Masters Student | Machine Learning

The Pennsylvania State University

Technical Skills: Python, PyTorch, Latex, MATLAB, C/C++, Mathematica

Education

• M.S., Electrical Engineering and Computer Science

  The Pennsylvania State University (December 2024)

• B.Tech, Electronics and Communication Engineering

  Jalpaiguri Government Engineering College (June 2022)

Work Experience

Machine Learning Engineer (R&D) @Eriez (_Jan 2025 - present)

• Develop machine learning, deep learning, and digital signal processing (DSP) algorithms for real-time sensing and detection in industrial processing systems.
• Designed and implemented multi-modal deep learning models by integrating vision and multi-sensor time series data for advanced process diagnostics.
• Lead research initiatives on fine-tuning large language models (LLMs) for secure, on-premise deployment in internal tools supporting marketing and finance applications.
• Collaborate with Penn State University to develop domain-informed classification and forecasting models tailored to industrial environments.
• Working under the supervision of Dr. Ankit Tyagi

Machine Learning Engineer (Intern) @Eriez (May 2024 - Jul 2024)

• Conducted data-collection, pre-processing, and modeling for developing novel domain-enriched classification models for identifying metal contaminants for industrial metal detection.
• Developed Physically-informed learnable Denoisers for curating inputs from noisy time-series data.
• Worked under the supervision of Dr. Ankit Tyagi and Dr. Vishal Monga

Research Experience

Graduate Research Assistant @PennState (Jan 2024 - Dec 2024)

• Used LSTM and Attention-based architectures on temporal physical features for Multiple Classification-based tasks.
• Worked under the supervision of Dr. Vishal Monga

Graduate Research Assistant @PennState (May 2023 - Dec 2023)

• Worked on the comparative study of Deep Learning based surrogate models vs Differential Surrogate Models.
• Built Physics-based models that utilize NeuralODE to effectively model and solve dynamic systems.
• Worked under the supervision of Dr. Daniel Kifer and Dr. Chaopeng Shen

Undergraduate Research Internship @IIT Guwahati (Mar 2021 - Oct 2021)

• Worked on a project based on employing multiple antenna diversity to simulate OFDM and methods effective in reducing PAPR in the system.

Undergraduate Research Internship @BITS Pilani (Apr 2021 - Sep 2021)

• Evolved an extensive study on the performance of a UWOC channel considering Generalised Gamma Fading by computing closed-form expressions for different statistical parameters under the integrated effects of oceanic turbulence and pointing errors and verifying the results through Monte-Carlo simulation.
• Authored a paper on this novel approach which is published at the 2022 IEEE 95th VTC.

Undergraduate Industrial Training @Shyama Prasad Mukherjee Port Trust (Sep 2020 - Oct 2020)

• Received technical and operational exposure to several industrial-grade instruments and systems used for the purposes of navigation, measurement, traffic control, and security in the Kolkata Port.
• Comprehended working principles behind Acoustic Doppler Current Profiler(ADCP), Differential Global Positioning System(DGPS), Vessel Traffic Management System(VTMS) and RFID-based Port Access Control System.

Teaching Experience

Graduate Teaching Assistant @PennState (Jan 2023 - May 2023)

• Taught a course(EE 453) designed to introduce the fundamentals of digital signal processing. The emphasis was on analysis tools, the design of digital filters, and on the computation of the DFT.

Graduate Teaching Assistant @PennState (Aug 2022 - Dec 2022)

• Taught a course on the introduction to neural nets(EE 456) providing experiences in identifying the best types of NNs for a particular task, developing and applying them to solve difficult problems.

Publications

• Suhrid Das, Ankit Tyagi, Vishal Monga: Towards Developing Frequency Robustness via Domain Enriched AI for Industrial Metal Detection. IEEE Sensors Conference 2025. (Accepted)

• Suhrid Das, Ankit Tyagi, Vishal Monga: Physically-Enriched Product Adaptive Deep Networks for Industrial Metal Detection. IEEE Sensors Journal. DOI: 10.1109/JSEN.2025.3562705

  Link

• Suhrid Das, Ziyaur Rahman, S. M. Zafaruddin: Optical Wireless Transmissions over Multi-layer Underwater Channels with Generalized Gamma Fading (2022). DOI: 10.1109/VTC2022-Spring54318.2022.9861003

  Link

• Suhrid Das, Shankha Shubhra Mukherjee, Sudip Mandal: Application Of Chaotic Neural Network In Cryptography (2022). DOI: 10.5120/ijca2022922133

  Link

References

• Vishal Monga

  Professor, School of Electrical Engineering and Computer Science, The Pennsylvania State University, State College Email: vum4@psu.edu Phone: +1-814-863-1267

• Ankit Tyagi

  R&D Manager – Electrical and Software Engineering, Eriez Manufacturing, Erie, PA Email: atyagi@eriez.com Phone: +1-631-561-8522

• Daniel Kifer

  Professor, Computer Science and Engineering, The Pennsylvania State University, State College Email: duk17@psu.edu Phone: +1-814-863-1187

• Chaopeng Shen

  Professor, Civil and Environmental Engineering, The Pennsylvania State University, State College Email: cxs1024@psu.edu Phone: +1-814-863-5844