Prof. Amit Meller Appointed as Dean of Biomedical Engineering
We are proud to announce that, as of August 1, 2026, Prof. Meller has officially assumed the role of Dean of the Faculty of Biomedical Engineering at the Technion – Israel Institute of Technology.
As Dean, Prof. Meller looks forward to promoting excellence in education, strengthening collaborations with industry and research hospitals, and advancing biomedical engineering research to improve human health.
We congratulate Prof. Meller on this well-deserved appointment and wish him great success in his new role.
Read the faculty’s LinkedIn post.
Dr. Neeraj Soni Joins MIT and the Broad Institute
We are excited to share that Dr. Neeraj Soni, who completed his Ph.D. in our lab at the Technion, has joined the Massachusetts Institute of Technology (MIT) Department of Chemistry and the Broad Institute as a postdoctoral researcher in Prof. Sam Peng’s laboratory.
In his new role, Neeraj will focus on developing next-generation technologies for ultra-long-term tracking of receptor molecules, enabling to monitor molecular dynamics in living systems over extended timescales.
Before his departure, we celebrated Neeraj with a farewell breakfast and wished him success in his new position.
Congratulations to Neeraj on this exciting milestone! We wish him continued success in his research and all the best in this new chapter of his scientific career.
Ali Kaiyal presented his research in a faculty seminar!
In his seminar, Ali, an MSc student, shared his work on deep learning-based classification of single proteins using nanochannel fluorescence sensing data. He presented a novel machine learning framework that analyzes the rich optical and physical trajectories generated as individual proteins pass through a nanochannel, enabling direct protein identification from raw sensing data.
Ali’s approach is built around a custom hybrid neural network architecture, MaskedInceptionTST, designed to handle variable-length sequences, class imbalance, and cross-session generalization. The model also addresses the challenge of identifying previously unseen protein classes by recognizing when an input does not belong to any class encountered during training.
This work lays the foundation for intelligent, data-driven single-molecule protein identification, with strong potential for fast, accurate, and noninvasive sensing platforms for future biomedical applications.
Great work, Ali!
New Publication: Classification of Colorectal Cancer cfDNA Using 3 nm Nanopores and Machine Learning
In the article we present a label- and amplification-free approach for classifying cell-free DNA (cfDNA) using ultra-small (~3 nm) solid-state nanopores paired with high-bandwidth electronics. By recording the ionic current signatures of individual cfDNA molecules, we capture biophysical information preserved in native, unmodified DNA.
To decode these signals, we developed a hybrid CNN-Transformer machine learning model that processes raw time series current, achieving ~95% accuracy in distinguishing healthy from colorectal cancer-derived cfDNA. This work establishes a proof-of-concept for rapid, low-volume cfDNA profiling as a potential point-of-care framework for cancer diagnostics.
Check our new paper in J. of Nanobiotechnology Journal about optipore sensing for single molecule analyses
In our latest paper, we present optipore sensing — a new approach that combines solid-state nanopores with optical measurements for improved single-molecule detection. By integrating electrical and optical signals, this method enables more accurate analysis of DNA, proteins, and other biomolecules.
This work highlights recent advances in electro-optical nanopore technologies and their potential for future diagnostic and biosensing applications.
Prof. Amit Meller Won the 2025–2026 Herschel Rich Innovation Prize
Congratulations to Prof. Amit Meller on receiving the 2025–2026 Herschel Rich Innovation Prize. The award recognizes his outstanding innovation and impactful research.
We are happy to celebrate this recognition and look forward to more achievements from Prof. Meller and the team.