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Master of Science in Computer Engineering - Artificial Intelligence

• Thesis Title: High Resolution Neural Topology Optimization via Differentiable Physics Engine
• Defence: Achieved maximum score during defense on Oct 22, 2022 with GPA of 17.17/20.00
• IUST: This university is one of the most prestigious in the country, being in top-4 consistently.

Bachelor of Computer Engineering

• Final Project: Descreening and Rescreening of Halftone Images via Data-Driven Deep Learning Methods
• Class Rank: Graduated 3rd out of 55 with a GPA of 18.64/20.00

• Doosti, Nikan, Julian Panetta, and Vahid Babaei. "Topology Optimization via Frequency Tuning of Neural Design Representations." In Symposium on Computational Fabrication, pp. 1-9. 2021. (ACM)

• Doosti, Nikan. 2022. "Neural Design Representations." Toronto Geometry Colloquium advised by Alec Jacobson - University of Toronto. March 4, 2022. toronto-geometry-colloquium.github.io. (Length: 10 mins., Video)

Research Assistant

• Project Overview: Novel self-supevised neural method for obtaining the optimum design showcased in Topology Optimization
• Collaboration: Supervised by Dr. Vahid Babaei and collaborated with Prof. Julian Panetta from the University of California, Davis, USA.
• Interdisciplinary Learning: Successfully navigated and mastered new topics outside my primary field, such as mechanical engineering, through self-directed learning.
• Experiment Management: Managed large-scale experiments by developing customized logging solutions and using MLflow to track and report results, particularly enabling easy follow-up near deadline.
• Team Collaboration: Actively supported group members by sharing expertise in AI, particularly in implementing mathematical models with PyTorch, and optimized workflows by guiding the team in using Slurm clusters effectively.
• Commitment: Dedicated over 1500 hours to research and development, demonstrating a strong commitment to the project and its outcomes.
• Outcome: Resulted in a master's thesis and a paper that was published and presented at the ACM Symposium on Computational Fabrication 2021.

Full-time Machine Learning Specialist

• Summary: Specializing in Data-driven Decision Making for Business Optimization.
• The Problem: Implemented an AI-driven solution to address the challenge of prioritizing customers applications in the tourism sector.
• Impact: Decreased personnel error by 10\%, mitigating potential losses equivalent to 5.5 times my annual salary. Also, awarded for dedication and leadership, leading to two promotions and a 70\% salary increase within one year. Moreover, I established myself as the primary resource for onboarding and training new team members, receiving praise for my ability to simplify fundamental concepts.
• Developed a comprehensive screening process automation from customer communication to application prioritization, filtering calls based on the complexity of inquiries, reducing manual workload by 40\%.
• Oversaw the development of a proprietary data extraction and preprocessing pipeline, resulting in a 35\% reduction in poor-quality data.
• Deployed classical machine learning models alongside deep learning methods, coupled with Explainable AI techniques to prioritize applications and provide transparent reasoning for each decision.
• This experience demonstrates my ability to leverage AI technologies to optimize decision-making processes, drive significant business outcomes, and collaborate effectively with stakeholders from various backgrounds.

Head Teaching Assistant

• Supervisor: Dr. Ghasem Mirroshandel
• Taught undergraduate students Java programming language in weekly 4-hour sessions
• Designed and graded their assignments and the final project

Head Teaching Assistant

• Supervisor: Dr. Mojtaba Shakeri
• Held weekly 2-hour QA sessions and graded the assignments

Head Teaching Assistant

• Supervisor: a href="https://www.linkedin.com/in/mojtaba-moe-shakeri-b34a2b6/">Dr. Mojtaba Shakeri
• Designed programming assignments (Material)
• Held weekly 2-hour QA sessions and graded all the assignments

Mentor and Lecturer

• An Open and Free Organization For Introducing AI and Mentorship
• Held lectures around applications of AI, particularly digital image processing (slides)
• Mentored few students who were interested in artificial intelligence and its applications

Organizer and Mentor

• An Open and Free Organization For Sharing Ideas, Showcasing Projects and Mentoring Students
• Attempted to challenge the siloed culture of the university through having open scientific/general discussions
• Mentored junior students in preparation for going through M.Sc thesis process; from ideation to publishing

Member

• Official forum with +50K members and authors of the PyTorch
• A top member (15th) with 183 solutions and 566 posts (summary)
• Commended by Thomas Viehmann for insightful posts