Proposes a transferable SEMI-CTDE region-based multi-agent RL architecture for adaptive traffic signal control with two complementary model variants and extensive ablations.
View preprint on arXiv View code on GitHub
Proposes a transferable SEMI-CTDE region-based multi-agent RL architecture for adaptive traffic signal control with two complementary model variants and extensive ablations.
View preprint on arXiv View code on GitHub
Completed a one-week international LLM program blending theory with implementation-focused work on six projects, including ViT-from-scratch training, SigLIP+Qwen LaTeX OCR, GRPO post-training for symbolic reasoning, inference-time compute strategies, and adversarial attacks on CLIP and vision models.
View LLM Armenia projects on GitHub
Working under the supervision of Dr. Monireh Abdoos on SEMI-CTDE region-based multi-agent deep reinforcement learning architectures for adaptive traffic signal control in SUMO. This line of work has resulted in a manuscript currently under review (see Publications).
Awarded silver medal in the highly competitive national Olympiad, demonstrating strong problem-solving skills in physics and mathematics.
Selective Olympiad summer camp for the top 40 candidates nationwide, combining advanced astronomy and physics instruction with frequent exams and problem-solving workshops used to determine final medal rankings.
Participated in the LLM Armenia 2025 Summer School, blending theoretical concepts and practical projects in machine learning. Key projects included ViT-from-scratch training, SigLIP+Qwen LaTeX OCR, GRPO post-training for symbolic reasoning, inference-time compute strategies, and adversarial attacks on CLIP and vision models.
View LLM Armenia projects on GitHub
Implemented an end-to-end emotion recognition pipeline: fine-tuned a pre-trained DistilBERT model on a custom emotion dataset, then used its embeddings as input to an MLP classifier with per-label threshold tuning to improve classification performance. The project includes dataset preprocessing, hyper-parameter search, and a simple real-time inference.
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Developed a sequence of assignments and a final project for a mobile robotics course, covering kinematics and wheel-velocity control, localization and hallway mapping, local navigation with Bug algorithms, and an indoor mapping and navigation project where a Mavic platform and TurtleBot perform wall-following, door detection, and particle-filter-based localization to reach target doors.
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Implemented two AI agents for the Connect Four board game. The first uses a minimax search with alpha–beta pruning and configurable depth to control playing strength; the second is a tabular Q-learning agent trained via large-scale self-play. The project contrasts search-based and reinforcement-learning approaches to decision making in a fully observable game.
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Built a tiny 2D platformer in Unity with a responsive run/jump controller, simple enemies with health bars, and collectible hearts. The game features multiple themed biomes (forest and snow) with a smooth transition and a clean project structure, making it a reusable template for future sidescroller ideas.
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Teach advanced Mathematics and Physics to high-performing high school students preparing for the National Astronomy & Astrophysics Olympiad, with a strong focus on rigorous problem solving and competition strategy.
Over the years, I have had the privilege of teaching students who later achieved national and international medals in Astronomy & Astrophysics Olympiads through their own hard work and dedication.