear programming.- Contributed to multi-UAV flight coordination research using multi-agent reinforcement learning.- Drafted 5+ research proposals on topics including object localization, combinatorial optimization, and robust AI techniques against adversarial attacks.

* Dynamic Resource Manager for Domain Focused Advanced Software-Reconfigurable Heterogeneous System on Chip program (DSSoC) (DARPA BAA HR001117S0055)- Led the team in problem analysis and solution development for reconfigurable heterogeneous systems.- Designed a neural chip scheduler for hierarchical jobs and heterogeneous resources using reinforcement learning and graph neural networks.- Published findings in venues such as ICML workshops and SCI(E)-indexed journals.* Alpha-Dogfight Trials (ADT / DARPA challenge)- Developed a hierarchical goal-finding agent using Hindsight Experience Replay for a fighter jet simulation.- Contributed to goal-oriented reinforcement learning research in high-dimensional environments.

Korea

- Enhanced and reproduced the House3D RoomNav project, optimizing its navigation capabilities using reinforcement learning techniques.

Jeju, South Korea

- Selected from 562 applicants across 55+ countries (4% acceptance rate) for a Google-sponsored program.- Led a team to design a proposal architecture integrating self-attention, DDPG, and NerveNet, outperforming baseline methods.- Published findings at the NeurIPS Deep RL workshop.- Gained hands-on experience with Google Cloud Platform, TPU, and TensorFlow’s eager mode.

Kwangwoon University

- Assisted in ‘Design and Simulation in Embedded System’ and ‘Computational Thinking’- Instructed advanced Linux tools for over 60 undergraduates on a weekly basis and completed entire Q&A sessions in person and online

Yuseong-Gu, Daejeon, Korea

* Development of document mining technology for analyzing gene-annotation-disease association - Surveyed document mining advancement for gene-annotation-disease association analysis - Researched and enhanced bio-literature mining system using Java and machine learning - Conducted experimental tests, analyzed machine learning based named entity recognition system, and published research paper

Gangneung, South Korea

- Served as a combat medic in the military.

Concurrent Master'S And Ph.D., Electrical, Electronics And Communications Engineering, 4.4/4.5

Bachelor Of Engineering (B.E.), Electrical And Electronics Engineering, 3.48/4.5