Sergei Akhmatdinov

ECE Ph.D. Student
University of Michigan

District Director in District 7
MI-K ‘23 - WMIAC
Tau Beta Pi

Co-Founder and Admin
Darkn.Space

✉ sakhmatd -at- umich.edu
✉ sakhmatd -at- darkn.space (XMPP)

My name is Sergei. I am a doctoral student, pursuing a Ph.D. in Electrical and Computer Engineering (ECE) at the University of Michigan, Ann Arbor. My research interests lie in embedded systems and privacy. I am currently advised by Dr. Robert Dick.

Previously, I worked in the fields of Computer Architecture and Advanced Sensors at Western Michigan University. I also have extensive experience as a tutor of college-level mathematics, computer science, and physics.

My main hobbies include electronics, microcontrollers, programming, foreign languages/cultures, and music.

I play acoustic and electric guitars, electric bass, autoharp, Arabic oud and ney.

Aside from projects listed below, my contributions to the free software community include work on the D programming language runtime and the FreeBSD operating system.

• Embedded Systems
• Infrastructure-less Communication and OppNets
• Embedded Architecture
• Security, Privacy, and Censorship Resistance

• A Novel Haptic System with Advanced Force Sensing Capabilities for Soft-Robotic Applications | FLEPS 2023 | S. Akhmatdinov; H. Dogdu; M. Haley; M. Panahi; A. J. Hanson; S. Masihi; A. H. Adineh; V. Palaniappan; D. Maddipatla; M. Z. Atashbar

  Tele-operation has seen considerable use in aerospace and medical applications. However, contemporary tele-robotic systems rely exclusively on visual feedback. We propose a haptic feedback system that would allow operators to receive touch-based feedback, increasing their control and dexterity. To address the flexibility and range issues found in modern capacitive touch sensors, we design a custom multi-layered touch sensor with cone and porous structure.

• Accurate Performance and Power Prediction for FPGAs Using Machine Learning | FCCM 2022 | Lina Sawalha; Tawfiq Abuaita; Martin Cowley; Sergei Akhmatdinov; Adam Dubs

  Calculating power consumption, execution time, and resource utilization for FPGA designs created using High Level Synthesis (HLS) tools requires a complete place & route procedure, which can take weeks or even months for some commercial designs. We propose a fast, accurate, and generalizable machine learning model to predict these design characteristics, bypassing the lengthy setup time required.

Please find my FLOSS projects on Github.

Featured projects:

• Rogueutil - Cross-platform C/C++ library for creating text-based user interfaces (TUI) and console-based games
• swege - Static WEbsite GEnerator
• sdwmbar - Simple statusbar for dwm

• 10BITS - A proof of concept Instruction Set Architecture implemented in Verilog.
• Intel i82C55A Clone - A clone of the classic Intel peripheral I/O (PIO) chip implemented in VHDL. Implements a partial subset of the original’s functionality: modes 0 and 1 on a single peripheral bus are supported.
• Conveyor belt interface - A complete interface to a conveyor belt assembly system running on an ARM STM32F429. Supports speed control, detection of the objects being moved via IR and ultrasonic sensors, emergency controls and detailed output to a graphical LCD screen.
• Gas leak detector - A gas leak detector implemented on an AVR ATTiny2313.

• Tau Beta Pi
• NASA Michigan Space Grant Consortium
• IEEE Student Member
• NSF REU
• WMU Computer Architecture and Systems Research Laboratory (CASRL)
• WMU Center for Advanced Smart Sensors and Structures (CASSS)
• KVCC Learning Center
• Free Software Foundation
• FreeBSD Foundation