News Syed Rakin Ahmed

I was inducted into Forbes 30 Under 30 US 2026, in the Healthcare category, from over 10,000+ nominations, for my 'research aimed towards creating AI models to help both diagnose cancer and create more precise treatments for it'.

I was inducted into the Alpha Omega Alpha (AOA) medical honor society, in recognition of my academic achievements, scholarship, leadership, professionalism and service.

My work on novel distance metric generation for assessing out-of-distribution performance of AI oncology models for clinical deployment was accepted in ASTRO 2025.

My work on generalizable deep learning models for image quality assessment was published in Nature Sci Rep.

My work on generating, validating and deploying an end-to-end AI pipeline for cervical cancer screening was featured on an NCI.gov press release

Four manuscripts from our work on uncertainty and generalizability of AI models were presented in MICCAI 2024, and published in the corresponding journals: MedAGI 2024, UNSURE 2024, PILM-AIPAD 2024, FAIMI-EPIMI 2024.

My work on assessing generalizability of deep learning models for cancer detection was published in PLOS Digital Health, while additional work on AI for cervical cancer screening was presented at IPVC 2024.

I graduated Sigma Xi with my PhD in Biophysics from Harvard, as part of the University Wide Commencement, Harvard Medical School Commencement, and Harvard Graduate School of Arts and Sciences Commencement 2024

I successfully defended my doctoral dissertation titled 'Generating Clinically Translatable AI Models for Cancer Diagnostics', after 3.5 years of PhD thesis work at Harvard.

I was awarded the Mind Brain Behavior (MBB) Graduate Student Award for 2023-2024, sponsored by the MBB Interfaculty Initiative at Harvard University, as well as the Fellowship in Values Engagement (Intellectual Vitality Fellow) for 2023-2024, sponsored by the Edmond & Lily Safra Center for Ethics at Harvard University, following extremely competitive selection processes.

My work on clinically translatable deep learning for cancer diagnosis was published in Nature Scientific Reports, on generalizable deep neural networks for image quality classification was posted to Research Square, on deep learning for immune phenotype prediction from breast cancer histopathology was presented at the 38th Annual AAAI Conference on Artificial Intelligence 2024 and posted to arXiv, and on deep-learning based automated volumetric measurement of meningioma burden was presented at the SNO 28th Annual Meeting and AI Cures Conference 2024.

Four manuscripts from my work on AI for cervical cancer screening were published in medRxiv, Cancer Epidemiology, JNCI, and in eLife respectively.

I was invited as a featured speaker at the Harvard Biophysics Annual Retreat 2023, and the 3rd Annual Dartmouth Radiation Oncology Research Retreat 2023, presenting a talk titled "Generating clinically translatable models for cancer diagnostics".

Five manuscripts and abstracts from my work on AI and computational methods for brain tumor diagnostics were published in Neuro-Oncology, in Volume 26 of the Annual Reviews of Biomedical Engineering, in the Machine Learning for Healthcare Conference (MLHC) 2023, in the Radiological Society of North America (RSNA) Annual Meeting 2023, and in the Society for NeuroOncology 28th Annual Meeting, respectively.

My work on algorithmic language lateralization from resting-state functional MRI was published in the Journal of Neuroimaging.

We presented our work on AI and cervical cancer screening at the International Papillomavirus Conference (IPVC) 2023, as well as to the Gates Foundation and WHO (funders) in the Annual Meeting in Washington, DC.

My work on designing reproducible and clinically translatable deep neural networks was posted to medRxiv.

Our work on assessing statistical methodology errors in Radiomics-ML research was published in Radiology together with an accompanying editorial.

I was invited as a featured speaker at the National Collegiate Research Conference (NCRC) 2022, and in several "Navigating medicine as an FGLI student" sessions sponsored by the Harvard Office of Career Services (MCS).

I presented my work on improving clinical deployability of AI models at the Radiological Society of North America (RSNA) Annual Meeting 2022.

I co-authored a book chapter on opportunities and challenges of DL in brain lesions, published in the Lecture Notes in Computer Science book series.

I presented my work on test performance estimation of unlabelled data using conformal predictions at the International Conference on Machine Learning (ICML) 2022.

I presented my work on improving repeatability of AI models at the Medical Imaging with Deep Learning (MIDL) Conference 2022.

Our review on AI applied to musculoskeletal oncology was published in Skeletal Radiology.

I was ranked in the top 12% among >1500 participants in RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2021, in the Brain Tumor Radiogenomic Classification task.

Our work on systemic coagulation activation in brain tumor patients was published in the Journal of Neuro-Oncology.

I received a 260 on the USMLE Step 1 ('first part of medical licensing') exam, placing me in the top 4% of all examinees.

I presented my work on language lateralization in resting state fMRI at the American Society of Neuroradiology (ASNR) 58th Annual Meeting 2020, published in its proceedings.

I was awarded the Medical Student Research Fellowship at Memorial Sloan Kettering Cancer Center (MSKCC) for Summer 2019.

I was awarded high honors on my undergraduate thesis, and graduated Phi Beta Kappa, Tau Beta Pi, and Magna Cum Laude, with 4 citations for academic excellence.

My work on radiotherapy-induced Cherenkov luminescence imaging in a body phantom was published in the Journal of Biomedical Optics.

Our work on coagulation activation in brain neoplasms was published in the Blood journal in relation to the 59th American Society of Hematology (ASH) Annual Meeting and Exposition 2017.

I was awarded the Class of 1866 Prize for Oratory.

I captained Dartmouth at World Universities Debating Championship (WUDC) 2016 in Thessaloniki, Greece